System

Abstract

A system is provided.SOLUTION: The system includes a school information management means which unitarily manages student information and enables teachers to access the information, an online learning means which digitally provides teaching materials and enables the students to learn online, a shared document management means which enables the teachers to share the teaching materials and teaching plans with each other, and an electronic scoring means which automatically scores examination questions and problems.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Long working hours for teachers have become a serious problem in modern school education. It is becoming increasingly difficult for teachers to find time for individual instruction and self-study while juggling a wide range of tasks, including managing student attendance and grades, creating and sharing teaching materials, and grading exam questions and assignments. This increased burden has led to increased mental stress for teachers, a decline in the number of people aspiring to become teachers, and a serious teacher shortage. This has led to a decline in the quality of education and a negative impact on society as a whole. The present invention aims to provide a platform that reduces the burden on teachers and improves the efficiency of their work. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides the following means.

[0006] A school information management system that centrally manages student information and makes it accessible to teachers;

[0007] Online learning means to provide educational materials digitally and enable students to learn online;

[0008] A shared document management tool that allows teachers to share teaching materials and lesson plans with each other,

[0009] an electronic marking means for automatically marking exam questions and assignments;

[0010] This platform will reduce the workload of teachers and cut down on overtime. It will also allow teachers to secure time for individual instruction and their own study. This will reduce the burden on teachers and improve the quality of education.

[0011] "Student information" refers to a set of information about individual students, such as their grades, attendance information, and history.

[0012] "Centralized management" is a method of managing multiple pieces of information and data in a unified manner in one place.

[0013] A "teacher" is a professional who provides educational activities to students at a school.

[0014] "Teaching materials" are learning materials or teaching materials used for educational purposes.

[0015] "Online learning" refers to a method in which students access course materials and assignments and carry out learning activities via the Internet.

[0016] A "shared document" is a document or file that can be used, viewed, and edited jointly by multiple users.

[0017] A "lesson plan" is a plan or lesson plan that a teacher creates to conduct a lesson.

[0018] "Automatic scoring" is a method of automatically evaluating and scoring test questions and assignment answers using a machine or program.

[0019] A "platform" is a fundamental system that integrates and provides multiple functions and services.

[0020] A "system" is a collection of equipment and software that functions by combining different elements and means. [Brief explanation of the drawings]

[0021] [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

[0022] 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.

[0023] First, the terms used in the following description will be explained.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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."

[0029] [First embodiment]

[0030] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0031] 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.

[0032] 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).

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] 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."

[0042] This invention relates to a system that includes the centralized management of student information, provision of digital teaching materials, shared document management, and electronic grading functions. This system consists of three main elements: a server, a terminal, and a user. We will explain in detail how each element works together and how the invention is specifically implemented.

[0043] A centralized student information management system

[0044] server

[0045] The server centrally manages student grades, attendance information, and records, making them accessible to teachers, allowing them to quickly obtain the information they need.

[0046] For example, if a teacher wants to check the grades of a specific student, a request is sent from the terminal. The server retrieves the grades of the student from the database and returns them to the teacher's terminal.

[0047] Online Learning Platform

[0048] server

[0049] The server provides digital learning materials and assignments, making them accessible to users (teachers and students). Teachers upload learning materials, and students can view and study them online.

[0050] Example: When a teacher uploads a new assignment, the server stores the data and students download it to study.

[0051] Terminal

[0052] The terminal provides an interface for the user to access the server and upload or download educational materials.

[0053] Example: A student logs into an online learning platform from their home device, downloads materials provided by their teacher, and studies.

[0054] Shared Document Management System

[0055] server

[0056] The server provides a system that allows teachers to share teaching materials and lesson plans with each other, and stores and updates shared documents, making it easier for teachers to share teaching materials with each other.

[0057] Example: Teacher A uploads a lesson plan he created to the server, and Teacher B can also view and download the plan.

[0058] Electronic Scoring System

[0059] server

[0060] The server automatically grades submitted exam questions and assignments and stores the results in a database, significantly reducing the grading workload for teachers.

[0061] Example: When a teacher uploads exam answers scanned on a device, the server processes the answers in an electronic scoring system and returns the scoring results to the teacher's device.

[0062] Terminal

[0063] The device provides an interface for teachers to upload exam and assignment answers and view the automatically graded results.

[0064] Example: A teacher uses a device at home to scan answer sheets, send them to a server, and receive the results of automatic grading.

[0065] Example

[0066] Example 1: Student Grade Management

[0067] 1. Send a request to view student grades from the teacher's device.

[0068] 2. The server retrieves the student's grades from the database.

[0069] 3. The server sends the grade information to the teacher's terminal, where the teacher can view the information.

[0070] Example 2: Online classes

[0071] 1. The teacher uploads the teaching materials from the device to the server.

[0072] 2. The server stores the learning materials and makes them accessible to students.

[0073] 3. Students download the learning materials to their devices and proceed with their studies.

[0074] Example 3: Electronic marking

[0075] 1. The teacher sends the exam answer sheet from the terminal to the server.

[0076] 2. The server uses an electronic scoring system to automatically score the tests.

[0077] 3. The server stores the grading results in a database and sends them to the teacher's device.

[0078] The system of the present invention significantly reduces the workload of teachers and enables them to effectively utilize the expertise of each teacher, thereby enabling them to provide higher quality education.

[0079] The processing flow will be explained below.

[0080] A centralized student information management system

[0081] Process flow: View student grades

[0082] Step 1:

[0083] A user (teacher) sends a request from a terminal to view the grades of a specific student.

[0084] Step 2:

[0085] The terminal forwards the request to the server.

[0086] Step 3:

[0087] The server accesses the database and obtains the grade information of the student.

[0088] Step 4:

[0089] The server transmits the acquired score information to the terminal.

[0090] Step 5:

[0091] The terminal displays the received grade information on the screen, and the user (teacher) checks it.

[0092] Online Learning Platform

[0093] Process flow: Uploading and viewing teaching materials

[0094] Step 1:

[0095] The user (teacher) selects the teaching material file and sends an upload request from the terminal.

[0096] Step 2:

[0097] The terminal uploads the selected educational material file to the server.

[0098] Step 3:

[0099] The server stores the received teaching material file in a data storage.

[0100] Step 4:

[0101] The server sends a notification to the device that the upload is complete.

[0102] Step 5:

[0103] A user (student) sends a request to access the online learning platform from a terminal.

[0104] Step 6:

[0105] The terminal accesses the server and sends a request to acquire a list of available learning materials.

[0106] Step 7:

[0107] The server retrieves a list of available learning materials from the database and sends it to the terminal.

[0108] Step 8:

[0109] The terminal displays a list of teaching materials on the screen, which the user (student) can view.

[0110] Shared Document Management System

[0111] Process flow: Sharing lesson plans

[0112] Step 1:

[0113] The user (teacher) selects a lesson plan document and sends a sharing request from their device.

[0114] Step 2:

[0115] The device uploads the document to the server.

[0116] Step 3:

[0117] The server saves the document in a shared folder and updates the sharing settings.

[0118] Step 4:

[0119] The server sends a notification of completion of sharing to the terminal.

[0120] Step 5:

[0121] Another user (teacher) sends a request from their device to find a shared lesson plan document.

[0122] Step 6:

[0123] The terminal accesses the shared folder and sends a request to the server to search for the document.

[0124] Step 7:

[0125] The server retrieves the document from the shared folder and sends it to the terminal.

[0126] Step 8:

[0127] The terminal displays the received document on the screen, and the user (teacher) views it.

[0128] Electronic Scoring System

[0129] Process flow: Automatic grading of assignments

[0130] Step 1:

[0131] The user (teacher) scans the students' answer sheets and sends a request from the terminal to upload them to the electronic marking system.

[0132] Step 2:

[0133] The device uploads the scanned image of the answer sheet to the server.

[0134] Step 3:

[0135] The server converts the received image data into text data using optical character recognition (OCR) technology.

[0136] Step 4:

[0137] The server applies an automatic scoring algorithm based on the text data.

[0138] Step 5:

[0139] The server stores the results of the scoring in a database.

[0140] Step 6:

[0141] The server transmits the automatic scoring results to the terminal.

[0142] Step 7:

[0143] The terminal displays the received grading results on the screen, and the user (teacher) checks them.

[0144] Example 1

[0145] 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."

[0146] In today's educational settings, a wide range of functions are required, such as the centralized management of student information, the digital provision of teaching materials, information sharing among teachers, and automatic grading of exams and assignments. In conventional systems, these functions are separate, which not only makes it time-consuming to consolidate and manage information, but also increases the workload of teachers. For this reason, a system that can integrate and manage these functions centrally is needed.

[0147] 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.

[0148] In this invention, the server includes an information management means for centrally managing student information and making it accessible to teachers, a learning means for providing digital learning materials so that students can study online, a document management means for allowing teachers to share learning materials and lesson plans, a grading means for automatically grading test questions and assignments, a grade management means for viewing and updating student grade information, an attendance management means for managing and analyzing student attendance information, a learning material uploading means for teachers to upload learning materials so that students can study online, an assignment submission means for students to submit assignments online, a document editing means for teachers to edit and save shared documents, and an exam answer uploading means for uploading and analyzing exam answers. This reduces the workload of teachers and improves the learning environment for students.

[0149] "Student information" refers to information related to individuals, such as the name, student ID number, grades, attendance information, and history of students belonging to a school.

[0150] "Information management" is a means of centrally managing student information and providing teachers with the ability to access, view, and edit it as needed.

[0151] "Learning medium" refers to the means by which learning materials are provided in digital format and students learn online.

[0152] "Document management" is a means by which teachers can share teaching materials and lesson plans, and edit and save them as needed.

[0153] A "grading tool" is a tool that automatically grades submitted test questions and assignments and manages the results.

[0154] A "grade management tool" is a means by which students' grade information can be viewed and updated, and is a system that allows teachers to quickly obtain the information they need.

[0155] The "attendance management means" is a means for managing and analyzing daily attendance information and understanding patterns of absence and lateness.

[0156] The "teaching material uploading means" is a means for uploading teaching materials created by teachers to a server so that students can download them and study.

[0157] "Assignment submission means" refers to the means by which students submit assignments online.

[0158] "Document editing means" refers to a means for teachers to edit and save shared documents.

[0159] The "test answer uploading means" is a means by which a teacher uploads test answers to a server, analyzes them, and grades them.

[0160] The present invention is a system that integrates the functions of unified management of student information, provision of digital teaching materials, management of shared documents, and electronic grading. A specific embodiment of this system will be described in detail below.

[0161] A centralized student information management system

[0162] The server centrally manages student information, including grades, attendance, and history, in a MySQL database. Teachers using terminals can access the server via a web browser to register, view, and update student information.

[0163] Specific examples

[0164] When a teacher enters the information of a new student into the terminal and presses the submit button, the server stores the information in a MySQL database. When a teacher enters a student ID number to view the grade information of a specific student, the server retrieves the information from the database and displays it on the teacher's terminal.

[0165] Online Learning Platform

[0166] The server provides teaching materials and assignments in digital format and allows users (teachers and students) to access them. Web applications built using web frameworks (e.g., Django or Rails) are used. Users using terminals can perform operations such as uploading and downloading teaching materials and submitting assignments.

[0167] Specific examples

[0168] When a teacher uploads new learning materials to the server, the materials are stored in a directory within the web application. Students can log in, download the materials, and proceed with their studies. Students who have completed their assignments can upload them from their devices and store them on the server.

[0169] Shared Document Management System

[0170] The server provides a document management system that allows teachers to share teaching materials and lesson plans. It connects with cloud services such as Google Docs and Microsoft Office 365 to manage access and editing of shared documents. Teachers using devices can access documents and edit and save them as needed.

[0171] Specific examples

[0172] When Teacher A uploads a lesson plan, other teachers can view and download it. For example, if you are using Google Docs, Teacher B can co-edit the document.

[0173] Electronic Scoring System

[0174] The server uses Python's OpenCV and Scikit-learn libraries to automatically grade exam questions and assignments. Teachers using terminals can upload scanned exam answers to the server and check the graded results online.

[0175] Specific examples

[0176] When a teacher scans and sends the test answers from their device to the server, the server analyzes the answers using OpenCV, automatically scores them using Scikit-learn, and returns the results to the teacher's device.

[0177] Prompt Sentence Examples

[0178] 1. "Please give an overview of your student information management system."

[0179] 2. "Please briefly explain the features of your online learning platform."

[0180] 3. "Please explain the technical details of the electronic marking system."

[0181] This reduces the workload of teachers and improves the learning environment for students. The system also provides users with intuitive operation through its interface, improving the quality of education.

[0182] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0183] A centralized student information management system

[0184] Processing Steps

[0185] Step 1: Register student information

[0186] Terminal: The teacher enters student information (name, student ID number, grades, etc.) into the input form and presses the send button.

[0187] Input: Student information (name, student ID number, grades)

[0188] Server: The server receives the input information and saves it in the database. Specifically, it executes an INSERT query on the MySQL database and stores the information in storage.

[0189] Output: Save complete response

[0190] Specific operation: A teacher enters new student information into the student registration form on the terminal, which is then sent to the server. The server saves the information in the database and returns a "Saving completed" message to the teacher's terminal.

[0191] Step 2: View Student Information

[0192] Terminal: The teacher enters the student's student ID number into the search form and presses the search button.

[0193] Input: Student ID number

[0194] Server: The server uses a SELECT query to retrieve the student's information from the database based on the received student ID number.

[0195] Output: Student information

[0196] Specific operation: When a teacher enters a student ID number and presses the search button, the server retrieves the relevant student's information from the database and displays it on the teacher's terminal.

[0197] Online Learning Platform

[0198] Processing Steps

[0199] Step 1: Upload your materials

[0200] Terminal: The teacher selects the teaching material file and presses the upload button.

[0201] Input: Teaching material file

[0202] Server: The server receives the uploaded file and saves it in the specified directory of the web application.

[0203] Output: Upload complete response

[0204] Specific operation: The teacher selects a teaching material file and uploads it to the server. The server saves the file in a specific directory and returns an "upload complete" message to the teacher.

[0205] Step 2: Download the materials

[0206] Device: Students log in to the web application and select the materials they want to download from the list of materials.

[0207] Input: Download request (teaching material ID)

[0208] Server: The server acquires the selected teaching material file and sends it to the student's terminal.

[0209] Output: Teaching material file

[0210] Specific operation: When a student selects a teaching material and presses the download button, the server sends the teaching material file to the student's device and the download begins.

[0211] Shared Document Management System

[0212] Processing Steps

[0213] Step 1: Share the document

[0214] Terminal: The teacher selects the shared document and uploads it to the specified folder.

[0215] Input: Shared Documents

[0216] Server: The server receives the uploaded shared documents and stores them in a specified directory.

[0217] Output: Sharing complete response

[0218] Specific operation: When a teacher selects a shared document and presses the upload button, the server saves the document in the specified directory and returns a message saying "Sharing completed."

[0219] Step 2: Edit the document

[0220] Device: The teacher accesses the shared document and makes any necessary edits.

[0221] Input:Edit

[0222] Server: The server receives the edits and updates the document, optionally providing version control.

[0223] Output: Update complete response

[0224] Specific behavior: When a teacher accesses a shared document, makes edits, and saves the content, the server updates the document and returns a message that the update is complete.

[0225] Electronic Scoring System

[0226] Processing Steps

[0227] Step 1: Upload your exam answers

[0228] Terminal: The teacher selects the scanned test answer sheet and presses the upload button.

[0229] Input: Scanned image of the test answer sheet

[0230] Server: The server receives the uploaded scanned images and stores them in a specified directory.

[0231] Output: Upload complete response

[0232] Specific operation: The teacher scans the exam answers and uploads the image to the server. The server saves the image and returns a message saying "upload completed."

[0233] Step 2: Automated scoring

[0234] Server: The server analyzes the test answer images using the OpenCV library and automatically scores the answers using Scikit-learn.

[0235] Input: Scanned image of the test answer sheet

[0236] Output:Scoring results

[0237] What it does: The server analyzes the scanned image, automatically scores it using a machine learning model, and stores the results in a database.

[0238] Step 3: Check your results

[0239] Terminal: The teacher accesses the server to check the grading results.

[0240] Input: Grading result inquiry request

[0241] Server: The server retrieves the grading results from the database and sends them to the teacher's terminal.

[0242] Output:Scoring results

[0243] Specific operation: The teacher checks the grading results on their device, and the information is retrieved from the server and displayed on the teacher's device.

[0244] Through these steps, the system enables management of student information, support for online learning, information sharing among teachers, and efficient grading.

[0245] (Application example 1)

[0246] 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."

[0247] In conventional educational systems, functions such as managing student information, providing teaching materials, sharing lesson plans, and grading assignments are distributed, making it difficult to operate them centrally. As a result, teachers' work becomes complicated and they are unable to provide effective educational support. In addition, there are limited ways for students to instantly check their learning progress and grades, hindering learning efficiency. Furthermore, the inconvenient management of annotations and notes on digital teaching materials makes it difficult to deepen learning content.

[0248] 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.

[0249] In this invention, the server includes a school information management means for centrally managing student information and making it accessible to teachers, an online learning means for providing digital teaching materials so that students can study online, a shared document management means for allowing teachers to share teaching materials and lesson plans, an electronic grading means for automatically grading test questions and assignments, a mobile access means for checking students' learning progress and grades from their smartphones, a digital annotation means for adding annotations to digital teaching materials and viewing them, and an electronic notification means for automatically grading submitted assignments and notifying the results. This makes it possible to improve the efficiency of teachers' work and students' learning.

[0250] "School information management means" refers to a means for centrally managing information such as student grades, attendance, and history, and making it accessible to teachers.

[0251] "Online learning means" means means by which educational materials are provided in digital format and students can learn online.

[0252] "Shared document management means" refers to a means by which teachers can share and manage teaching materials and lesson plans.

[0253] "Electronic marking means" means a means for automatically marking test questions or assignments and providing the results.

[0254] "Mobile access means" refers to a means that allows students to check their learning progress and grades from their smartphones.

[0255] "Digital annotation means" refers to a means for annotating and viewing digital teaching materials.

[0256] "Electronic notification means" refers to a means for automatically grading assignment submissions and notifying the results.

[0257] This invention is a system that includes a unified management of student information, a means for students to study online, a means for teachers to share teaching materials and lesson plans, a means for automatically grading test questions and assignments, a means for checking learning progress and grades from a smartphone, a means for annotating and viewing digital teaching materials, and a means for automatically grading submitted assignments and notifying the results. Specific methods for realizing this system are described below.

[0258] Hardware and Software Configuration

[0259] This system is mainly composed of three main elements: a server, a terminal, and a user.

[0260] server

[0261] The server has a central database for unifying student information and stores various information (grades, attendance, history, etc.). The server runs a software framework (e.g., Flask) for managing the provision of digital learning materials, automatic grading of assignments, and notification of grades. SQLite is used as the database.

[0262] Centralized management of student information: Provides API endpoints to make student information more accessible to teachers and handles data requests and responses.

[0263] Providing digital learning materials: Stores learning materials uploaded by teachers and makes them available for students to download.

[0264] Shared Document Management: Manage, store, and provide shared access to documents shared among faculty members.

[0265] Electronic grading: Automatically grade exam questions and assignments and store the results.

[0266] Terminal

[0267] The device (smartphone or PC) provides an interface for users to access the server, and students download digital learning materials, annotate them, and submit assignments from the device.

[0268] Mobile access: Provide students with an interface to check their progress and grades using their smartphones.

[0269] Digital annotation: A function that allows you to add notes and annotations to digital teaching materials.

[0270] Electronic notifications: Has the function of notifying assignment grading results in real time.

[0271] Specific examples

[0272] Here are some specific scenarios where this system can be used:

[0273] 1. Student grade management: When a teacher sends a request to view a student's grades from their device to the server, the server retrieves the student's grades from the database and returns them to the teacher's device. The teacher can then check the grades on their smartphone.

[0274] 2. Online lessons: Teachers upload digital learning materials to a server, and students download them from their smartphones. Students annotate the downloaded materials and progress with their learning.

[0275] 3. Electronic grading: When teachers send exam answer sheets from their devices to the server, the server automatically grades them using the electronic grading system and stores the results in a database. Students are notified of the grade results via their smartphones.

[0276] Prompt Sentence Examples

[0277] The questions are automatically scored by inputting the following prompts into the generative AI model:

[0278] Teacher-created math assignment answers:

[0279] Q1: B

[0280] Q2: B

[0281] Q3: A

[0282] Please rate this.

[0283] In this way, a system is provided that can improve the efficiency of teachers' work and students' learning.

[0284] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0285] Step 1:

[0286] Requester: User (teacher)

[0287] Processing content: The teacher sends a request to the server from the terminal to view the student's grades.

[0288] Input: Student ID entered on the teacher's device.

[0289] Data processing: Generate an HTTP request including the student ID.

[0290] Output: A request containing the student ID is sent to the server.

[0291] Specific operations: The teacher enters the ID of the student whose grades they want to check into their smartphone or computer and presses the "Check Grades" button.

[0292] Step 2:

[0293] Requested by: Server

[0294] Processing content: The server retrieves the student's grades from the database.

[0295] Input: A request containing a student ID.

[0296] Data processing: Generate a database query to obtain the student's academic performance information.

[0297] Output: Academic information for the student.

[0298] Specific operation: The server issues a query to the database using the received student ID and extracts the student's grade information.

[0299] Step 3:

[0300] Requested by: Server

[0301] Processing content: The server returns the grade information it has acquired to the teacher's terminal.

[0302] Input: Academic information for the student in question.

[0303] Data processing: Generate an HTTP response containing performance information.

[0304] Output: A response containing grade information is sent to the teacher's terminal.

[0305] Specific operation: The server sends the grade information obtained from the database to the teacher's terminal as an HTTP response.

[0306] Step 4:

[0307] Requester: User (teacher)

[0308] Processing details: Teachers check students' grade information on their smartphones or computers.

[0309] Input: Achievement information received from the server.

[0310] Data processing: Convert received grade information into a display format.

[0311] Output: Student grades are displayed on the screen.

[0312] Specific actions: The teacher checks the grade information displayed on the device and takes the necessary action.

[0313] Step 5:

[0314] Requester: User (student)

[0315] What happens: Students log in to an online learning platform from their home devices and download the learning materials provided by their teachers.

[0316] Input: Login information, request for materials.

[0317] Data processing: Authenticating login information and processing requests for learning materials.

[0318] Output: Teaching material data.

[0319] Specific operation: Students log in to their devices, search for the teaching materials uploaded by the teacher, and press the download button.

[0320] Step 6:

[0321] Requested by: Server

[0322] Processing content: The server provides teaching material data in response to student requests.

[0323] Input: Student materials request.

[0324] Data processing: Search for teaching material data and include it in the HTTP response.

[0325] Output: A response containing the teaching material data is sent to the student's device.

[0326] Specific operation: The server retrieves digital learning materials from the database and provides them to students in a downloadable format.

[0327] Step 7:

[0328] Requested by: Server

[0329] Processing content: The server inputs the submitted assignment into a generative AI model and performs automatic grading.

[0330] Input: Submitted assignment response data.

[0331] Data processing: The answer data is fed into the generative AI model to obtain the scoring results.

[0332] Output: Scoring results.

[0333] Specific operation: The server inputs the assignments submitted by the students into the generative AI model and generates the grading results.

[0334] Step 8:

[0335] Requested by: Server

[0336] Processing details: The server saves the grading results in a database and notifies the teacher's terminal.

[0337] Input:Scoring results.

[0338] Data processing: The grading results are stored in a database and notifications are sent to teachers.

[0339] Output: Saved grading results, notifications.

[0340] Specific operation: The server saves the generated grading results in a database and sends a notification to the teacher's terminal saying "The grading results have been updated."

[0341] Step 9:

[0342] Requester: User (teacher)

[0343] Processing details: Teachers check the grading results on their smartphones or computers.

[0344] Input: Notification from the server.

[0345] Data processing: Retrieve the scoring results from the database and convert them into a display format.

[0346] Output: The results are displayed on the screen.

[0347] Specific operation: The teacher clicks on the notification on the device and checks the grading results.

[0348] In this way, the present invention provides a system that can manage student information, provide digital teaching materials, automatically grade assignments, manage grades, and check progress on a smartphone in an integrated manner.

[0349] 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.

[0350] This invention relates to a system that combines the centralized management of student information, provision of digital teaching materials, shared document management, and electronic grading functions with an emotion engine that recognizes user emotions. This system is composed of three main elements: a server, a terminal, and a user. The emotion engine recognizes user emotions and reflects them in the system, with the aim of further improving the quality of education. We will now explain in detail how each element works together and how the invention is specifically implemented.

[0351] A centralized student information management system

[0352] server

[0353] The server centrally manages student grades, attendance information, and records, making them accessible to teachers. This allows teachers to quickly obtain the information they need. Furthermore, the emotion engine stores students' emotional information on the server, enabling comprehensive information management.

[0354] For example, if a teacher wants to check the grades and recent emotional state of a specific student, a request is sent from the device. The server retrieves the student's grades and emotional state from the database and returns them to the teacher's device.

[0355] Online Learning Platform

[0356] server

[0357] The server provides digital learning materials and assignments for users (teachers and students) to access. Teachers upload learning materials, and students can view and study them online. The emotion engine recognizes students' emotional state in real time during online learning, improving the effectiveness of their learning.

[0358] For example, when a teacher uploads a new assignment, the server stores the data and students download it to study. The emotion engine monitors students' emotions as they work on the assignment and provides feedback according to their learning progress.

[0359] Terminal

[0360] The terminal provides an interface for users to access the server and upload or download learning materials. It also has an emotion engine that recognizes users' emotions in real time.

[0361] Example: When a student logs into an online learning platform from their home device and downloads materials provided by their teacher to study, the emotion engine recognizes the student's emotional state and displays advice to optimize learning efficiency.

[0362] Shared Document Management System

[0363] server

[0364] The server provides a system that allows teachers to share teaching materials and lesson plans, and stores and updates the shared documents. The emotion engine strengthens the collaborative system among teachers by monitoring the viewing status of the shared documents and the emotional state of the viewers.

[0365] Example: Teacher A uploads a lesson plan he created to the server, and when Teacher B views the document, the emotion engine recognizes Teacher B's reaction and provides feedback.

[0366] Electronic Scoring System

[0367] server

[0368] The server automatically grades submitted exam questions and assignments and stores the results in a database. In addition, an emotion engine monitors the student's emotional state when answering questions and takes this into account as a factor that may affect the grade.

[0369] Example: When a teacher uploads exam answers scanned on a device, the server processes the answers in an electronic scoring system, and the emotion engine analyzes the student's emotional state and notifies the teacher of the results.

[0370] Terminal

[0371] The device provides an interface for teachers to upload exam and assignment answers and view the automated marking results. It also has an emotion engine that monitors the teacher's reactions and emotional state.

[0372] Example: When a teacher uses a device at home to scan an answer sheet, send it to a server, and receive the results of automatic grading, the emotion engine recognizes the teacher's emotional state and makes suggestions to reduce stress.

[0373] Example

[0374] Example 1: Student performance management and emotion monitoring

[0375] 1. Send a request to view student grades from the teacher's device.

[0376] 2. The server retrieves the student's grades and emotional state from the database.

[0377] 3. The server sends the grade information and emotional state to the teacher's terminal, and the teacher checks the information.

[0378] Example 2: Online classes and emotional feedback

[0379] 1. The teacher uploads the teaching materials from the device to the server.

[0380] 2. The server stores the learning materials and makes them accessible to students.

[0381] 3. Students download the learning materials to their devices and proceed with their studies.

[0382] 4. The emotion engine monitors students' emotional state in real time while they are learning and provides appropriate feedback.

[0383] Example 3: Electronic scoring and sentiment analysis

[0384] 1. The teacher sends the exam answer sheet from the terminal to the server.

[0385] 2. The server uses an electronic scoring system to automatically score the tests.

[0386] 3. The emotion engine analyzes the student's emotional state when answering and reflects this in the scoring results.

[0387] 4. The server sends the scoring results and emotion analysis results to the teacher's terminal, where the teacher can check them.

[0388] The system of the present invention significantly reduces the workload of teachers and enables them to effectively utilize their expertise. The introduction of an emotion engine provides feedback based on the user's emotional state, further improving the quality and efficiency of education.

[0389] The processing flow will be explained below.

[0390] A centralized student information management system

[0391] Process flow: Viewing student grades and emotional information

[0392] Step 1:

[0393] A user (teacher) sends a request from a terminal to view the grades and emotional information of a specific student.

[0394] Step 2:

[0395] The terminal forwards the request to the server.

[0396] Step 3:

[0397] A server accesses a database containing student performance and emotional information.

[0398] Step 4:

[0399] The server retrieves the student's grade information and emotion information from the database.

[0400] Step 5:

[0401] The server transmits the acquired performance information and emotion information to the terminal.

[0402] Step 6:

[0403] The terminal displays the received information on the screen, and the user (teacher) checks it.

[0404] Online Learning Platform

[0405] Process flow: Uploading teaching materials and monitoring emotions

[0406] Step 1:

[0407] The user (teacher) selects the teaching material file and sends an upload request from the terminal.

[0408] Step 2:

[0409] The terminal uploads the selected educational material file to the server.

[0410] Step 3:

[0411] The server stores the received teaching material file in a data storage.

[0412] Step 4:

[0413] The server sends a notification to the device that the upload is complete.

[0414] Step 5:

[0415] A user (student) sends a request to access the online learning platform from a terminal.

[0416] Step 6:

[0417] The terminal accesses the server and sends a request to acquire a list of available learning materials.

[0418] Step 7:

[0419] The server retrieves a list of available learning materials from the database and sends it to the terminal.

[0420] Step 8:

[0421] The terminal displays a list of teaching materials on the screen, which the user (student) can view.

[0422] Step 9:

[0423] The emotion engine analyzes the user's (student's) facial expressions and voice in real time to recognize their emotional state.

[0424] Step 10:

[0425] The emotion engine sends feedback to the device based on the recognized emotional state to improve learning efficiency.

[0426] Shared Document Management System

[0427] Process flow: Sharing lesson plans and emotional feedback

[0428] Step 1:

[0429] The user (teacher) selects a lesson plan document and sends a sharing request from their device.

[0430] Step 2:

[0431] The device uploads the document to the server.

[0432] Step 3:

[0433] The server saves the document in a shared folder and updates the sharing settings.

[0434] Step 4:

[0435] The server sends a notification of completion of sharing to the terminal.

[0436] Step 5:

[0437] Another user (teacher) sends a request from their device to find a shared lesson plan document.

[0438] Step 6:

[0439] The terminal accesses the shared folder and sends a request to the server to search for the document.

[0440] Step 7:

[0441] The server retrieves the document from the shared folder and sends it to the terminal.

[0442] Step 8:

[0443] The terminal displays the received document on the screen, and the user (teacher) views it.

[0444] Step 9:

[0445] The emotion engine analyzes the user's (teacher's) facial expressions and voice in real time and recognizes their reactions to shared documents.

[0446] Step 10:

[0447] The emotion engine sends feedback and improvement suggestions to the device based on the recognized emotional state.

[0448] Electronic Scoring System

[0449] Process flow: Automatic marking of assignments and sentiment analysis

[0450] Step 1:

[0451] The user (teacher) scans the students' answer sheets and sends a request from the terminal to upload them to the electronic marking system.

[0452] Step 2:

[0453] The device uploads the scanned image of the answer sheet to the server.

[0454] Step 3:

[0455] The server converts the received image data into text data using optical character recognition (OCR) technology.

[0456] Step 4:

[0457] The server applies an automatic scoring algorithm based on the text data.

[0458] Step 5:

[0459] The emotion engine analyzes the facial expressions and voice of students during their responses and generates emotional information.

[0460] Step 6:

[0461] The server stores the scoring results and emotion information in a database.

[0462] Step 7:

[0463] The server sends a notification including the grading results and emotion information to the teacher's terminal.

[0464] Step 8:

[0465] The terminal displays the received scoring results and emotion information on the screen, and the user (teacher) checks them.

[0466] Step 9:

[0467] The emotion engine analyzes teachers' reactions in real time and provides feedback and stress-reducing suggestions as appropriate.

[0468] Example 2

[0469] 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."

[0470] While traditional education systems require centralized management of student information and efficient online learning, they lack functionality such as emotion recognition and real-time feedback, making it difficult to maximize student learning outcomes. Furthermore, there are limited means to streamline teacher work, and strengthening cooperation among teachers and improving the accuracy of automated grading of exams and assignments are also issues.

[0471] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0472] In this invention, the server includes an information management means, an online learning means, a sharing management means, a scoring means, and an emotion recognition means. This makes it possible to:

[0473] 1. Students' grades, attendance, history and emotional information can be managed in an integrated manner.

[0474] 2. Efficient online learning can be achieved through the uploading, viewing, and editing of teaching materials, as well as real-time monitoring of students' emotional states.

[0475] 3. Teachers can strengthen collaboration and share teaching materials and lesson plans more efficiently.

[0476] 4. Exams and assignments can be graded automatically, and emotion recognition can be used to reflect emotional information in the grading results.

[0477] The "information management means" is a system including a database that comprehensively manages student grades, attendance information, history, and emotional information.

[0478] "Online learning means" means a system that includes functions for providing educational materials digitally and enabling students to learn online, and allows for the uploading, viewing, and modification of educational materials, as well as real-time monitoring of students' emotional state.

[0479] A "shared management tool" is a system that allows teachers to share teaching materials and lesson plans with each other.

[0480] A "grading tool" is a system that automatically grades exams and assignments.

[0481] The "emotion recognition means" is a system that recognizes the user's emotions in real time and reflects them in education.

[0482] This invention relates to a system that combines the functions of unified student information management, digital teaching materials provision, shared document management, and electronic grading with an emotion recognition engine that recognizes user emotions in real time. This system includes three main elements: a server, a terminal, and a user, and these elements work in conjunction with each other.

[0483] Hardware and software used

[0484] The system mainly uses the following hardware and software:

[0485] Server: Database and emotion recognition engine (e.g., SQL database, emotion recognition algorithm implemented in Python)

[0486] Device: The interface through which the user accesses the device (e.g., PC, tablet, dedicated application)

[0487] Users: Teachers and students

[0488] A centralized student information management system

[0489] server

[0490] The server maintains a database that comprehensively manages student grades, attendance, history, and emotional information. Upon request from a teacher, it retrieves the relevant student data and returns it to the teacher's device.

[0491] Example: When a teacher wants to check the grade information and emotional state of a particular student from his / her terminal, the server retrieves the information from the database and sends it to the teacher's terminal.

[0492] Online Learning Platform

[0493] server

[0494] The server digitally stores teaching materials uploaded by teachers and makes them available for students to access online. An emotion recognition engine also recognizes students' emotional state while they are studying and provides appropriate feedback.

[0495] Example: When a teacher uploads new learning materials, the server stores them and makes them available for students to view. An emotion recognition engine monitors students' emotional state while they are learning and generates feedback according to their learning progress.

[0496] Terminal

[0497] The device provides an interface for students to access online learning platforms, download learning materials, and study. It also includes an emotion recognition engine that can recognize users' emotions in real time.

[0498] Example: When a student is downloading learning materials from their home device and studying, an emotion recognition engine analyzes the student's emotional state and displays advice on how to relax if stress levels are rising.

[0499] Shared Document Management System

[0500] server

[0501] The server allows teachers to upload, save, and update shared documents. The emotion recognition engine monitors the viewing status of shared documents and the emotional state of the viewer, and provides feedback.

[0502] Example: When Teacher A uploads a shared document to the server and Teacher B views it, an emotion recognition engine analyzes Teacher B's reaction and provides Teacher A with feedback based on the reaction.

[0503] Electronic Scoring System

[0504] server

[0505] The server automatically grades test answers and assignments, storing the results in a database. An emotion recognition engine also analyzes the emotional state of students when they answer questions and reflects this in the grades.

[0506] Example: When a teacher scans an answer sheet and sends it to a server, the electronic scoring system automatically scores it and sends the results and sentiment analysis results to the teacher's device.

[0507] Terminal

[0508] The device provides an interface for teachers to upload exam and assignment answers and receive automated grading results. It also includes an emotion recognition engine that monitors teachers' reactions and emotional state.

[0509] Example: When a teacher scans an answer sheet using a device at home and sends it to a server, and receives the grading results and emotion analysis results, the emotion recognition engine monitors the teacher's stress level and suggests relaxation methods if necessary.

[0510] Example

[0511] Prompt Sentence Examples

[0512] "Please detail the procedures for faculty to monitor students' academic performance and emotional state."

[0513] "Please explain specific ways in which you can monitor students' emotional states in online learning platforms."

[0514] "Please show us specifically how you will perform sentiment analysis in your electronic scoring system and reflect it in the results."

[0515] This system will reduce the workload of teachers and maximize the learning effect of students. The introduction of an emotion recognition engine will enable real-time feedback, which is expected to further improve the quality of education.

[0516] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0517] A centralized student information management system

[0518] Step 1:

[0519] A teacher sends a request to view a student's grades on a terminal. The input is the teacher's identification information for the student (student ID, name, etc.). The terminal generates this request and sends it to the server. The output is the request data sent to the server.

[0520] Step 2:

[0521] The server receives the request and retrieves the student's grades and emotional state from the database. The input is the request data from the teacher. The server executes the database query to retrieve the grade information and emotional state information. The output is the retrieved data of the student's grades and emotional state.

[0522] Step 3:

[0523] The server returns the acquired information to the teacher's terminal. The input is the student's grades and emotional state data acquired by the server. The server structures this data and sends it to the teacher's terminal. The output is the grade information and emotional information acquired by the teacher.

[0524] Step 4:

[0525] The teacher checks the information on the terminal. The input is the grade information and emotional state data sent from the server. The teacher displays and checks the received information through the terminal interface. The output is information that the teacher uses to make decisions.

[0526] Online Learning Platform

[0527] Step 1:

[0528] The teacher uploads the teaching material from the terminal. The input is the digital teaching material file and related metadata (title, description, etc.). The terminal collects this data and sends it to the server. The output is the uploaded data to the server.

[0529] Step 2:

[0530] The server stores the teaching materials and sets them up so that students can access them. The input is the teaching material data and metadata sent by the teacher. The server stores this in a database and sets permissions so that students can access it. The output is the teaching materials stored and accessible.

[0531] Step 3:

[0532] Students download learning materials to their devices and progress with their studies. The input is the student sending a download request and the learning material data stored on the server. The device generates a request and retrieves the learning material from the server. The output is the learning material data downloaded to the student's device.

[0533] Step 4:

[0534] The emotion engine monitors students' emotional states in real time and provides feedback. The input is data such as the student's facial expressions, voice volume, and tone of voice obtained from the device's camera and microphone. The emotion engine analyzes this data and estimates the student's emotional state. The output is advice and recommendations presented to the student as real-time feedback.

[0535] Shared Document Management System

[0536] Step 1:

[0537] The teacher uploads a shared document from a terminal. The input is the shared document file and related metadata. The terminal sends these to the server. The output is the uploaded data to the server.

[0538] Step 2:

[0539] The server saves the document and sets it up so that other teachers can access it. The input is the shared document data sent by the teacher. The server saves it in a database and sets permissions so that other teachers can access it. The output is the saved document and access right setting data.

[0540] Step 3:

[0541] Another teacher views the document on their device. The input is a view request and the document data stored on the server. The device generates a request and retrieves the document from the server. The output is the document data displayed on the teacher's device.

[0542] Step 4:

[0543] The emotion engine monitors the viewer's emotional state and provides feedback. The input is data such as the teacher's facial expression, voice volume, and tone obtained from the device's camera and microphone. The emotion engine analyzes this data and estimates the teacher's emotional state. The output is advice and recommendations that are presented to the teacher as feedback during viewing.

[0544] Electronic Scoring System

[0545] Step 1:

[0546] The teacher sends the exam answer sheet from the terminal. The input is a digital file of the scanned exam answer sheet. The terminal sends this to the server. The output is the exam answer data sent to the server.

[0547] Step 2:

[0548] The server uses an electronic marking system to perform marking. The input is test answer data. The server calls the electronic marking system and automatically performs marking. The output is marking result data.

[0549] Step 3:

[0550] The emotion engine analyzes the emotional state of the student when answering. The input is facial expression and voice data recorded when answering. The emotion engine analyzes this and estimates the emotional state. The output is emotion analysis result data.

[0551] Step 4:

[0552] The server sends the scoring results and sentiment analysis results to the teacher's terminal. The input is the scoring result data and sentiment analysis result data. The server structures these and sends them to the teacher's terminal. The output is the scoring results and sentiment analysis results received by the teacher.

[0553] Step 5:

[0554] The teacher checks the grading results and sentiment analysis results on the terminal. The input is the grading results and sentiment analysis results received from the server. The teacher displays and checks this information on the terminal. The output is information that the teacher can use to make decisions.

[0555] (Application example 2)

[0556] 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."

[0557] Existing educational systems manage students' grades and learning progress without considering their emotional state, making it difficult to provide optimal instruction and feedback to individual students. Furthermore, general online shopping sites lack a means to provide a personalized shopping experience that reflects users' emotional state. There is a need to address these issues, improve the quality and efficiency of education, and enhance the user experience of online shopping.

[0558] 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.

[0559] In this invention, the server includes an information management means, a learning means, a shared document management means, a scoring means, and an emotion-aware shopping assistant means, thereby enabling a comprehensive education and shopping experience that takes into account the user's emotions.

[0560] "Information management means" refers to the part of the system that centrally manages students' grades, attendance information, and records, and allows teachers to access this information.

[0561] "Learning tools" are the system's capabilities to provide learning materials digitally and enable students to learn online.

[0562] The "shared document management tool" is part of a system that provides the ability for teachers to share teaching materials and lesson plans and edit them collaboratively.

[0563] A "grading tool" is a system that has the function of automatically grading test questions and assignments and providing the results to teachers.

[0564] The "emotion recognition shopping assistant means" is a system function that analyzes the user's facial expressions and voice to recognize their emotions, and then makes product recommendations and promotions based on this.

[0565] The system for implementing this invention mainly comprises a server, a terminal, and a user. Each of these components will be described in detail below.

[0566] Information management means

[0567] The information management system is provided by a server and is a system that centrally manages student grades, attendance information, and records. Teachers can access this information using their terminals and quickly obtain the data they need. The data is stored and managed in a database on the server.

[0568] Learning tools

[0569] Learning tools are provided by a server. The server provides learning materials and assignments in digital format, and students can study online using their devices. Teachers upload learning materials to the server, and students download them to study. The system is also equipped with an emotion engine that provides feedback based on students' emotional state.

[0570] Shared document management tools

[0571] The shared document management system is provided by a server and allows teachers to share teaching materials and lesson plans. Teachers can upload documents from their devices, and other teachers can view and edit them collaboratively. The emotion engine also monitors the emotional state of viewers and provides effective feedback.

[0572] Scoring method

[0573] The grading method is a function in which the server automatically grades submitted exam questions and assignments. When teachers scan and upload answer sheets from their devices, the server processes them with an electronic grading system. In addition, an emotion engine monitors the students' emotional state when answering, and this is also reflected in the grading results.

[0574] Emotion-aware shopping assistant

[0575] The emotion-aware shopping assistant uses the user's terminal or smart device (e.g., smartphone or tablet) to analyze the user's facial expressions and voice to recognize emotions. Based on the recognized emotions, the server provides appropriate product recommendations and promotions. This allows the user to have an individualized shopping experience.

[0576] Hardware and software used

[0577] Hardware used: smartphone, tablet, PC, camera

[0578] Software used: Python, Flask, OpenCV, TextBlob

[0579] Processing flow

[0580] The specific process flow is implemented based on the following steps:

[0581] 1. Obtain the user's camera video and audio input.

[0582] 2. The captured video is analyzed using OpenCV and the face_recognition library to analyze the user's facial expressions and recognize their emotional state.

[0583] 3. The voice input (or text) is analyzed with the TextBlob library to determine the user's sentiment as text.

[0584] 4. Based on the results of sentiment and text analysis, the server recommends appropriate products and promotions to the user.

[0585] Specific examples

[0586] 1. When a user opens an online shopping app on their smartphone, if the camera recognizes the user's face and determines that they are "Happy," the app will recommend "new fashion items that perfectly match their current mood."

[0587] 2. When a user asks "What are your recent recommendations?" using voice input, TextBlob analyzes the voice text, and if it is determined to be "positive," it suggests products with many positive reviews.

[0588] Prompt Sentence Examples

[0589] 1. "Analyze this user's facial expressions and voice to determine their emotional state."

[0590] 2. "What promotion should I offer if the user has a smiling face?"

[0591] This provides a holistic education and purchasing experience that takes into account the user's emotions.

[0592] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0593] Step 1:

[0594] The user launches the application on their device (smartphone or tablet).

[0595] Input: Launching an app on a smartphone or tablet.

[0596] Output: The app starts and goes to the initial screen.

[0597] Step 2:

[0598] The device's camera captures the user's face and obtains video data in real time.

[0599] Input: Camera image (user's face).

[0600] Output: Captured video frames.

[0601] Step 3:

[0602] The video data acquired by the device is analyzed using OpenCV and the face_recognition library to recognize the user's facial expressions.

[0603] Input: Captured video frames.

[0604] Output: Recognized facial expression data (e.g. smile, sadness).

[0605] Step 4:

[0606] The user speaks and the device captures the speech and converts it into text.

[0607] Input: Audio data.

[0608] Output: Audio converted to text data.

[0609] Step 5:

[0610] The device uses the TextBlob library to analyze the sentiment of the text converted from the audio data.

[0611] Input: Text data.

[0612] Output: Sentiment analysis result (e.g. positive, negative).

[0613] Step 6:

[0614] The device sends facial expression data and text analysis results to the server.

[0615] Input: facial expression data, emotion analysis results.

[0616] Output: Sending data to the server.

[0617] Step 7:

[0618] The server determines product recommendations and promotions based on the received data according to the user's emotional state.

[0619] Input: facial expression data, emotion analysis results.

[0620] Output: Recommendation data, promotion data.

[0621] Step 8:

[0622] The server transmits recommendation data and promotion data to the terminal.

[0623] Input: Recommendation data, Promotion data.

[0624] Output: Sending data to a terminal.

[0625] Step 9:

[0626] The device displays the received recommendations and promotions to the user.

[0627] Input: Recommendation data, Promotion data.

[0628] Output: Recommendations and promotion information displayed in a user interface.

[0629] 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.

[0630] 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.

[0631] 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.

[0632] [Second embodiment]

[0633] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0634] 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.

[0635] 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).

[0636] 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.

[0637] 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.

[0638] 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).

[0639] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0640] 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.

[0641] 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.

[0642] 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.

[0643] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0644] 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."

[0645] This invention relates to a system that includes the centralized management of student information, provision of digital teaching materials, shared document management, and electronic grading functions. This system consists of three main elements: a server, a terminal, and a user. We will explain in detail how each element works together and how the invention is specifically implemented.

[0646] A centralized student information management system

[0647] server

[0648] The server centrally manages student grades, attendance information, and records, making them accessible to teachers, allowing them to quickly obtain the information they need.

[0649] For example, if a teacher wants to check the grades of a specific student, a request is sent from the terminal. The server retrieves the grades of the student from the database and returns them to the teacher's terminal.

[0650] Online Learning Platform

[0651] server

[0652] The server provides digital learning materials and assignments, making them accessible to users (teachers and students). Teachers upload learning materials, and students can view and study them online.

[0653] Example: When a teacher uploads a new assignment, the server stores the data and students download it to study.

[0654] Terminal

[0655] The terminal provides an interface for the user to access the server and upload or download educational materials.

[0656] Example: A student logs into an online learning platform from their home device, downloads materials provided by their teacher, and studies.

[0657] Shared Document Management System

[0658] server

[0659] The server provides a system that allows teachers to share teaching materials and lesson plans with each other, and stores and updates shared documents, making it easier for teachers to share teaching materials with each other.

[0660] Example: Teacher A uploads a lesson plan he created to the server, and Teacher B can also view and download the plan.

[0661] Electronic Scoring System

[0662] server

[0663] The server automatically grades submitted exam questions and assignments and stores the results in a database, significantly reducing the grading workload for teachers.

[0664] Example: When a teacher uploads exam answers scanned on a device, the server processes the answers in an electronic scoring system and returns the scoring results to the teacher's device.

[0665] Terminal

[0666] The device provides an interface for teachers to upload exam and assignment answers and view the automatically graded results.

[0667] Example: A teacher uses a device at home to scan answer sheets, send them to a server, and receive the results of automatic grading.

[0668] Example

[0669] Example 1: Student Grade Management

[0670] 1. Send a request to view student grades from the teacher's device.

[0671] 2. The server retrieves the student's grades from the database.

[0672] 3. The server sends the grade information to the teacher's terminal, where the teacher can view the information.

[0673] Example 2: Online classes

[0674] 1. The teacher uploads the teaching materials from the device to the server.

[0675] 2. The server stores the learning materials and makes them accessible to students.

[0676] 3. Students download the learning materials to their devices and proceed with their studies.

[0677] Example 3: Electronic marking

[0678] 1. The teacher sends the exam answer sheet from the terminal to the server.

[0679] 2. The server uses an electronic scoring system to automatically score the tests.

[0680] 3. The server stores the grading results in a database and sends them to the teacher's device.

[0681] The system of the present invention significantly reduces the workload of teachers and enables them to effectively utilize the expertise of each teacher, thereby enabling them to provide higher quality education.

[0682] The processing flow will be explained below.

[0683] A centralized student information management system

[0684] Process flow: View student grades

[0685] Step 1:

[0686] A user (teacher) sends a request from a terminal to view the grades of a specific student.

[0687] Step 2:

[0688] The terminal forwards the request to the server.

[0689] Step 3:

[0690] The server accesses the database and obtains the grade information of the student.

[0691] Step 4:

[0692] The server transmits the acquired score information to the terminal.

[0693] Step 5:

[0694] The terminal displays the received grade information on the screen, and the user (teacher) checks it.

[0695] Online Learning Platform

[0696] Process flow: Uploading and viewing teaching materials

[0697] Step 1:

[0698] The user (teacher) selects the teaching material file and sends an upload request from the terminal.

[0699] Step 2:

[0700] The terminal uploads the selected educational material file to the server.

[0701] Step 3:

[0702] The server stores the received teaching material file in a data storage.

[0703] Step 4:

[0704] The server sends a notification to the device that the upload is complete.

[0705] Step 5:

[0706] A user (student) sends a request to access the online learning platform from a terminal.

[0707] Step 6:

[0708] The terminal accesses the server and sends a request to acquire a list of available learning materials.

[0709] Step 7:

[0710] The server retrieves a list of available learning materials from the database and sends it to the terminal.

[0711] Step 8:

[0712] The terminal displays a list of teaching materials on the screen, which the user (student) can view.

[0713] Shared Document Management System

[0714] Process flow: Sharing lesson plans

[0715] Step 1:

[0716] The user (teacher) selects a lesson plan document and sends a sharing request from their device.

[0717] Step 2:

[0718] The device uploads the document to the server.

[0719] Step 3:

[0720] The server saves the document in a shared folder and updates the sharing settings.

[0721] Step 4:

[0722] The server sends a notification of completion of sharing to the terminal.

[0723] Step 5:

[0724] Another user (teacher) sends a request from their device to find a shared lesson plan document.

[0725] Step 6:

[0726] The terminal accesses the shared folder and sends a request to the server to search for the document.

[0727] Step 7:

[0728] The server retrieves the document from the shared folder and sends it to the terminal.

[0729] Step 8:

[0730] The terminal displays the received document on the screen, and the user (teacher) views it.

[0731] Electronic Scoring System

[0732] Process flow: Automatic grading of assignments

[0733] Step 1:

[0734] The user (teacher) scans the students' answer sheets and sends a request from the terminal to upload them to the electronic marking system.

[0735] Step 2:

[0736] The device uploads the scanned image of the answer sheet to the server.

[0737] Step 3:

[0738] The server converts the received image data into text data using optical character recognition (OCR) technology.

[0739] Step 4:

[0740] The server applies an automatic scoring algorithm based on the text data.

[0741] Step 5:

[0742] The server stores the results of the scoring in a database.

[0743] Step 6:

[0744] The server transmits the automatic scoring results to the terminal.

[0745] Step 7:

[0746] The terminal displays the received grading results on the screen, and the user (teacher) checks them.

[0747] Example 1

[0748] 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."

[0749] In today's educational settings, a wide range of functions are required, such as the centralized management of student information, the digital provision of teaching materials, information sharing among teachers, and automatic grading of exams and assignments. In conventional systems, these functions are separate, which not only makes it time-consuming to consolidate and manage information, but also increases the workload of teachers. For this reason, a system that can integrate and manage these functions centrally is needed.

[0750] 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.

[0751] In this invention, the server includes an information management means for centrally managing student information and making it accessible to teachers, a learning means for providing digital learning materials so that students can study online, a document management means for allowing teachers to share learning materials and lesson plans, a grading means for automatically grading test questions and assignments, a grade management means for viewing and updating student grade information, an attendance management means for managing and analyzing student attendance information, a learning material uploading means for teachers to upload learning materials so that students can study online, an assignment submission means for students to submit assignments online, a document editing means for teachers to edit and save shared documents, and an exam answer uploading means for uploading and analyzing exam answers. This reduces the workload of teachers and improves the learning environment for students.

[0752] "Student information" refers to information related to individuals, such as the name, student ID number, grades, attendance information, and history of students belonging to a school.

[0753] "Information management" is a means of centrally managing student information and providing teachers with the ability to access, view, and edit it as needed.

[0754] "Learning medium" refers to the means by which learning materials are provided in digital format and students learn online.

[0755] "Document management" is a means by which teachers can share teaching materials and lesson plans, and edit and save them as needed.

[0756] A "grading tool" is a tool that automatically grades submitted test questions and assignments and manages the results.

[0757] A "grade management tool" is a means by which students' grade information can be viewed and updated, and is a system that allows teachers to quickly obtain the information they need.

[0758] The "attendance management means" is a means for managing and analyzing daily attendance information and understanding patterns of absence and lateness.

[0759] The "teaching material uploading means" is a means for uploading teaching materials created by teachers to a server so that students can download them and study.

[0760] "Assignment submission means" refers to the means by which students submit assignments online.

[0761] "Document editing means" refers to a means for teachers to edit and save shared documents.

[0762] The "test answer uploading means" is a means by which a teacher uploads test answers to a server, analyzes them, and grades them.

[0763] The present invention is a system that integrates the functions of unified management of student information, provision of digital teaching materials, management of shared documents, and electronic grading. A specific embodiment of this system will be described in detail below.

[0764] A centralized student information management system

[0765] The server centrally manages student information, including grades, attendance, and history, in a MySQL database. Teachers using terminals can access the server via a web browser to register, view, and update student information.

[0766] Specific examples

[0767] When a teacher enters the information of a new student into the terminal and presses the submit button, the server stores the information in a MySQL database. When a teacher enters a student ID number to view the grade information of a specific student, the server retrieves the information from the database and displays it on the teacher's terminal.

[0768] Online Learning Platform

[0769] The server provides teaching materials and assignments in digital format and allows users (teachers and students) to access them. Web applications built using web frameworks (e.g., Django or Rails) are used. Users using terminals can perform operations such as uploading and downloading teaching materials and submitting assignments.

[0770] Specific examples

[0771] When a teacher uploads new learning materials to the server, the materials are stored in a directory within the web application. Students can log in, download the materials, and proceed with their studies. Students who have completed their assignments can upload them from their devices and store them on the server.

[0772] Shared Document Management System

[0773] The server provides a document management system that allows teachers to share teaching materials and lesson plans. It connects with cloud services such as Google Docs and Microsoft Office 365 to manage access and editing of shared documents. Teachers using devices can access documents and edit and save them as needed.

[0774] Specific examples

[0775] When Teacher A uploads a lesson plan, other teachers can view and download it. For example, if you are using Google Docs, Teacher B can co-edit the document.

[0776] Electronic Scoring System

[0777] The server uses Python's OpenCV and Scikit-learn libraries to automatically grade exam questions and assignments. Teachers using terminals can upload scanned exam answers to the server and check the graded results online.

[0778] Specific examples

[0779] When a teacher scans and sends the test answers from their device to the server, the server analyzes the answers using OpenCV, automatically scores them using Scikit-learn, and returns the results to the teacher's device.

[0780] Prompt Sentence Examples

[0781] 1. "Please give an overview of your student information management system."

[0782] 2. "Please briefly explain the features of your online learning platform."

[0783] 3. "Please explain the technical details of the electronic marking system."

[0784] This reduces the workload of teachers and improves the learning environment for students. The system also provides users with intuitive operation through its interface, improving the quality of education.

[0785] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0786] A centralized student information management system

[0787] Processing Steps

[0788] Step 1: Register student information

[0789] Terminal: The teacher enters student information (name, student ID number, grades, etc.) into the input form and presses the send button.

[0790] Input: Student information (name, student ID number, grades)

[0791] Server: The server receives the input information and saves it in the database. Specifically, it executes an INSERT query on the MySQL database and stores the information in storage.

[0792] Output: Save complete response

[0793] Specific operation: A teacher enters new student information into the student registration form on the terminal, which is then sent to the server. The server saves the information in the database and returns a "Saving completed" message to the teacher's terminal.

[0794] Step 2: View Student Information

[0795] Terminal: The teacher enters the student's student ID number into the search form and presses the search button.

[0796] Input: Student ID number

[0797] Server: The server uses a SELECT query to retrieve the student's information from the database based on the received student ID number.

[0798] Output: Student information

[0799] Specific operation: When a teacher enters a student ID number and presses the search button, the server retrieves the relevant student's information from the database and displays it on the teacher's terminal.

[0800] Online Learning Platform

[0801] Processing Steps

[0802] Step 1: Upload your materials

[0803] Terminal: The teacher selects the teaching material file and presses the upload button.

[0804] Input: Teaching material file

[0805] Server: The server receives the uploaded file and saves it in the specified directory of the web application.

[0806] Output: Upload complete response

[0807] Specific operation: The teacher selects a teaching material file and uploads it to the server. The server saves the file in a specific directory and returns an "upload complete" message to the teacher.

[0808] Step 2: Download the materials

[0809] Device: Students log in to the web application and select the materials they want to download from the list of materials.

[0810] Input: Download request (teaching material ID)

[0811] Server: The server acquires the selected teaching material file and sends it to the student's terminal.

[0812] Output: Teaching material file

[0813] Specific operation: When a student selects a teaching material and presses the download button, the server sends the teaching material file to the student's device and the download begins.

[0814] Shared Document Management System

[0815] Processing Steps

[0816] Step 1: Share the document

[0817] Terminal: The teacher selects the shared document and uploads it to the specified folder.

[0818] Input: Shared Documents

[0819] Server: The server receives the uploaded shared documents and stores them in a specified directory.

[0820] Output: Sharing complete response

[0821] Specific operation: When a teacher selects a shared document and presses the upload button, the server saves the document in the specified directory and returns a message saying "Sharing completed."

[0822] Step 2: Edit the document

[0823] Device: The teacher accesses the shared document and makes any necessary edits.

[0824] Input:Edit

[0825] Server: The server receives the edits and updates the document, optionally providing version control.

[0826] Output: Update complete response

[0827] Specific behavior: When a teacher accesses a shared document, makes edits, and saves the content, the server updates the document and returns a message that the update is complete.

[0828] Electronic Scoring System

[0829] Processing Steps

[0830] Step 1: Upload your exam answers

[0831] Terminal: The teacher selects the scanned test answer sheet and presses the upload button.

[0832] Input: Scanned image of the test answer sheet

[0833] Server: The server receives the uploaded scanned images and stores them in a specified directory.

[0834] Output: Upload complete response

[0835] Specific operation: The teacher scans the exam answers and uploads the image to the server. The server saves the image and returns a message saying "upload completed."

[0836] Step 2: Automated scoring

[0837] Server: The server analyzes the test answer images using the OpenCV library and automatically scores the answers using Scikit-learn.

[0838] Input: Scanned image of the test answer sheet

[0839] Output:Scoring results

[0840] What it does: The server analyzes the scanned image, automatically scores it using a machine learning model, and stores the results in a database.

[0841] Step 3: Check your results

[0842] Terminal: The teacher accesses the server to check the grading results.

[0843] Input: Grading result inquiry request

[0844] Server: The server retrieves the grading results from the database and sends them to the teacher's terminal.

[0845] Output:Scoring results

[0846] Specific operation: The teacher checks the grading results on their device, and the information is retrieved from the server and displayed on the teacher's device.

[0847] Through these steps, the system enables management of student information, support for online learning, information sharing among teachers, and efficient grading.

[0848] (Application example 1)

[0849] 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."

[0850] In conventional educational systems, functions such as managing student information, providing teaching materials, sharing lesson plans, and grading assignments are distributed, making it difficult to operate them centrally. As a result, teachers' work becomes complicated and they are unable to provide effective educational support. In addition, there are limited ways for students to instantly check their learning progress and grades, hindering learning efficiency. Furthermore, the inconvenient management of annotations and notes on digital teaching materials makes it difficult to deepen learning content.

[0851] 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.

[0852] In this invention, the server includes a school information management means for centrally managing student information and making it accessible to teachers, an online learning means for providing digital teaching materials so that students can study online, a shared document management means for allowing teachers to share teaching materials and lesson plans, an electronic grading means for automatically grading test questions and assignments, a mobile access means for checking students' learning progress and grades from their smartphones, a digital annotation means for adding annotations to digital teaching materials and viewing them, and an electronic notification means for automatically grading submitted assignments and notifying the results. This makes it possible to improve the efficiency of teachers' work and students' learning.

[0853] "School information management means" refers to a means for centrally managing information such as student grades, attendance, and history, and making it accessible to teachers.

[0854] "Online learning means" means means by which educational materials are provided in digital format and students can learn online.

[0855] "Shared document management means" refers to a means by which teachers can share and manage teaching materials and lesson plans.

[0856] "Electronic marking means" means a means for automatically marking test questions or assignments and providing the results.

[0857] "Mobile access means" refers to a means that allows students to check their learning progress and grades from their smartphones.

[0858] "Digital annotation means" refers to a means for annotating and viewing digital teaching materials.

[0859] "Electronic notification means" refers to a means for automatically grading assignment submissions and notifying the results.

[0860] This invention is a system that includes a unified management of student information, a means for students to study online, a means for teachers to share teaching materials and lesson plans, a means for automatically grading test questions and assignments, a means for checking learning progress and grades from a smartphone, a means for annotating and viewing digital teaching materials, and a means for automatically grading submitted assignments and notifying the results. Specific methods for realizing this system are described below.

[0861] Hardware and Software Configuration

[0862] This system is mainly composed of three main elements: a server, a terminal, and a user.

[0863] server

[0864] The server has a central database for unifying student information and stores various information (grades, attendance, history, etc.). The server runs a software framework (e.g., Flask) for managing the provision of digital learning materials, automatic grading of assignments, and notification of grades. SQLite is used as the database.

[0865] Centralized management of student information: Provides API endpoints to make student information more accessible to teachers and handles data requests and responses.

[0866] Providing digital learning materials: Stores learning materials uploaded by teachers and makes them available for students to download.

[0867] Shared Document Management: Manage, store, and provide shared access to documents shared among faculty members.

[0868] Electronic grading: Automatically grade exam questions and assignments and store the results.

[0869] Terminal

[0870] The device (smartphone or PC) provides an interface for users to access the server, and students download digital learning materials, annotate them, and submit assignments from the device.

[0871] Mobile access: Provide students with an interface to check their progress and grades using their smartphones.

[0872] Digital annotation: A function that allows you to add notes and annotations to digital teaching materials.

[0873] Electronic notifications: Has the function of notifying assignment grading results in real time.

[0874] Specific examples

[0875] Here are some specific scenarios where this system can be used:

[0876] 1. Student grade management: When a teacher sends a request to view a student's grades from their device to the server, the server retrieves the student's grades from the database and returns them to the teacher's device. The teacher can then check the grades on their smartphone.

[0877] 2. Online lessons: Teachers upload digital learning materials to a server, and students download them from their smartphones. Students annotate the downloaded materials and progress with their learning.

[0878] 3. Electronic grading: When teachers send exam answer sheets from their devices to the server, the server automatically grades them using the electronic grading system and stores the results in a database. Students are notified of the grade results via their smartphones.

[0879] Prompt Sentence Examples

[0880] The questions are automatically scored by inputting the following prompts into the generative AI model:

[0881] Teacher-created math assignment answers:

[0882] Q1: B

[0883] Q2: B

[0884] Q3: A

[0885] Please rate this.

[0886] In this way, a system is provided that can improve the efficiency of teachers' work and students' learning.

[0887] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0888] Step 1:

[0889] Requester: User (teacher)

[0890] Processing content: The teacher sends a request to the server from the terminal to view the student's grades.

[0891] Input: Student ID entered on the teacher's device.

[0892] Data processing: Generate an HTTP request including the student ID.

[0893] Output: A request containing the student ID is sent to the server.

[0894] Specific operations: The teacher enters the ID of the student whose grades they want to check into their smartphone or computer and presses the "Check Grades" button.

[0895] Step 2:

[0896] Requested by: Server

[0897] Processing content: The server retrieves the student's grades from the database.

[0898] Input: A request containing a student ID.

[0899] Data processing: Generate a database query to obtain the student's academic performance information.

[0900] Output: Academic information for the student.

[0901] Specific operation: The server issues a query to the database using the received student ID and extracts the student's grade information.

[0902] Step 3:

[0903] Requested by: Server

[0904] Processing content: The server returns the grade information it has acquired to the teacher's terminal.

[0905] Input: Academic information for the student in question.

[0906] Data processing: Generate an HTTP response containing performance information.

[0907] Output: A response containing grade information is sent to the teacher's terminal.

[0908] Specific operation: The server sends the grade information obtained from the database to the teacher's terminal as an HTTP response.

[0909] Step 4:

[0910] Requester: User (teacher)

[0911] Processing details: Teachers check students' grade information on their smartphones or computers.

[0912] Input: Achievement information received from the server.

[0913] Data processing: Convert received grade information into a display format.

[0914] Output: Student grades are displayed on the screen.

[0915] Specific actions: The teacher checks the grade information displayed on the device and takes the necessary action.

[0916] Step 5:

[0917] Requester: User (student)

[0918] What happens: Students log in to an online learning platform from their home devices and download the learning materials provided by their teachers.

[0919] Input: Login information, request for materials.

[0920] Data processing: Authenticating login information and processing requests for learning materials.

[0921] Output: Teaching material data.

[0922] Specific operation: Students log in to their devices, search for the teaching materials uploaded by the teacher, and press the download button.

[0923] Step 6:

[0924] Requested by: Server

[0925] Processing content: The server provides teaching material data in response to student requests.

[0926] Input: Student materials request.

[0927] Data processing: Search for teaching material data and include it in the HTTP response.

[0928] Output: A response containing the teaching material data is sent to the student's device.

[0929] Specific operation: The server retrieves digital learning materials from the database and provides them to students in a downloadable format.

[0930] Step 7:

[0931] Requested by: Server

[0932] Processing content: The server inputs the submitted assignment into a generative AI model and performs automatic grading.

[0933] Input: Submitted assignment response data.

[0934] Data processing: The answer data is fed into the generative AI model to obtain the scoring results.

[0935] Output: Scoring results.

[0936] Specific operation: The server inputs the assignments submitted by the students into the generative AI model and generates the grading results.

[0937] Step 8:

[0938] Requested by: Server

[0939] Processing details: The server saves the grading results in a database and notifies the teacher's terminal.

[0940] Input:Scoring results.

[0941] Data processing: The grading results are stored in a database and notifications are sent to teachers.

[0942] Output: Saved grading results, notifications.

[0943] Specific operation: The server saves the generated grading results in a database and sends a notification to the teacher's terminal saying "The grading results have been updated."

[0944] Step 9:

[0945] Requester: User (teacher)

[0946] Processing details: Teachers check the grading results on their smartphones or computers.

[0947] Input: Notification from the server.

[0948] Data processing: Retrieve the scoring results from the database and convert them into a display format.

[0949] Output: The results are displayed on the screen.

[0950] Specific operation: The teacher clicks on the notification on the device and checks the grading results.

[0951] In this way, the present invention provides a system that can manage student information, provide digital teaching materials, automatically grade assignments, manage grades, and check progress on a smartphone in an integrated manner.

[0952] 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.

[0953] This invention relates to a system that combines the centralized management of student information, provision of digital teaching materials, shared document management, and electronic grading functions with an emotion engine that recognizes user emotions. This system is composed of three main elements: a server, a terminal, and a user. The emotion engine recognizes user emotions and reflects them in the system, with the aim of further improving the quality of education. We will now explain in detail how each element works together and how the invention is specifically implemented.

[0954] A centralized student information management system

[0955] server

[0956] The server centrally manages student grades, attendance information, and records, making them accessible to teachers. This allows teachers to quickly obtain the information they need. Furthermore, the emotion engine stores students' emotional information on the server, enabling comprehensive information management.

[0957] For example, if a teacher wants to check the grades and recent emotional state of a specific student, a request is sent from the device. The server retrieves the student's grades and emotional state from the database and returns them to the teacher's device.

[0958] Online Learning Platform

[0959] server

[0960] The server provides digital learning materials and assignments for users (teachers and students) to access. Teachers upload learning materials, and students can view and study them online. The emotion engine recognizes students' emotional state in real time during online learning, improving the effectiveness of their learning.

[0961] For example, when a teacher uploads a new assignment, the server stores the data and students download it to study. The emotion engine monitors students' emotions as they work on the assignment and provides feedback according to their learning progress.

[0962] Terminal

[0963] The terminal provides an interface for users to access the server and upload or download learning materials. It also has an emotion engine that recognizes users' emotions in real time.

[0964] Example: When a student logs into an online learning platform from their home device and downloads materials provided by their teacher to study, the emotion engine recognizes the student's emotional state and displays advice to optimize learning efficiency.

[0965] Shared Document Management System

[0966] server

[0967] The server provides a system that allows teachers to share teaching materials and lesson plans, and stores and updates the shared documents. The emotion engine strengthens the collaborative system among teachers by monitoring the viewing status of the shared documents and the emotional state of the viewers.

[0968] Example: Teacher A uploads a lesson plan he created to the server, and when Teacher B views the document, the emotion engine recognizes Teacher B's reaction and provides feedback.

[0969] Electronic Scoring System

[0970] server

[0971] The server automatically grades submitted exam questions and assignments and stores the results in a database. In addition, an emotion engine monitors the student's emotional state when answering questions and takes this into account as a factor that may affect the grade.

[0972] Example: When a teacher uploads exam answers scanned on a device, the server processes the answers in an electronic scoring system, and the emotion engine analyzes the student's emotional state and notifies the teacher of the results.

[0973] Terminal

[0974] The device provides an interface for teachers to upload exam and assignment answers and view the automated marking results. It also has an emotion engine that monitors the teacher's reactions and emotional state.

[0975] Example: When a teacher uses a device at home to scan an answer sheet, send it to a server, and receive the results of automatic grading, the emotion engine recognizes the teacher's emotional state and makes suggestions to reduce stress.

[0976] Example

[0977] Example 1: Student performance management and emotion monitoring

[0978] 1. Send a request to view student grades from the teacher's device.

[0979] 2. The server retrieves the student's grades and emotional state from the database.

[0980] 3. The server sends the grade information and emotional state to the teacher's terminal, and the teacher checks the information.

[0981] Example 2: Online classes and emotional feedback

[0982] 1. The teacher uploads the teaching materials from the device to the server.

[0983] 2. The server stores the learning materials and makes them accessible to students.

[0984] 3. Students download the learning materials to their devices and proceed with their studies.

[0985] 4. The emotion engine monitors students' emotional state in real time while they are learning and provides appropriate feedback.

[0986] Example 3: Electronic scoring and sentiment analysis

[0987] 1. The teacher sends the exam answer sheet from the terminal to the server.

[0988] 2. The server uses an electronic scoring system to automatically score the tests.

[0989] 3. The emotion engine analyzes the student's emotional state when answering and reflects this in the scoring results.

[0990] 4. The server sends the scoring results and emotion analysis results to the teacher's terminal, where the teacher can check them.

[0991] The system of the present invention significantly reduces the workload of teachers and enables them to effectively utilize their expertise. The introduction of an emotion engine provides feedback based on the user's emotional state, further improving the quality and efficiency of education.

[0992] The processing flow will be explained below.

[0993] A centralized student information management system

[0994] Process flow: Viewing student grades and emotional information

[0995] Step 1:

[0996] A user (teacher) sends a request from a terminal to view the grades and emotional information of a specific student.

[0997] Step 2:

[0998] The terminal forwards the request to the server.

[0999] Step 3:

[1000] A server accesses a database containing student performance and emotional information.

[1001] Step 4:

[1002] The server retrieves the student's grade information and emotion information from the database.

[1003] Step 5:

[1004] The server transmits the acquired performance information and emotion information to the terminal.

[1005] Step 6:

[1006] The terminal displays the received information on the screen, and the user (teacher) checks it.

[1007] Online Learning Platform

[1008] Process flow: Uploading teaching materials and monitoring emotions

[1009] Step 1:

[1010] The user (teacher) selects the teaching material file and sends an upload request from the terminal.

[1011] Step 2:

[1012] The terminal uploads the selected educational material file to the server.

[1013] Step 3:

[1014] The server stores the received teaching material file in a data storage.

[1015] Step 4:

[1016] The server sends a notification to the device that the upload is complete.

[1017] Step 5:

[1018] A user (student) sends a request to access the online learning platform from a terminal.

[1019] Step 6:

[1020] The terminal accesses the server and sends a request to acquire a list of available learning materials.

[1021] Step 7:

[1022] The server retrieves a list of available learning materials from the database and sends it to the terminal.

[1023] Step 8:

[1024] The terminal displays a list of teaching materials on the screen, which the user (student) can view.

[1025] Step 9:

[1026] The emotion engine analyzes the user's (student's) facial expressions and voice in real time to recognize their emotional state.

[1027] Step 10:

[1028] The emotion engine sends feedback to the device based on the recognized emotional state to improve learning efficiency.

[1029] Shared Document Management System

[1030] Process flow: Sharing lesson plans and emotional feedback

[1031] Step 1:

[1032] The user (teacher) selects a lesson plan document and sends a sharing request from their device.

[1033] Step 2:

[1034] The device uploads the document to the server.

[1035] Step 3:

[1036] The server saves the document in a shared folder and updates the sharing settings.

[1037] Step 4:

[1038] The server sends a notification of completion of sharing to the terminal.

[1039] Step 5:

[1040] Another user (teacher) sends a request from their device to find a shared lesson plan document.

[1041] Step 6:

[1042] The terminal accesses the shared folder and sends a request to the server to search for the document.

[1043] Step 7:

[1044] The server retrieves the document from the shared folder and sends it to the terminal.

[1045] Step 8:

[1046] The terminal displays the received document on the screen, and the user (teacher) views it.

[1047] Step 9:

[1048] The emotion engine analyzes the user's (teacher's) facial expressions and voice in real time and recognizes their reactions to shared documents.

[1049] Step 10:

[1050] The emotion engine sends feedback and improvement suggestions to the device based on the recognized emotional state.

[1051] Electronic Scoring System

[1052] Process flow: Automatic marking of assignments and sentiment analysis

[1053] Step 1:

[1054] The user (teacher) scans the students' answer sheets and sends a request from the terminal to upload them to the electronic marking system.

[1055] Step 2:

[1056] The device uploads the scanned image of the answer sheet to the server.

[1057] Step 3:

[1058] The server converts the received image data into text data using optical character recognition (OCR) technology.

[1059] Step 4:

[1060] The server applies an automatic scoring algorithm based on the text data.

[1061] Step 5:

[1062] The emotion engine analyzes the facial expressions and voice of students during their responses and generates emotional information.

[1063] Step 6:

[1064] The server stores the scoring results and emotion information in a database.

[1065] Step 7:

[1066] The server sends a notification including the grading results and emotion information to the teacher's terminal.

[1067] Step 8:

[1068] The terminal displays the received scoring results and emotion information on the screen, and the user (teacher) checks them.

[1069] Step 9:

[1070] The emotion engine analyzes teachers' reactions in real time and provides feedback and stress-reducing suggestions as appropriate.

[1071] Example 2

[1072] 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."

[1073] While traditional education systems require centralized management of student information and efficient online learning, they lack functionality such as emotion recognition and real-time feedback, making it difficult to maximize student learning outcomes. Furthermore, there are limited means to streamline teacher work, and strengthening cooperation among teachers and improving the accuracy of automated grading of exams and assignments are also issues.

[1074] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1075] In this invention, the server includes an information management means, an online learning means, a sharing management means, a scoring means, and an emotion recognition means. This makes it possible to:

[1076] 1. Students' grades, attendance, history and emotional information can be managed in an integrated manner.

[1077] 2. Efficient online learning can be achieved through the uploading, viewing, and editing of teaching materials, as well as real-time monitoring of students' emotional states.

[1078] 3. Teachers can strengthen collaboration and share teaching materials and lesson plans more efficiently.

[1079] 4. Exams and assignments can be graded automatically, and emotion recognition can be used to reflect emotional information in the grading results.

[1080] The "information management means" is a system including a database that comprehensively manages student grades, attendance information, history, and emotional information.

[1081] "Online learning means" means a system that includes functions for providing educational materials digitally and enabling students to learn online, and allows for the uploading, viewing, and modification of educational materials, as well as real-time monitoring of students' emotional state.

[1082] A "shared management tool" is a system that allows teachers to share teaching materials and lesson plans with each other.

[1083] A "grading tool" is a system that automatically grades exams and assignments.

[1084] The "emotion recognition means" is a system that recognizes the user's emotions in real time and reflects them in education.

[1085] This invention relates to a system that combines the functions of unified student information management, digital teaching materials provision, shared document management, and electronic grading with an emotion recognition engine that recognizes user emotions in real time. This system includes three main elements: a server, a terminal, and a user, and these elements work in conjunction with each other.

[1086] Hardware and software used

[1087] The system mainly uses the following hardware and software:

[1088] Server: Database and emotion recognition engine (e.g., SQL database, emotion recognition algorithm implemented in Python)

[1089] Device: The interface through which the user accesses the device (e.g., PC, tablet, dedicated application)

[1090] Users: Teachers and students

[1091] A centralized student information management system

[1092] server

[1093] The server maintains a database that comprehensively manages student grades, attendance, history, and emotional information. Upon request from a teacher, it retrieves the relevant student data and returns it to the teacher's device.

[1094] Example: When a teacher wants to check the grade information and emotional state of a particular student from his / her terminal, the server retrieves the information from the database and sends it to the teacher's terminal.

[1095] Online Learning Platform

[1096] server

[1097] The server digitally stores teaching materials uploaded by teachers and makes them available for students to access online. An emotion recognition engine also recognizes students' emotional state while they are studying and provides appropriate feedback.

[1098] Example: When a teacher uploads new learning materials, the server stores them and makes them available for students to view. An emotion recognition engine monitors students' emotional state while they are learning and generates feedback according to their learning progress.

[1099] Terminal

[1100] The device provides an interface for students to access online learning platforms, download learning materials, and study. It also includes an emotion recognition engine that can recognize users' emotions in real time.

[1101] Example: When a student is downloading learning materials from their home device and studying, an emotion recognition engine analyzes the student's emotional state and displays advice on how to relax if stress levels are rising.

[1102] Shared Document Management System

[1103] server

[1104] The server allows teachers to upload, save, and update shared documents. The emotion recognition engine monitors the viewing status of shared documents and the emotional state of the viewer, and provides feedback.

[1105] Example: When Teacher A uploads a shared document to the server and Teacher B views it, an emotion recognition engine analyzes Teacher B's reaction and provides Teacher A with feedback based on the reaction.

[1106] Electronic Scoring System

[1107] server

[1108] The server automatically grades test answers and assignments, storing the results in a database. An emotion recognition engine also analyzes the emotional state of students when they answer questions and reflects this in the grades.

[1109] Example: When a teacher scans an answer sheet and sends it to a server, the electronic scoring system automatically scores it and sends the results and sentiment analysis results to the teacher's device.

[1110] Terminal

[1111] The device provides an interface for teachers to upload exam and assignment answers and receive automated grading results. It also includes an emotion recognition engine that monitors teachers' reactions and emotional state.

[1112] Example: When a teacher scans an answer sheet using a device at home and sends it to a server, and receives the grading results and emotion analysis results, the emotion recognition engine monitors the teacher's stress level and suggests relaxation methods if necessary.

[1113] Example

[1114] Prompt Sentence Examples

[1115] "Please detail the procedures for faculty to monitor students' academic performance and emotional state."

[1116] "Please explain specific ways in which you can monitor students' emotional states in online learning platforms."

[1117] "Please show us specifically how you will perform sentiment analysis in your electronic scoring system and reflect it in the results."

[1118] This system will reduce the workload of teachers and maximize the learning effect of students. The introduction of an emotion recognition engine will enable real-time feedback, which is expected to further improve the quality of education.

[1119] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1120] A centralized student information management system

[1121] Step 1:

[1122] A teacher sends a request to view a student's grades on a terminal. The input is the teacher's identification information for the student (student ID, name, etc.). The terminal generates this request and sends it to the server. The output is the request data sent to the server.

[1123] Step 2:

[1124] The server receives the request and retrieves the student's grades and emotional state from the database. The input is the request data from the teacher. The server executes the database query to retrieve the grade information and emotional state information. The output is the retrieved data of the student's grades and emotional state.

[1125] Step 3:

[1126] The server returns the acquired information to the teacher's terminal. The input is the student's grades and emotional state data acquired by the server. The server structures this data and sends it to the teacher's terminal. The output is the grade information and emotional information acquired by the teacher.

[1127] Step 4:

[1128] The teacher checks the information on the terminal. The input is the grade information and emotional state data sent from the server. The teacher displays and checks the received information through the terminal interface. The output is information that the teacher uses to make decisions.

[1129] Online Learning Platform

[1130] Step 1:

[1131] The teacher uploads the teaching material from the terminal. The input is the digital teaching material file and related metadata (title, description, etc.). The terminal collects this data and sends it to the server. The output is the uploaded data to the server.

[1132] Step 2:

[1133] The server stores the teaching materials and sets them up so that students can access them. The input is the teaching material data and metadata sent by the teacher. The server stores this in a database and sets permissions so that students can access it. The output is the teaching materials stored and accessible.

[1134] Step 3:

[1135] Students download learning materials to their devices and progress with their studies. The input is the student sending a download request and the learning material data stored on the server. The device generates a request and retrieves the learning material from the server. The output is the learning material data downloaded to the student's device.

[1136] Step 4:

[1137] The emotion engine monitors students' emotional states in real time and provides feedback. The input is data such as the student's facial expressions, voice volume, and tone of voice obtained from the device's camera and microphone. The emotion engine analyzes this data and estimates the student's emotional state. The output is advice and recommendations presented to the student as real-time feedback.

[1138] Shared Document Management System

[1139] Step 1:

[1140] The teacher uploads a shared document from a terminal. The input is the shared document file and related metadata. The terminal sends these to the server. The output is the uploaded data to the server.

[1141] Step 2:

[1142] The server saves the document and sets it up so that other teachers can access it. The input is the shared document data sent by the teacher. The server saves it in a database and sets permissions so that other teachers can access it. The output is the saved document and access right setting data.

[1143] Step 3:

[1144] Another teacher views the document on their device. The input is a view request and the document data stored on the server. The device generates a request and retrieves the document from the server. The output is the document data displayed on the teacher's device.

[1145] Step 4:

[1146] The emotion engine monitors the viewer's emotional state and provides feedback. The input is data such as the teacher's facial expression, voice volume, and tone obtained from the device's camera and microphone. The emotion engine analyzes this data and estimates the teacher's emotional state. The output is advice and recommendations that are presented to the teacher as feedback during viewing.

[1147] Electronic Scoring System

[1148] Step 1:

[1149] The teacher sends the exam answer sheet from the terminal. The input is a digital file of the scanned exam answer sheet. The terminal sends this to the server. The output is the exam answer data sent to the server.

[1150] Step 2:

[1151] The server uses an electronic marking system to perform marking. The input is test answer data. The server calls the electronic marking system and automatically performs marking. The output is marking result data.

[1152] Step 3:

[1153] The emotion engine analyzes the emotional state of the student when answering. The input is facial expression and voice data recorded when answering. The emotion engine analyzes this and estimates the emotional state. The output is emotion analysis result data.

[1154] Step 4:

[1155] The server sends the scoring results and sentiment analysis results to the teacher's terminal. The input is the scoring result data and sentiment analysis result data. The server structures these and sends them to the teacher's terminal. The output is the scoring results and sentiment analysis results received by the teacher.

[1156] Step 5:

[1157] The teacher checks the grading results and sentiment analysis results on the terminal. The input is the grading results and sentiment analysis results received from the server. The teacher displays and checks this information on the terminal. The output is information that the teacher can use to make decisions.

[1158] (Application example 2)

[1159] 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."

[1160] Existing educational systems manage students' grades and learning progress without considering their emotional state, making it difficult to provide optimal instruction and feedback to individual students. Furthermore, general online shopping sites lack a means to provide a personalized shopping experience that reflects users' emotional state. There is a need to address these issues, improve the quality and efficiency of education, and enhance the user experience of online shopping.

[1161] 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.

[1162] In this invention, the server includes an information management means, a learning means, a shared document management means, a scoring means, and an emotion-aware shopping assistant means, thereby enabling a comprehensive education and shopping experience that takes into account the user's emotions.

[1163] "Information management means" refers to the part of the system that centrally manages students' grades, attendance information, and records, and allows teachers to access this information.

[1164] "Learning tools" are the system's capabilities to provide learning materials digitally and enable students to learn online.

[1165] The "shared document management tool" is part of a system that provides the ability for teachers to share teaching materials and lesson plans and edit them collaboratively.

[1166] A "grading tool" is a system that has the function of automatically grading test questions and assignments and providing the results to teachers.

[1167] The "emotion recognition shopping assistant means" is a system function that analyzes the user's facial expressions and voice to recognize their emotions, and then makes product recommendations and promotions based on this.

[1168] The system for implementing this invention mainly comprises a server, a terminal, and a user. Each of these components will be described in detail below.

[1169] Information management means

[1170] The information management system is provided by a server and is a system that centrally manages student grades, attendance information, and records. Teachers can access this information using their terminals and quickly obtain the data they need. The data is stored and managed in a database on the server.

[1171] Learning tools

[1172] Learning tools are provided by a server. The server provides learning materials and assignments in digital format, and students can study online using their devices. Teachers upload learning materials to the server, and students download them to study. The system is also equipped with an emotion engine that provides feedback based on students' emotional state.

[1173] Shared document management tools

[1174] The shared document management system is provided by a server and allows teachers to share teaching materials and lesson plans. Teachers can upload documents from their devices, and other teachers can view and edit them collaboratively. The emotion engine also monitors the emotional state of viewers and provides effective feedback.

[1175] Scoring method

[1176] The grading method is a function in which the server automatically grades submitted exam questions and assignments. When teachers scan and upload answer sheets from their devices, the server processes them with an electronic grading system. In addition, an emotion engine monitors the students' emotional state when answering, and this is also reflected in the grading results.

[1177] Emotion-aware shopping assistant

[1178] The emotion-aware shopping assistant uses the user's terminal or smart device (e.g., smartphone or tablet) to analyze the user's facial expressions and voice to recognize emotions. Based on the recognized emotions, the server provides appropriate product recommendations and promotions. This allows the user to have an individualized shopping experience.

[1179] Hardware and software used

[1180] Hardware used: smartphone, tablet, PC, camera

[1181] Software used: Python, Flask, OpenCV, TextBlob

[1182] Processing flow

[1183] The specific process flow is implemented based on the following steps:

[1184] 1. Obtain the user's camera video and audio input.

[1185] 2. The captured video is analyzed using OpenCV and the face_recognition library to analyze the user's facial expressions and recognize their emotional state.

[1186] 3. The voice input (or text) is analyzed with the TextBlob library to determine the user's sentiment as text.

[1187] 4. Based on the results of sentiment and text analysis, the server recommends appropriate products and promotions to the user.

[1188] Specific examples

[1189] 1. When a user opens an online shopping app on their smartphone, if the camera recognizes the user's face and determines that they are "Happy," the app will recommend "new fashion items that perfectly match their current mood."

[1190] 2. When a user asks "What are your recent recommendations?" using voice input, TextBlob analyzes the voice text, and if it is determined to be "positive," it suggests products with many positive reviews.

[1191] Prompt Sentence Examples

[1192] 1. "Analyze this user's facial expressions and voice to determine their emotional state."

[1193] 2. "What promotion should I offer if the user has a smiling face?"

[1194] This provides a holistic education and purchasing experience that takes into account the user's emotions.

[1195] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1196] Step 1:

[1197] The user launches the application on their device (smartphone or tablet).

[1198] Input: Launching an app on a smartphone or tablet.

[1199] Output: The app starts and goes to the initial screen.

[1200] Step 2:

[1201] The device's camera captures the user's face and obtains video data in real time.

[1202] Input: Camera image (user's face).

[1203] Output: Captured video frames.

[1204] Step 3:

[1205] The video data acquired by the device is analyzed using OpenCV and the face_recognition library to recognize the user's facial expressions.

[1206] Input: Captured video frames.

[1207] Output: Recognized facial expression data (e.g. smile, sadness).

[1208] Step 4:

[1209] The user speaks and the device captures the speech and converts it into text.

[1210] Input: Audio data.

[1211] Output: Audio converted to text data.

[1212] Step 5:

[1213] The device uses the TextBlob library to analyze the sentiment of the text converted from the audio data.

[1214] Input: Text data.

[1215] Output: Sentiment analysis result (e.g. positive, negative).

[1216] Step 6:

[1217] The device sends facial expression data and text analysis results to the server.

[1218] Input: facial expression data, emotion analysis results.

[1219] Output: Sending data to the server.

[1220] Step 7:

[1221] The server determines product recommendations and promotions based on the received data according to the user's emotional state.

[1222] Input: facial expression data, emotion analysis results.

[1223] Output: Recommendation data, promotion data.

[1224] Step 8:

[1225] The server transmits recommendation data and promotion data to the terminal.

[1226] Input: Recommendation data, Promotion data.

[1227] Output: Sending data to a terminal.

[1228] Step 9:

[1229] The device displays the received recommendations and promotions to the user.

[1230] Input: Recommendation data, Promotion data.

[1231] Output: Recommendations and promotion information displayed in a user interface.

[1232] 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.

[1233] 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.

[1234] 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.

[1235] [Third embodiment]

[1236] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1237] 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.

[1238] 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).

[1239] 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.

[1240] 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.

[1241] 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).

[1242] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1243] 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.

[1244] 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.

[1245] 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.

[1246] 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.

[1247] 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."

[1248] This invention relates to a system that includes the centralized management of student information, provision of digital teaching materials, shared document management, and electronic grading functions. This system consists of three main elements: a server, a terminal, and a user. We will explain in detail how each element works together and how the invention is specifically implemented.

[1249] A centralized student information management system

[1250] server

[1251] The server centrally manages student grades, attendance information, and records, making them accessible to teachers, allowing them to quickly obtain the information they need.

[1252] For example, if a teacher wants to check the grades of a specific student, a request is sent from the terminal. The server retrieves the grades of the student from the database and returns them to the teacher's terminal.

[1253] Online Learning Platform

[1254] server

[1255] The server provides digital learning materials and assignments, making them accessible to users (teachers and students). Teachers upload learning materials, and students can view and study them online.

[1256] Example: When a teacher uploads a new assignment, the server stores the data and students download it to study.

[1257] Terminal

[1258] The terminal provides an interface for the user to access the server and upload or download educational materials.

[1259] Example: A student logs into an online learning platform from their home device, downloads materials provided by their teacher, and studies.

[1260] Shared Document Management System

[1261] server

[1262] The server provides a system that allows teachers to share teaching materials and lesson plans with each other, and stores and updates shared documents, making it easier for teachers to share teaching materials with each other.

[1263] Example: Teacher A uploads a lesson plan he created to the server, and Teacher B can also view and download the plan.

[1264] Electronic Scoring System

[1265] server

[1266] The server automatically grades submitted exam questions and assignments and stores the results in a database, significantly reducing the grading workload for teachers.

[1267] Example: When a teacher uploads exam answers scanned on a device, the server processes the answers in an electronic scoring system and returns the scoring results to the teacher's device.

[1268] Terminal

[1269] The device provides an interface for teachers to upload exam and assignment answers and view the automatically graded results.

[1270] Example: A teacher uses a device at home to scan answer sheets, send them to a server, and receive the results of automatic grading.

[1271] Example

[1272] Example 1: Student Grade Management

[1273] 1. Send a request to view student grades from the teacher's device.

[1274] 2. The server retrieves the student's grades from the database.

[1275] 3. The server sends the grade information to the teacher's terminal, where the teacher can view the information.

[1276] Example 2: Online classes

[1277] 1. The teacher uploads the teaching materials from the device to the server.

[1278] 2. The server stores the learning materials and makes them accessible to students.

[1279] 3. Students download the learning materials to their devices and proceed with their studies.

[1280] Example 3: Electronic marking

[1281] 1. The teacher sends the exam answer sheet from the terminal to the server.

[1282] 2. The server uses an electronic scoring system to automatically score the tests.

[1283] 3. The server stores the grading results in a database and sends them to the teacher's device.

[1284] The system of the present invention significantly reduces the workload of teachers and enables them to effectively utilize the expertise of each teacher, thereby enabling them to provide higher quality education.

[1285] The processing flow will be explained below.

[1286] A centralized student information management system

[1287] Process flow: View student grades

[1288] Step 1:

[1289] A user (teacher) sends a request from a terminal to view the grades of a specific student.

[1290] Step 2:

[1291] The terminal forwards the request to the server.

[1292] Step 3:

[1293] The server accesses the database and obtains the grade information of the student.

[1294] Step 4:

[1295] The server transmits the acquired score information to the terminal.

[1296] Step 5:

[1297] The terminal displays the received grade information on the screen, and the user (teacher) checks it.

[1298] Online Learning Platform

[1299] Process flow: Uploading and viewing teaching materials

[1300] Step 1:

[1301] The user (teacher) selects the teaching material file and sends an upload request from the terminal.

[1302] Step 2:

[1303] The terminal uploads the selected educational material file to the server.

[1304] Step 3:

[1305] The server stores the received teaching material file in a data storage.

[1306] Step 4:

[1307] The server sends a notification to the device that the upload is complete.

[1308] Step 5:

[1309] A user (student) sends a request to access the online learning platform from a terminal.

[1310] Step 6:

[1311] The terminal accesses the server and sends a request to acquire a list of available learning materials.

[1312] Step 7:

[1313] The server retrieves a list of available learning materials from the database and sends it to the terminal.

[1314] Step 8:

[1315] The terminal displays a list of teaching materials on the screen, which the user (student) can view.

[1316] Shared Document Management System

[1317] Process flow: Sharing lesson plans

[1318] Step 1:

[1319] The user (teacher) selects a lesson plan document and sends a sharing request from their device.

[1320] Step 2:

[1321] The device uploads the document to the server.

[1322] Step 3:

[1323] The server saves the document in a shared folder and updates the sharing settings.

[1324] Step 4:

[1325] The server sends a notification of completion of sharing to the terminal.

[1326] Step 5:

[1327] Another user (teacher) sends a request from their device to find a shared lesson plan document.

[1328] Step 6:

[1329] The terminal accesses the shared folder and sends a request to the server to search for the document.

[1330] Step 7:

[1331] The server retrieves the document from the shared folder and sends it to the terminal.

[1332] Step 8:

[1333] The terminal displays the received document on the screen, and the user (teacher) views it.

[1334] Electronic Scoring System

[1335] Process flow: Automatic grading of assignments

[1336] Step 1:

[1337] The user (teacher) scans the students' answer sheets and sends a request from the terminal to upload them to the electronic marking system.

[1338] Step 2:

[1339] The device uploads the scanned image of the answer sheet to the server.

[1340] Step 3:

[1341] The server converts the received image data into text data using optical character recognition (OCR) technology.

[1342] Step 4:

[1343] The server applies an automatic scoring algorithm based on the text data.

[1344] Step 5:

[1345] The server stores the results of the scoring in a database.

[1346] Step 6:

[1347] The server transmits the automatic scoring results to the terminal.

[1348] Step 7:

[1349] The terminal displays the received grading results on the screen, and the user (teacher) checks them.

[1350] Example 1

[1351] 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."

[1352] In today's educational settings, a wide range of functions are required, such as the centralized management of student information, the digital provision of teaching materials, information sharing among teachers, and automatic grading of exams and assignments. In conventional systems, these functions are separate, which not only makes it time-consuming to consolidate and manage information, but also increases the workload of teachers. For this reason, a system that can integrate and manage these functions centrally is needed.

[1353] 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.

[1354] In this invention, the server includes an information management means for centrally managing student information and making it accessible to teachers, a learning means for providing digital learning materials so that students can study online, a document management means for allowing teachers to share learning materials and lesson plans, a grading means for automatically grading test questions and assignments, a grade management means for viewing and updating student grade information, an attendance management means for managing and analyzing student attendance information, a learning material uploading means for teachers to upload learning materials so that students can study online, an assignment submission means for students to submit assignments online, a document editing means for teachers to edit and save shared documents, and an exam answer uploading means for uploading and analyzing exam answers. This reduces the workload of teachers and improves the learning environment for students.

[1355] "Student information" refers to information related to individuals, such as the name, student ID number, grades, attendance information, and history of students belonging to a school.

[1356] "Information management" is a means of centrally managing student information and providing teachers with the ability to access, view, and edit it as needed.

[1357] "Learning medium" refers to the means by which learning materials are provided in digital format and students learn online.

[1358] "Document management" is a means by which teachers can share teaching materials and lesson plans, and edit and save them as needed.

[1359] A "grading tool" is a tool that automatically grades submitted test questions and assignments and manages the results.

[1360] A "grade management tool" is a means by which students' grade information can be viewed and updated, and is a system that allows teachers to quickly obtain the information they need.

[1361] The "attendance management means" is a means for managing and analyzing daily attendance information and understanding patterns of absence and lateness.

[1362] The "teaching material uploading means" is a means for uploading teaching materials created by teachers to a server so that students can download them and study.

[1363] "Assignment submission means" refers to the means by which students submit assignments online.

[1364] "Document editing means" refers to a means for teachers to edit and save shared documents.

[1365] The "test answer uploading means" is a means by which a teacher uploads test answers to a server, analyzes them, and grades them.

[1366] The present invention is a system that integrates the functions of unified management of student information, provision of digital teaching materials, management of shared documents, and electronic grading. A specific embodiment of this system will be described in detail below.

[1367] A centralized student information management system

[1368] The server centrally manages student information, including grades, attendance, and history, in a MySQL database. Teachers using terminals can access the server via a web browser to register, view, and update student information.

[1369] Specific examples

[1370] When a teacher enters the information of a new student into the terminal and presses the submit button, the server stores the information in a MySQL database. When a teacher enters a student ID number to view the grade information of a specific student, the server retrieves the information from the database and displays it on the teacher's terminal.

[1371] Online Learning Platform

[1372] The server provides teaching materials and assignments in digital format and allows users (teachers and students) to access them. Web applications built using web frameworks (e.g., Django or Rails) are used. Users using terminals can perform operations such as uploading and downloading teaching materials and submitting assignments.

[1373] Specific examples

[1374] When a teacher uploads new learning materials to the server, the materials are stored in a directory within the web application. Students can log in, download the materials, and proceed with their studies. Students who have completed their assignments can upload them from their devices and store them on the server.

[1375] Shared Document Management System

[1376] The server provides a document management system that allows teachers to share teaching materials and lesson plans. It connects with cloud services such as Google Docs and Microsoft Office 365 to manage access and editing of shared documents. Teachers using devices can access documents and edit and save them as needed.

[1377] Specific examples

[1378] When Teacher A uploads a lesson plan, other teachers can view and download it. For example, if you are using Google Docs, Teacher B can co-edit the document.

[1379] Electronic Scoring System

[1380] The server uses Python's OpenCV and Scikit-learn libraries to automatically grade exam questions and assignments. Teachers using terminals can upload scanned exam answers to the server and check the graded results online.

[1381] Specific examples

[1382] When a teacher scans and sends the test answers from their device to the server, the server analyzes the answers using OpenCV, automatically scores them using Scikit-learn, and returns the results to the teacher's device.

[1383] Prompt Sentence Examples

[1384] 1. "Please give an overview of your student information management system."

[1385] 2. "Please briefly explain the features of your online learning platform."

[1386] 3. "Please explain the technical details of the electronic marking system."

[1387] This reduces the workload of teachers and improves the learning environment for students. The system also provides users with intuitive operation through its interface, improving the quality of education.

[1388] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1389] A centralized student information management system

[1390] Processing Steps

[1391] Step 1: Register student information

[1392] Terminal: The teacher enters student information (name, student ID number, grades, etc.) into the input form and presses the send button.

[1393] Input: Student information (name, student ID number, grades)

[1394] Server: The server receives the input information and saves it in the database. Specifically, it executes an INSERT query on the MySQL database and stores the information in storage.

[1395] Output: Save complete response

[1396] Specific operation: A teacher enters new student information into the student registration form on the terminal, which is then sent to the server. The server saves the information in the database and returns a "Saving completed" message to the teacher's terminal.

[1397] Step 2: View Student Information

[1398] Terminal: The teacher enters the student's student ID number into the search form and presses the search button.

[1399] Input: Student ID number

[1400] Server: The server uses a SELECT query to retrieve the student's information from the database based on the received student ID number.

[1401] Output: Student information

[1402] Specific operation: When a teacher enters a student ID number and presses the search button, the server retrieves the relevant student's information from the database and displays it on the teacher's terminal.

[1403] Online Learning Platform

[1404] Processing Steps

[1405] Step 1: Upload your materials

[1406] Terminal: The teacher selects the teaching material file and presses the upload button.

[1407] Input: Teaching material file

[1408] Server: The server receives the uploaded file and saves it in the specified directory of the web application.

[1409] Output: Upload complete response

[1410] Specific operation: The teacher selects a teaching material file and uploads it to the server. The server saves the file in a specific directory and returns an "upload complete" message to the teacher.

[1411] Step 2: Download the materials

[1412] Device: Students log in to the web application and select the materials they want to download from the list of materials.

[1413] Input: Download request (teaching material ID)

[1414] Server: The server acquires the selected teaching material file and sends it to the student's terminal.

[1415] Output: Teaching material file

[1416] Specific operation: When a student selects a teaching material and presses the download button, the server sends the teaching material file to the student's device and the download begins.

[1417] Shared Document Management System

[1418] Processing Steps

[1419] Step 1: Share the document

[1420] Terminal: The teacher selects the shared document and uploads it to the specified folder.

[1421] Input: Shared Documents

[1422] Server: The server receives the uploaded shared documents and stores them in a specified directory.

[1423] Output: Sharing complete response

[1424] Specific operation: When a teacher selects a shared document and presses the upload button, the server saves the document in the specified directory and returns a message saying "Sharing completed."

[1425] Step 2: Edit the document

[1426] Device: The teacher accesses the shared document and makes any necessary edits.

[1427] Input:Edit

[1428] Server: The server receives the edits and updates the document, optionally providing version control.

[1429] Output: Update complete response

[1430] Specific behavior: When a teacher accesses a shared document, makes edits, and saves the content, the server updates the document and returns a message that the update is complete.

[1431] Electronic Scoring System

[1432] Processing Steps

[1433] Step 1: Upload your exam answers

[1434] Terminal: The teacher selects the scanned test answer sheet and presses the upload button.

[1435] Input: Scanned image of the test answer sheet

[1436] Server: The server receives the uploaded scanned images and stores them in a specified directory.

[1437] Output: Upload complete response

[1438] Specific operation: The teacher scans the exam answers and uploads the image to the server. The server saves the image and returns a message saying "upload completed."

[1439] Step 2: Automated scoring

[1440] Server: The server analyzes the test answer images using the OpenCV library and automatically scores the answers using Scikit-learn.

[1441] Input: Scanned image of the test answer sheet

[1442] Output:Scoring results

[1443] What it does: The server analyzes the scanned image, automatically scores it using a machine learning model, and stores the results in a database.

[1444] Step 3: Check your results

[1445] Terminal: The teacher accesses the server to check the grading results.

[1446] Input: Grading result inquiry request

[1447] Server: The server retrieves the grading results from the database and sends them to the teacher's terminal.

[1448] Output:Scoring results

[1449] Specific operation: The teacher checks the grading results on their device, and the information is retrieved from the server and displayed on the teacher's device.

[1450] Through these steps, the system enables management of student information, support for online learning, information sharing among teachers, and efficient grading.

[1451] (Application example 1)

[1452] 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."

[1453] In conventional educational systems, functions such as managing student information, providing teaching materials, sharing lesson plans, and grading assignments are distributed, making it difficult to operate them centrally. As a result, teachers' work becomes complicated and they are unable to provide effective educational support. In addition, there are limited ways for students to instantly check their learning progress and grades, hindering learning efficiency. Furthermore, the inconvenient management of annotations and notes on digital teaching materials makes it difficult to deepen learning content.

[1454] 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.

[1455] In this invention, the server includes a school information management means for centrally managing student information and making it accessible to teachers, an online learning means for providing digital teaching materials so that students can study online, a shared document management means for allowing teachers to share teaching materials and lesson plans, an electronic grading means for automatically grading test questions and assignments, a mobile access means for checking students' learning progress and grades from their smartphones, a digital annotation means for adding annotations to digital teaching materials and viewing them, and an electronic notification means for automatically grading submitted assignments and notifying the results. This makes it possible to improve the efficiency of teachers' work and students' learning.

[1456] "School information management means" refers to a means for centrally managing information such as student grades, attendance, and history, and making it accessible to teachers.

[1457] "Online learning means" means means by which educational materials are provided in digital format and students can learn online.

[1458] "Shared document management means" refers to a means by which teachers can share and manage teaching materials and lesson plans.

[1459] "Electronic marking means" means a means for automatically marking test questions or assignments and providing the results.

[1460] "Mobile access means" refers to a means that allows students to check their learning progress and grades from their smartphones.

[1461] "Digital annotation means" refers to a means for annotating and viewing digital teaching materials.

[1462] "Electronic notification means" refers to a means for automatically grading assignment submissions and notifying the results.

[1463] This invention is a system that includes a unified management of student information, a means for students to study online, a means for teachers to share teaching materials and lesson plans, a means for automatically grading test questions and assignments, a means for checking learning progress and grades from a smartphone, a means for annotating and viewing digital teaching materials, and a means for automatically grading submitted assignments and notifying the results. Specific methods for realizing this system are described below.

[1464] Hardware and Software Configuration

[1465] This system is mainly composed of three main elements: a server, a terminal, and a user.

[1466] server

[1467] The server has a central database for unifying student information and stores various information (grades, attendance, history, etc.). The server runs a software framework (e.g., Flask) for managing the provision of digital learning materials, automatic grading of assignments, and notification of grades. SQLite is used as the database.

[1468] Centralized management of student information: Provides API endpoints to make student information more accessible to teachers and handles data requests and responses.

[1469] Providing digital learning materials: Stores learning materials uploaded by teachers and makes them available for students to download.

[1470] Shared Document Management: Manage, store, and provide shared access to documents shared among faculty members.

[1471] Electronic grading: Automatically grade exam questions and assignments and store the results.

[1472] Terminal

[1473] The device (smartphone or PC) provides an interface for users to access the server, and students download digital learning materials, annotate them, and submit assignments from the device.

[1474] Mobile access: Provide students with an interface to check their progress and grades using their smartphones.

[1475] Digital annotation: A function that allows you to add notes and annotations to digital teaching materials.

[1476] Electronic notifications: Has the function of notifying assignment grading results in real time.

[1477] Specific examples

[1478] Here are some specific scenarios where this system can be used:

[1479] 1. Student grade management: When a teacher sends a request to view a student's grades from their device to the server, the server retrieves the student's grades from the database and returns them to the teacher's device. The teacher can then check the grades on their smartphone.

[1480] 2. Online lessons: Teachers upload digital learning materials to a server, and students download them from their smartphones. Students annotate the downloaded materials and progress with their learning.

[1481] 3. Electronic grading: When teachers send exam answer sheets from their devices to the server, the server automatically grades them using the electronic grading system and stores the results in a database. Students are notified of the grade results via their smartphones.

[1482] Prompt Sentence Examples

[1483] The questions are automatically scored by inputting the following prompts into the generative AI model:

[1484] Teacher-created math assignment answers:

[1485] Q1: B

[1486] Q2: B

[1487] Q3: A

[1488] Please rate this.

[1489] In this way, a system is provided that can improve the efficiency of teachers' work and students' learning.

[1490] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1491] Step 1:

[1492] Requester: User (teacher)

[1493] Processing content: The teacher sends a request to the server from the terminal to view the student's grades.

[1494] Input: Student ID entered on the teacher's device.

[1495] Data processing: Generate an HTTP request including the student ID.

[1496] Output: A request containing the student ID is sent to the server.

[1497] Specific operations: The teacher enters the ID of the student whose grades they want to check into their smartphone or computer and presses the "Check Grades" button.

[1498] Step 2:

[1499] Requested by: Server

[1500] Processing content: The server retrieves the student's grades from the database.

[1501] Input: A request containing a student ID.

[1502] Data processing: Generate a database query to obtain the student's academic performance information.

[1503] Output: Academic information for the student.

[1504] Specific operation: The server issues a query to the database using the received student ID and extracts the student's grade information.

[1505] Step 3:

[1506] Requested by: Server

[1507] Processing content: The server returns the grade information it has acquired to the teacher's terminal.

[1508] Input: Academic information for the student in question.

[1509] Data processing: Generate an HTTP response containing performance information.

[1510] Output: A response containing grade information is sent to the teacher's terminal.

[1511] Specific operation: The server sends the grade information obtained from the database to the teacher's terminal as an HTTP response.

[1512] Step 4:

[1513] Requester: User (teacher)

[1514] Processing details: Teachers check students' grade information on their smartphones or computers.

[1515] Input: Achievement information received from the server.

[1516] Data processing: Convert received grade information into a display format.

[1517] Output: Student grades are displayed on the screen.

[1518] Specific actions: The teacher checks the grade information displayed on the device and takes the necessary action.

[1519] Step 5:

[1520] Requester: User (student)

[1521] What happens: Students log in to an online learning platform from their home devices and download the learning materials provided by their teachers.

[1522] Input: Login information, request for materials.

[1523] Data processing: Authenticating login information and processing requests for learning materials.

[1524] Output: Teaching material data.

[1525] Specific operation: Students log in to their devices, search for the teaching materials uploaded by the teacher, and press the download button.

[1526] Step 6:

[1527] Requested by: Server

[1528] Processing content: The server provides teaching material data in response to student requests.

[1529] Input: Student materials request.

[1530] Data processing: Search for teaching material data and include it in the HTTP response.

[1531] Output: A response containing the teaching material data is sent to the student's device.

[1532] Specific operation: The server retrieves digital learning materials from the database and provides them to students in a downloadable format.

[1533] Step 7:

[1534] Requested by: Server

[1535] Processing content: The server inputs the submitted assignment into a generative AI model and performs automatic grading.

[1536] Input: Submitted assignment response data.

[1537] Data processing: The answer data is fed into the generative AI model to obtain the scoring results.

[1538] Output: Scoring results.

[1539] Specific operation: The server inputs the assignments submitted by the students into the generative AI model and generates the grading results.

[1540] Step 8:

[1541] Requested by: Server

[1542] Processing details: The server saves the grading results in a database and notifies the teacher's terminal.

[1543] Input:Scoring results.

[1544] Data processing: The grading results are stored in a database and notifications are sent to teachers.

[1545] Output: Saved grading results, notifications.

[1546] Specific operation: The server saves the generated grading results in a database and sends a notification to the teacher's terminal saying "The grading results have been updated."

[1547] Step 9:

[1548] Requester: User (teacher)

[1549] Processing details: Teachers check the grading results on their smartphones or computers.

[1550] Input: Notification from the server.

[1551] Data processing: Retrieve the scoring results from the database and convert them into a display format.

[1552] Output: The results are displayed on the screen.

[1553] Specific operation: The teacher clicks on the notification on the device and checks the grading results.

[1554] In this way, the present invention provides a system that can manage student information, provide digital teaching materials, automatically grade assignments, manage grades, and check progress on a smartphone in an integrated manner.

[1555] 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.

[1556] This invention relates to a system that combines the centralized management of student information, provision of digital teaching materials, shared document management, and electronic grading functions with an emotion engine that recognizes user emotions. This system is composed of three main elements: a server, a terminal, and a user. The emotion engine recognizes user emotions and reflects them in the system, with the aim of further improving the quality of education. We will now explain in detail how each element works together and how the invention is specifically implemented.

[1557] A centralized student information management system

[1558] server

[1559] The server centrally manages student grades, attendance information, and records, making them accessible to teachers. This allows teachers to quickly obtain the information they need. Furthermore, the emotion engine stores students' emotional information on the server, enabling comprehensive information management.

[1560] For example, if a teacher wants to check the grades and recent emotional state of a specific student, a request is sent from the device. The server retrieves the student's grades and emotional state from the database and returns them to the teacher's device.

[1561] Online Learning Platform

[1562] server

[1563] The server provides digital learning materials and assignments for users (teachers and students) to access. Teachers upload learning materials, and students can view and study them online. The emotion engine recognizes students' emotional state in real time during online learning, improving the effectiveness of their learning.

[1564] For example, when a teacher uploads a new assignment, the server stores the data and students download it to study. The emotion engine monitors students' emotions as they work on the assignment and provides feedback according to their learning progress.

[1565] Terminal

[1566] The terminal provides an interface for users to access the server and upload or download learning materials. It also has an emotion engine that recognizes users' emotions in real time.

[1567] Example: When a student logs into an online learning platform from their home device and downloads materials provided by their teacher to study, the emotion engine recognizes the student's emotional state and displays advice to optimize learning efficiency.

[1568] Shared Document Management System

[1569] server

[1570] The server provides a system that allows teachers to share teaching materials and lesson plans, and stores and updates the shared documents. The emotion engine strengthens the collaborative system among teachers by monitoring the viewing status of the shared documents and the emotional state of the viewers.

[1571] Example: Teacher A uploads a lesson plan he created to the server, and when Teacher B views the document, the emotion engine recognizes Teacher B's reaction and provides feedback.

[1572] Electronic Scoring System

[1573] server

[1574] The server automatically grades submitted exam questions and assignments and stores the results in a database. In addition, an emotion engine monitors the student's emotional state when answering questions and takes this into account as a factor that may affect the grade.

[1575] Example: When a teacher uploads exam answers scanned on a device, the server processes the answers in an electronic scoring system, and the emotion engine analyzes the student's emotional state and notifies the teacher of the results.

[1576] Terminal

[1577] The device provides an interface for teachers to upload exam and assignment answers and view the automated marking results. It also has an emotion engine that monitors the teacher's reactions and emotional state.

[1578] Example: When a teacher uses a device at home to scan an answer sheet, send it to a server, and receive the results of automatic grading, the emotion engine recognizes the teacher's emotional state and makes suggestions to reduce stress.

[1579] Example

[1580] Example 1: Student performance management and emotion monitoring

[1581] 1. Send a request to view student grades from the teacher's device.

[1582] 2. The server retrieves the student's grades and emotional state from the database.

[1583] 3. The server sends the grade information and emotional state to the teacher's terminal, and the teacher checks the information.

[1584] Example 2: Online classes and emotional feedback

[1585] 1. The teacher uploads the teaching materials from the device to the server.

[1586] 2. The server stores the learning materials and makes them accessible to students.

[1587] 3. Students download the learning materials to their devices and proceed with their studies.

[1588] 4. The emotion engine monitors students' emotional state in real time while they are learning and provides appropriate feedback.

[1589] Example 3: Electronic scoring and sentiment analysis

[1590] 1. The teacher sends the exam answer sheet from the terminal to the server.

[1591] 2. The server uses an electronic scoring system to automatically score the tests.

[1592] 3. The emotion engine analyzes the student's emotional state when answering and reflects this in the scoring results.

[1593] 4. The server sends the scoring results and emotion analysis results to the teacher's terminal, where the teacher can check them.

[1594] The system of the present invention significantly reduces the workload of teachers and enables them to effectively utilize their expertise. The introduction of an emotion engine provides feedback based on the user's emotional state, further improving the quality and efficiency of education.

[1595] The processing flow will be explained below.

[1596] A centralized student information management system

[1597] Process flow: Viewing student grades and emotional information

[1598] Step 1:

[1599] A user (teacher) sends a request from a terminal to view the grades and emotional information of a specific student.

[1600] Step 2:

[1601] The terminal forwards the request to the server.

[1602] Step 3:

[1603] A server accesses a database containing student performance and emotional information.

[1604] Step 4:

[1605] The server retrieves the student's grade information and emotion information from the database.

[1606] Step 5:

[1607] The server transmits the acquired performance information and emotion information to the terminal.

[1608] Step 6:

[1609] The terminal displays the received information on the screen, and the user (teacher) checks it.

[1610] Online Learning Platform

[1611] Process flow: Uploading teaching materials and monitoring emotions

[1612] Step 1:

[1613] The user (teacher) selects the teaching material file and sends an upload request from the terminal.

[1614] Step 2:

[1615] The terminal uploads the selected educational material file to the server.

[1616] Step 3:

[1617] The server stores the received teaching material file in a data storage.

[1618] Step 4:

[1619] The server sends a notification to the device that the upload is complete.

[1620] Step 5:

[1621] A user (student) sends a request to access the online learning platform from a terminal.

[1622] Step 6:

[1623] The terminal accesses the server and sends a request to acquire a list of available learning materials.

[1624] Step 7:

[1625] The server retrieves a list of available learning materials from the database and sends it to the terminal.

[1626] Step 8:

[1627] The terminal displays a list of teaching materials on the screen, which the user (student) can view.

[1628] Step 9:

[1629] The emotion engine analyzes the user's (student's) facial expressions and voice in real time to recognize their emotional state.

[1630] Step 10:

[1631] The emotion engine sends feedback to the device based on the recognized emotional state to improve learning efficiency.

[1632] Shared Document Management System

[1633] Process flow: Sharing lesson plans and emotional feedback

[1634] Step 1:

[1635] The user (teacher) selects a lesson plan document and sends a sharing request from their device.

[1636] Step 2:

[1637] The device uploads the document to the server.

[1638] Step 3:

[1639] The server saves the document in a shared folder and updates the sharing settings.

[1640] Step 4:

[1641] The server sends a notification of completion of sharing to the terminal.

[1642] Step 5:

[1643] Another user (teacher) sends a request from their device to find a shared lesson plan document.

[1644] Step 6:

[1645] The terminal accesses the shared folder and sends a request to the server to search for the document.

[1646] Step 7:

[1647] The server retrieves the document from the shared folder and sends it to the terminal.

[1648] Step 8:

[1649] The terminal displays the received document on the screen, and the user (teacher) views it.

[1650] Step 9:

[1651] The emotion engine analyzes the user's (teacher's) facial expressions and voice in real time and recognizes their reactions to shared documents.

[1652] Step 10:

[1653] The emotion engine sends feedback and improvement suggestions to the device based on the recognized emotional state.

[1654] Electronic Scoring System

[1655] Process flow: Automatic marking of assignments and sentiment analysis

[1656] Step 1:

[1657] The user (teacher) scans the students' answer sheets and sends a request from the terminal to upload them to the electronic marking system.

[1658] Step 2:

[1659] The device uploads the scanned image of the answer sheet to the server.

[1660] Step 3:

[1661] The server converts the received image data into text data using optical character recognition (OCR) technology.

[1662] Step 4:

[1663] The server applies an automatic scoring algorithm based on the text data.

[1664] Step 5:

[1665] The emotion engine analyzes the facial expressions and voice of students during their responses and generates emotional information.

[1666] Step 6:

[1667] The server stores the scoring results and emotion information in a database.

[1668] Step 7:

[1669] The server sends a notification including the grading results and emotion information to the teacher's terminal.

[1670] Step 8:

[1671] The terminal displays the received scoring results and emotion information on the screen, and the user (teacher) checks them.

[1672] Step 9:

[1673] The emotion engine analyzes teachers' reactions in real time and provides feedback and stress-reducing suggestions as appropriate.

[1674] Example 2

[1675] 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."

[1676] While traditional education systems require centralized management of student information and efficient online learning, they lack functionality such as emotion recognition and real-time feedback, making it difficult to maximize student learning outcomes. Furthermore, there are limited means to streamline teacher work, and strengthening cooperation among teachers and improving the accuracy of automated grading of exams and assignments are also issues.

[1677] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1678] In this invention, the server includes an information management means, an online learning means, a sharing management means, a scoring means, and an emotion recognition means. This makes it possible to:

[1679] 1. Students' grades, attendance, history and emotional information can be managed in an integrated manner.

[1680] 2. Efficient online learning can be achieved through the uploading, viewing, and editing of teaching materials, as well as real-time monitoring of students' emotional states.

[1681] 3. Teachers can strengthen collaboration and share teaching materials and lesson plans more efficiently.

[1682] 4. Exams and assignments can be graded automatically, and emotion recognition can be used to reflect emotional information in the grading results.

[1683] The "information management means" is a system including a database that comprehensively manages student grades, attendance information, history, and emotional information.

[1684] "Online learning means" means a system that includes functions for providing educational materials digitally and enabling students to learn online, and allows for the uploading, viewing, and modification of educational materials, as well as real-time monitoring of students' emotional state.

[1685] A "shared management tool" is a system that allows teachers to share teaching materials and lesson plans with each other.

[1686] A "grading tool" is a system that automatically grades exams and assignments.

[1687] The "emotion recognition means" is a system that recognizes the user's emotions in real time and reflects them in education.

[1688] This invention relates to a system that combines the functions of unified student information management, digital teaching materials provision, shared document management, and electronic grading with an emotion recognition engine that recognizes user emotions in real time. This system includes three main elements: a server, a terminal, and a user, and these elements work in conjunction with each other.

[1689] Hardware and software used

[1690] The system mainly uses the following hardware and software:

[1691] Server: Database and emotion recognition engine (e.g., SQL database, emotion recognition algorithm implemented in Python)

[1692] Device: The interface through which the user accesses the device (e.g., PC, tablet, dedicated application)

[1693] Users: Teachers and students

[1694] A centralized student information management system

[1695] server

[1696] The server maintains a database that comprehensively manages student grades, attendance, history, and emotional information. Upon request from a teacher, it retrieves the relevant student data and returns it to the teacher's device.

[1697] Example: When a teacher wants to check the grade information and emotional state of a particular student from his / her terminal, the server retrieves the information from the database and sends it to the teacher's terminal.

[1698] Online Learning Platform

[1699] server

[1700] The server digitally stores teaching materials uploaded by teachers and makes them available for students to access online. An emotion recognition engine also recognizes students' emotional state while they are studying and provides appropriate feedback.

[1701] Example: When a teacher uploads new learning materials, the server stores them and makes them available for students to view. An emotion recognition engine monitors students' emotional state while they are learning and generates feedback according to their learning progress.

[1702] Terminal

[1703] The device provides an interface for students to access online learning platforms, download learning materials, and study. It also includes an emotion recognition engine that can recognize users' emotions in real time.

[1704] Example: When a student is downloading learning materials from their home device and studying, an emotion recognition engine analyzes the student's emotional state and displays advice on how to relax if stress levels are rising.

[1705] Shared Document Management System

[1706] server

[1707] The server allows teachers to upload, save, and update shared documents. The emotion recognition engine monitors the viewing status of shared documents and the emotional state of the viewer, and provides feedback.

[1708] Example: When Teacher A uploads a shared document to the server and Teacher B views it, an emotion recognition engine analyzes Teacher B's reaction and provides Teacher A with feedback based on the reaction.

[1709] Electronic Scoring System

[1710] server

[1711] The server automatically grades test answers and assignments, storing the results in a database. An emotion recognition engine also analyzes the emotional state of students when they answer questions and reflects this in the grades.

[1712] Example: When a teacher scans an answer sheet and sends it to a server, the electronic scoring system automatically scores it and sends the results and sentiment analysis results to the teacher's device.

[1713] Terminal

[1714] The device provides an interface for teachers to upload exam and assignment answers and receive automated grading results. It also includes an emotion recognition engine that monitors teachers' reactions and emotional state.

[1715] Example: When a teacher scans an answer sheet using a device at home and sends it to a server, and receives the grading results and emotion analysis results, the emotion recognition engine monitors the teacher's stress level and suggests relaxation methods if necessary.

[1716] Example

[1717] Prompt Sentence Examples

[1718] "Please detail the procedures for faculty to monitor students' academic performance and emotional state."

[1719] "Please explain specific ways in which you can monitor students' emotional states in online learning platforms."

[1720] "Please show us specifically how you will perform sentiment analysis in your electronic scoring system and reflect it in the results."

[1721] This system will reduce the workload of teachers and maximize the learning effect of students. The introduction of an emotion recognition engine will enable real-time feedback, which is expected to further improve the quality of education.

[1722] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1723] A centralized student information management system

[1724] Step 1:

[1725] A teacher sends a request to view a student's grades on a terminal. The input is the teacher's identification information for the student (student ID, name, etc.). The terminal generates this request and sends it to the server. The output is the request data sent to the server.

[1726] Step 2:

[1727] The server receives the request and retrieves the student's grades and emotional state from the database. The input is the request data from the teacher. The server executes the database query to retrieve the grade information and emotional state information. The output is the retrieved data of the student's grades and emotional state.

[1728] Step 3:

[1729] The server returns the acquired information to the teacher's terminal. The input is the student's grades and emotional state data acquired by the server. The server structures this data and sends it to the teacher's terminal. The output is the grade information and emotional information acquired by the teacher.

[1730] Step 4:

[1731] The teacher checks the information on the terminal. The input is the grade information and emotional state data sent from the server. The teacher displays and checks the received information through the terminal interface. The output is information that the teacher uses to make decisions.

[1732] Online Learning Platform

[1733] Step 1:

[1734] The teacher uploads the teaching material from the terminal. The input is the digital teaching material file and related metadata (title, description, etc.). The terminal collects this data and sends it to the server. The output is the uploaded data to the server.

[1735] Step 2:

[1736] The server stores the teaching materials and sets them up so that students can access them. The input is the teaching material data and metadata sent by the teacher. The server stores this in a database and sets permissions so that students can access it. The output is the teaching materials stored and accessible.

[1737] Step 3:

[1738] Students download learning materials to their devices and progress with their studies. The input is the student sending a download request and the learning material data stored on the server. The device generates a request and retrieves the learning material from the server. The output is the learning material data downloaded to the student's device.

[1739] Step 4:

[1740] The emotion engine monitors students' emotional states in real time and provides feedback. The input is data such as the student's facial expressions, voice volume, and tone of voice obtained from the device's camera and microphone. The emotion engine analyzes this data and estimates the student's emotional state. The output is advice and recommendations presented to the student as real-time feedback.

[1741] Shared Document Management System

[1742] Step 1:

[1743] The teacher uploads a shared document from a terminal. The input is the shared document file and related metadata. The terminal sends these to the server. The output is the uploaded data to the server.

[1744] Step 2:

[1745] The server saves the document and sets it up so that other teachers can access it. The input is the shared document data sent by the teacher. The server saves it in a database and sets permissions so that other teachers can access it. The output is the saved document and access right setting data.

[1746] Step 3:

[1747] Another teacher views the document on their device. The input is a view request and the document data stored on the server. The device generates a request and retrieves the document from the server. The output is the document data displayed on the teacher's device.

[1748] Step 4:

[1749] The emotion engine monitors the viewer's emotional state and provides feedback. The input is data such as the teacher's facial expression, voice volume, and tone obtained from the device's camera and microphone. The emotion engine analyzes this data and estimates the teacher's emotional state. The output is advice and recommendations that are presented to the teacher as feedback during viewing.

[1750] Electronic Scoring System

[1751] Step 1:

[1752] The teacher sends the exam answer sheet from the terminal. The input is a digital file of the scanned exam answer sheet. The terminal sends this to the server. The output is the exam answer data sent to the server.

[1753] Step 2:

[1754] The server uses an electronic marking system to perform marking. The input is test answer data. The server calls the electronic marking system and automatically performs marking. The output is marking result data.

[1755] Step 3:

[1756] The emotion engine analyzes the emotional state of the student when answering. The input is facial expression and voice data recorded when answering. The emotion engine analyzes this and estimates the emotional state. The output is emotion analysis result data.

[1757] Step 4:

[1758] The server sends the scoring results and sentiment analysis results to the teacher's terminal. The input is the scoring result data and sentiment analysis result data. The server structures these and sends them to the teacher's terminal. The output is the scoring results and sentiment analysis results received by the teacher.

[1759] Step 5:

[1760] The teacher checks the grading results and sentiment analysis results on the terminal. The input is the grading results and sentiment analysis results received from the server. The teacher displays and checks this information on the terminal. The output is information that the teacher can use to make decisions.

[1761] (Application example 2)

[1762] 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."

[1763] Existing educational systems manage students' grades and learning progress without considering their emotional state, making it difficult to provide optimal instruction and feedback to individual students. Furthermore, general online shopping sites lack a means to provide a personalized shopping experience that reflects users' emotional state. There is a need to address these issues, improve the quality and efficiency of education, and enhance the user experience of online shopping.

[1764] 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.

[1765] In this invention, the server includes an information management means, a learning means, a shared document management means, a scoring means, and an emotion-aware shopping assistant means, thereby enabling a comprehensive education and shopping experience that takes into account the user's emotions.

[1766] "Information management means" refers to the part of the system that centrally manages students' grades, attendance information, and records, and allows teachers to access this information.

[1767] "Learning tools" are the system's capabilities to provide learning materials digitally and enable students to learn online.

[1768] The "shared document management tool" is part of a system that provides the ability for teachers to share teaching materials and lesson plans and edit them collaboratively.

[1769] A "grading tool" is a system that has the function of automatically grading test questions and assignments and providing the results to teachers.

[1770] The "emotion recognition shopping assistant means" is a system function that analyzes the user's facial expressions and voice to recognize their emotions, and then makes product recommendations and promotions based on this.

[1771] The system for implementing this invention mainly comprises a server, a terminal, and a user. Each of these components will be described in detail below.

[1772] Information management means

[1773] The information management system is provided by a server and is a system that centrally manages student grades, attendance information, and records. Teachers can access this information using their terminals and quickly obtain the data they need. The data is stored and managed in a database on the server.

[1774] Learning tools

[1775] Learning tools are provided by a server. The server provides learning materials and assignments in digital format, and students can study online using their devices. Teachers upload learning materials to the server, and students download them to study. The system is also equipped with an emotion engine that provides feedback based on students' emotional state.

[1776] Shared document management tools

[1777] The shared document management system is provided by a server and allows teachers to share teaching materials and lesson plans. Teachers can upload documents from their devices, and other teachers can view and edit them collaboratively. The emotion engine also monitors the emotional state of viewers and provides effective feedback.

[1778] Scoring method

[1779] The grading method is a function in which the server automatically grades submitted exam questions and assignments. When teachers scan and upload answer sheets from their devices, the server processes them with an electronic grading system. In addition, an emotion engine monitors the students' emotional state when answering, and this is also reflected in the grading results.

[1780] Emotion-aware shopping assistant

[1781] The emotion-aware shopping assistant uses the user's terminal or smart device (e.g., smartphone or tablet) to analyze the user's facial expressions and voice to recognize emotions. Based on the recognized emotions, the server provides appropriate product recommendations and promotions. This allows the user to have an individualized shopping experience.

[1782] Hardware and software used

[1783] Hardware used: smartphone, tablet, PC, camera

[1784] Software used: Python, Flask, OpenCV, TextBlob

[1785] Processing flow

[1786] The specific process flow is implemented based on the following steps:

[1787] 1. Obtain the user's camera video and audio input.

[1788] 2. The captured video is analyzed using OpenCV and the face_recognition library to analyze the user's facial expressions and recognize their emotional state.

[1789] 3. The voice input (or text) is analyzed with the TextBlob library to determine the user's sentiment as text.

[1790] 4. Based on the results of sentiment and text analysis, the server recommends appropriate products and promotions to the user.

[1791] Specific examples

[1792] 1. When a user opens an online shopping app on their smartphone, if the camera recognizes the user's face and determines that they are "Happy," the app will recommend "new fashion items that perfectly match their current mood."

[1793] 2. When a user asks "What are your recent recommendations?" using voice input, TextBlob analyzes the voice text, and if it is determined to be "positive," it suggests products with many positive reviews.

[1794] Prompt Sentence Examples

[1795] 1. "Analyze this user's facial expressions and voice to determine their emotional state."

[1796] 2. "What promotion should I offer if the user has a smiling face?"

[1797] This provides a holistic education and purchasing experience that takes into account the user's emotions.

[1798] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1799] Step 1:

[1800] The user launches the application on their device (smartphone or tablet).

[1801] Input: Launching an app on a smartphone or tablet.

[1802] Output: The app starts and goes to the initial screen.

[1803] Step 2:

[1804] The device's camera captures the user's face and obtains video data in real time.

[1805] Input: Camera image (user's face).

[1806] Output: Captured video frames.

[1807] Step 3:

[1808] The video data acquired by the device is analyzed using OpenCV and the face_recognition library to recognize the user's facial expressions.

[1809] Input: Captured video frames.

[1810] Output: Recognized facial expression data (e.g. smile, sadness).

[1811] Step 4:

[1812] The user speaks and the device captures the speech and converts it into text.

[1813] Input: Audio data.

[1814] Output: Audio converted to text data.

[1815] Step 5:

[1816] The device uses the TextBlob library to analyze the sentiment of the text converted from the audio data.

[1817] Input: Text data.

[1818] Output: Sentiment analysis result (e.g. positive, negative).

[1819] Step 6:

[1820] The device sends facial expression data and text analysis results to the server.

[1821] Input: facial expression data, emotion analysis results.

[1822] Output: Sending data to the server.

[1823] Step 7:

[1824] The server determines product recommendations and promotions based on the received data according to the user's emotional state.

[1825] Input: facial expression data, emotion analysis results.

[1826] Output: Recommendation data, promotion data.

[1827] Step 8:

[1828] The server transmits recommendation data and promotion data to the terminal.

[1829] Input: Recommendation data, Promotion data.

[1830] Output: Sending data to a terminal.

[1831] Step 9:

[1832] The device displays the received recommendations and promotions to the user.

[1833] Input: Recommendation data, Promotion data.

[1834] Output: Recommendations and promotion information displayed in a user interface.

[1835] 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.

[1836] 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.

[1837] 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.

[1838] [Fourth embodiment]

[1839] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1840] 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.

[1841] 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).

[1842] 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.

[1843] 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.

[1844] 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).

[1845] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1846] 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.

[1847] 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.

[1848] 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.

[1849] 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.

[1850] 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.

[1851] 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."

[1852] This invention relates to a system that includes the centralized management of student information, provision of digital teaching materials, shared document management, and electronic grading functions. This system consists of three main elements: a server, a terminal, and a user. We will explain in detail how each element works together and how the invention is specifically implemented.

[1853] A centralized student information management system

[1854] server

[1855] The server centrally manages student grades, attendance information, and records, making them accessible to teachers, allowing them to quickly obtain the information they need.

[1856] For example, if a teacher wants to check the grades of a specific student, a request is sent from the terminal. The server retrieves the grades of the student from the database and returns them to the teacher's terminal.

[1857] Online Learning Platform

[1858] server

[1859] The server provides digital learning materials and assignments, making them accessible to users (teachers and students). Teachers upload learning materials, and students can view and study them online.

[1860] Example: When a teacher uploads a new assignment, the server stores the data and students download it to study.

[1861] Terminal

[1862] The terminal provides an interface for the user to access the server and upload or download educational materials.

[1863] Example: A student logs into an online learning platform from their home device, downloads materials provided by their teacher, and studies.

[1864] Shared Document Management System

[1865] server

[1866] The server provides a system that allows teachers to share teaching materials and lesson plans with each other, and stores and updates shared documents, making it easier for teachers to share teaching materials with each other.

[1867] Example: Teacher A uploads a lesson plan he created to the server, and Teacher B can also view and download the plan.

[1868] Electronic Scoring System

[1869] server

[1870] The server automatically grades submitted exam questions and assignments and stores the results in a database, significantly reducing the grading workload for teachers.

[1871] Example: When a teacher uploads exam answers scanned on a device, the server processes the answers in an electronic scoring system and returns the scoring results to the teacher's device.

[1872] Terminal

[1873] The device provides an interface for teachers to upload exam and assignment answers and view the automatically graded results.

[1874] Example: A teacher uses a device at home to scan answer sheets, send them to a server, and receive the results of automatic grading.

[1875] Example

[1876] Example 1: Student Grade Management

[1877] 1. Send a request to view student grades from the teacher's device.

[1878] 2. The server retrieves the student's grades from the database.

[1879] 3. The server sends the grade information to the teacher's terminal, where the teacher can view the information.

[1880] Example 2: Online classes

[1881] 1. The teacher uploads the teaching materials from the device to the server.

[1882] 2. The server stores the learning materials and makes them accessible to students.

[1883] 3. Students download the learning materials to their devices and proceed with their studies.

[1884] Example 3: Electronic marking

[1885] 1. The teacher sends the exam answer sheet from the terminal to the server.

[1886] 2. The server uses an electronic scoring system to automatically score the tests.

[1887] 3. The server stores the grading results in a database and sends them to the teacher's device.

[1888] The system of the present invention significantly reduces the workload of teachers and enables them to effectively utilize the expertise of each teacher, thereby enabling them to provide higher quality education.

[1889] The processing flow will be explained below.

[1890] A centralized student information management system

[1891] Process flow: View student grades

[1892] Step 1:

[1893] A user (teacher) sends a request from a terminal to view the grades of a specific student.

[1894] Step 2:

[1895] The terminal forwards the request to the server.

[1896] Step 3:

[1897] The server accesses the database and obtains the grade information of the student.

[1898] Step 4:

[1899] The server transmits the acquired score information to the terminal.

[1900] Step 5:

[1901] The terminal displays the received grade information on the screen, and the user (teacher) checks it.

[1902] Online Learning Platform

[1903] Process flow: Uploading and viewing teaching materials

[1904] Step 1:

[1905] The user (teacher) selects the teaching material file and sends an upload request from the terminal.

[1906] Step 2:

[1907] The terminal uploads the selected educational material file to the server.

[1908] Step 3:

[1909] The server stores the received teaching material file in a data storage.

[1910] Step 4:

[1911] The server sends a notification to the device that the upload is complete.

[1912] Step 5:

[1913] A user (student) sends a request to access the online learning platform from a terminal.

[1914] Step 6:

[1915] The terminal accesses the server and sends a request to acquire a list of available learning materials.

[1916] Step 7:

[1917] The server retrieves a list of available learning materials from the database and sends it to the terminal.

[1918] Step 8:

[1919] The terminal displays a list of teaching materials on the screen, which the user (student) can view.

[1920] Shared Document Management System

[1921] Process flow: Sharing lesson plans

[1922] Step 1:

[1923] The user (teacher) selects a lesson plan document and sends a sharing request from their device.

[1924] Step 2:

[1925] The device uploads the document to the server.

[1926] Step 3:

[1927] The server saves the document in a shared folder and updates the sharing settings.

[1928] Step 4:

[1929] The server sends a notification of completion of sharing to the terminal.

[1930] Step 5:

[1931] Another user (teacher) sends a request from their device to find a shared lesson plan document.

[1932] Step 6:

[1933] The terminal accesses the shared folder and sends a request to the server to search for the document.

[1934] Step 7:

[1935] The server retrieves the document from the shared folder and sends it to the terminal.

[1936] Step 8:

[1937] The terminal displays the received document on the screen, and the user (teacher) views it.

[1938] Electronic Scoring System

[1939] Process flow: Automatic grading of assignments

[1940] Step 1:

[1941] The user (teacher) scans the students' answer sheets and sends a request from the terminal to upload them to the electronic marking system.

[1942] Step 2:

[1943] The device uploads the scanned image of the answer sheet to the server.

[1944] Step 3:

[1945] The server converts the received image data into text data using optical character recognition (OCR) technology.

[1946] Step 4:

[1947] The server applies an automatic scoring algorithm based on the text data.

[1948] Step 5:

[1949] The server stores the results of the scoring in a database.

[1950] Step 6:

[1951] The server transmits the automatic scoring results to the terminal.

[1952] Step 7:

[1953] The terminal displays the received grading results on the screen, and the user (teacher) checks them.

[1954] Example 1

[1955] 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."

[1956] In today's educational settings, a wide range of functions are required, such as the centralized management of student information, the digital provision of teaching materials, information sharing among teachers, and automatic grading of exams and assignments. In conventional systems, these functions are separate, which not only makes it time-consuming to consolidate and manage information, but also increases the workload of teachers. For this reason, a system that can integrate and manage these functions centrally is needed.

[1957] 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.

[1958] In this invention, the server includes an information management means for centrally managing student information and making it accessible to teachers, a learning means for providing digital learning materials so that students can study online, a document management means for allowing teachers to share learning materials and lesson plans, a grading means for automatically grading test questions and assignments, a grade management means for viewing and updating student grade information, an attendance management means for managing and analyzing student attendance information, a learning material uploading means for teachers to upload learning materials so that students can study online, an assignment submission means for students to submit assignments online, a document editing means for teachers to edit and save shared documents, and an exam answer uploading means for uploading and analyzing exam answers. This reduces the workload of teachers and improves the learning environment for students.

[1959] "Student information" refers to information related to individuals, such as the name, student ID number, grades, attendance information, and history of students belonging to a school.

[1960] "Information management" is a means of centrally managing student information and providing teachers with the ability to access, view, and edit it as needed.

[1961] "Learning medium" refers to the means by which learning materials are provided in digital format and students learn online.

[1962] "Document management" is a means by which teachers can share teaching materials and lesson plans, and edit and save them as needed.

[1963] A "grading tool" is a tool that automatically grades submitted test questions and assignments and manages the results.

[1964] A "grade management tool" is a means by which students' grade information can be viewed and updated, and is a system that allows teachers to quickly obtain the information they need.

[1965] The "attendance management means" is a means for managing and analyzing daily attendance information and understanding patterns of absence and lateness.

[1966] The "teaching material uploading means" is a means for uploading teaching materials created by teachers to a server so that students can download them and study.

[1967] "Assignment submission means" refers to the means by which students submit assignments online.

[1968] "Document editing means" refers to a means for teachers to edit and save shared documents.

[1969] The "test answer uploading means" is a means by which a teacher uploads test answers to a server, analyzes them, and grades them.

[1970] The present invention is a system that integrates the functions of unified management of student information, provision of digital teaching materials, management of shared documents, and electronic grading. A specific embodiment of this system will be described in detail below.

[1971] A centralized student information management system

[1972] The server centrally manages student information, including grades, attendance, and history, in a MySQL database. Teachers using terminals can access the server via a web browser to register, view, and update student information.

[1973] Specific examples

[1974] When a teacher enters the information of a new student into the terminal and presses the submit button, the server stores the information in a MySQL database. When a teacher enters a student ID number to view the grade information of a specific student, the server retrieves the information from the database and displays it on the teacher's terminal.

[1975] Online Learning Platform

[1976] The server provides teaching materials and assignments in digital format and allows users (teachers and students) to access them. Web applications built using web frameworks (e.g., Django or Rails) are used. Users using terminals can perform operations such as uploading and downloading teaching materials and submitting assignments.

[1977] Specific examples

[1978] When a teacher uploads new learning materials to the server, the materials are stored in a directory within the web application. Students can log in, download the materials, and proceed with their studies. Students who have completed their assignments can upload them from their devices and store them on the server.

[1979] Shared Document Management System

[1980] The server provides a document management system that allows teachers to share teaching materials and lesson plans. It connects with cloud services such as Google Docs and Microsoft Office 365 to manage access and editing of shared documents. Teachers using devices can access documents and edit and save them as needed.

[1981] Specific examples

[1982] When Teacher A uploads a lesson plan, other teachers can view and download it. For example, if you are using Google Docs, Teacher B can co-edit the document.

[1983] Electronic Scoring System

[1984] The server uses Python's OpenCV and Scikit-learn libraries to automatically grade exam questions and assignments. Teachers using terminals can upload scanned exam answers to the server and check the graded results online.

[1985] Specific examples

[1986] When a teacher scans and sends the test answers from their device to the server, the server analyzes the answers using OpenCV, automatically scores them using Scikit-learn, and returns the results to the teacher's device.

[1987] Prompt Sentence Examples

[1988] 1. "Please give an overview of your student information management system."

[1989] 2. "Please briefly explain the features of your online learning platform."

[1990] 3. "Please explain the technical details of the electronic marking system."

[1991] This reduces the workload of teachers and improves the learning environment for students. The system also provides users with intuitive operation through its interface, improving the quality of education.

[1992] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1993] A centralized student information management system

[1994] Processing Steps

[1995] Step 1: Register student information

[1996] Terminal: The teacher enters student information (name, student ID number, grades, etc.) into the input form and presses the send button.

[1997] Input: Student information (name, student ID number, grades)

[1998] Server: The server receives the input information and saves it in the database. Specifically, it executes an INSERT query on the MySQL database and stores the information in storage.

[1999] Output: Save complete response

[2000] Specific operation: A teacher enters new student information into the student registration form on the terminal, which is then sent to the server. The server saves the information in the database and returns a "Saving completed" message to the teacher's terminal.

[2001] Step 2: View Student Information

[2002] Terminal: The teacher enters the student's student ID number into the search form and presses the search button.

[2003] Input: Student ID number

[2004] Server: The server uses a SELECT query to retrieve the student's information from the database based on the received student ID number.

[2005] Output: Student information

[2006] Specific operation: When a teacher enters a student ID number and presses the search button, the server retrieves the relevant student's information from the database and displays it on the teacher's terminal.

[2007] Online Learning Platform

[2008] Processing Steps

[2009] Step 1: Upload your materials

[2010] Terminal: The teacher selects the teaching material file and presses the upload button.

[2011] Input: Teaching material file

[2012] Server: The server receives the uploaded file and saves it in the specified directory of the web application.

[2013] Output: Upload complete response

[2014] Specific operation: The teacher selects a teaching material file and uploads it to the server. The server saves the file in a specific directory and returns an "upload complete" message to the teacher.

[2015] Step 2: Download the materials

[2016] Device: Students log in to the web application and select the materials they want to download from the list of materials.

[2017] Input: Download request (teaching material ID)

[2018] Server: The server acquires the selected teaching material file and sends it to the student's terminal.

[2019] Output: Teaching material file

[2020] Specific operation: When a student selects a teaching material and presses the download button, the server sends the teaching material file to the student's device and the download begins.

[2021] Shared Document Management System

[2022] Processing Steps

[2023] Step 1: Share the document

[2024] Terminal: The teacher selects the shared document and uploads it to the specified folder.

[2025] Input: Shared Documents

[2026] Server: The server receives the uploaded shared documents and stores them in a specified directory.

[2027] Output: Sharing complete response

[2028] Specific operation: When a teacher selects a shared document and presses the upload button, the server saves the document in the specified directory and returns a message saying "Sharing completed."

[2029] Step 2: Edit the document

[2030] Device: The teacher accesses the shared document and makes any necessary edits.

[2031] Input:Edit

[2032] Server: The server receives the edits and updates the document, optionally providing version control.

[2033] Output: Update complete response

[2034] Specific behavior: When a teacher accesses a shared document, makes edits, and saves the content, the server updates the document and returns a message that the update is complete.

[2035] Electronic Scoring System

[2036] Processing Steps

[2037] Step 1: Upload your exam answers

[2038] Terminal: The teacher selects the scanned test answer sheet and presses the upload button.

[2039] Input: Scanned image of the test answer sheet

[2040] Server: The server receives the uploaded scanned images and stores them in a specified directory.

[2041] Output: Upload complete response

[2042] Specific operation: The teacher scans the exam answers and uploads the image to the server. The server saves the image and returns a message saying "upload completed."

[2043] Step 2: Automated scoring

[2044] Server: The server analyzes the test answer images using the OpenCV library and automatically scores the answers using Scikit-learn.

[2045] Input: Scanned image of the test answer sheet

[2046] Output:Scoring results

[2047] What it does: The server analyzes the scanned image, automatically scores it using a machine learning model, and stores the results in a database.

[2048] Step 3: Check your results

[2049] Terminal: The teacher accesses the server to check the grading results.

[2050] Input: Grading result inquiry request

[2051] Server: The server retrieves the grading results from the database and sends them to the teacher's terminal.

[2052] Output:Scoring results

[2053] Specific operation: The teacher checks the grading results on their device, and the information is retrieved from the server and displayed on the teacher's device.

[2054] Through these steps, the system enables management of student information, support for online learning, information sharing among teachers, and efficient grading.

[2055] (Application example 1)

[2056] 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."

[2057] In conventional educational systems, functions such as managing student information, providing teaching materials, sharing lesson plans, and grading assignments are distributed, making it difficult to operate them centrally. As a result, teachers' work becomes complicated and they are unable to provide effective educational support. In addition, there are limited ways for students to instantly check their learning progress and grades, hindering learning efficiency. Furthermore, the inconvenient management of annotations and notes on digital teaching materials makes it difficult to deepen learning content.

[2058] 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.

[2059] In this invention, the server includes a school information management means for centrally managing student information and making it accessible to teachers, an online learning means for providing digital teaching materials so that students can study online, a shared document management means for allowing teachers to share teaching materials and lesson plans, an electronic grading means for automatically grading test questions and assignments, a mobile access means for checking students' learning progress and grades from their smartphones, a digital annotation means for adding annotations to digital teaching materials and viewing them, and an electronic notification means for automatically grading submitted assignments and notifying the results. This makes it possible to improve the efficiency of teachers' work and students' learning.

[2060] "School information management means" refers to a means for centrally managing information such as student grades, attendance, and history, and making it accessible to teachers.

[2061] "Online learning means" means means by which educational materials are provided in digital format and students can learn online.

[2062] "Shared document management means" refers to a means by which teachers can share and manage teaching materials and lesson plans.

[2063] "Electronic marking means" means a means for automatically marking test questions or assignments and providing the results.

[2064] "Mobile access means" refers to a means that allows students to check their learning progress and grades from their smartphones.

[2065] "Digital annotation means" refers to a means for annotating and viewing digital teaching materials.

[2066] "Electronic notification means" refers to a means for automatically grading assignment submissions and notifying the results.

[2067] This invention is a system that includes a unified management of student information, a means for students to study online, a means for teachers to share teaching materials and lesson plans, a means for automatically grading test questions and assignments, a means for checking learning progress and grades from a smartphone, a means for annotating and viewing digital teaching materials, and a means for automatically grading submitted assignments and notifying the results. Specific methods for realizing this system are described below.

[2068] Hardware and Software Configuration

[2069] This system is mainly composed of three main elements: a server, a terminal, and a user.

[2070] server

[2071] The server has a central database for unifying student information and stores various information (grades, attendance, history, etc.). The server runs a software framework (e.g., Flask) for managing the provision of digital learning materials, automatic grading of assignments, and notification of grades. SQLite is used as the database.

[2072] Centralized management of student information: Provides API endpoints to make student information more accessible to teachers and handles data requests and responses.

[2073] Providing digital learning materials: Stores learning materials uploaded by teachers and makes them available for students to download.

[2074] Shared Document Management: Manage, store, and provide shared access to documents shared among faculty members.

[2075] Electronic grading: Automatically grade exam questions and assignments and store the results.

[2076] Terminal

[2077] The device (smartphone or PC) provides an interface for users to access the server, and students download digital learning materials, annotate them, and submit assignments from the device.

[2078] Mobile access: Provide students with an interface to check their progress and grades using their smartphones.

[2079] Digital annotation: A function that allows you to add notes and annotations to digital teaching materials.

[2080] Electronic notifications: Has the function of notifying assignment grading results in real time.

[2081] Specific examples

[2082] Here are some specific scenarios where this system can be used:

[2083] 1. Student grade management: When a teacher sends a request to view a student's grades from their device to the server, the server retrieves the student's grades from the database and returns them to the teacher's device. The teacher can then check the grades on their smartphone.

[2084] 2. Online lessons: Teachers upload digital learning materials to a server, and students download them from their smartphones. Students annotate the downloaded materials and progress with their learning.

[2085] 3. Electronic grading: When teachers send exam answer sheets from their devices to the server, the server automatically grades them using the electronic grading system and stores the results in a database. Students are notified of the grade results via their smartphones.

[2086] Prompt Sentence Examples

[2087] The questions are automatically scored by inputting the following prompts into the generative AI model:

[2088] Teacher-created math assignment answers:

[2089] Q1: B

[2090] Q2: B

[2091] Q3: A

[2092] Please rate this.

[2093] In this way, a system is provided that can improve the efficiency of teachers' work and students' learning.

[2094] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2095] Step 1:

[2096] Requester: User (teacher)

[2097] Processing content: The teacher sends a request to the server from the terminal to view the student's grades.

[2098] Input: Student ID entered on the teacher's device.

[2099] Data processing: Generate an HTTP request including the student ID.

[2100] Output: A request containing the student ID is sent to the server.

[2101] Specific operations: The teacher enters the ID of the student whose grades they want to check into their smartphone or computer and presses the "Check Grades" button.

[2102] Step 2:

[2103] Requested by: Server

[2104] Processing content: The server retrieves the student's grades from the database.

[2105] Input: A request containing a student ID.

[2106] Data processing: Generate a database query to obtain the student's academic performance information.

[2107] Output: Academic information for the student.

[2108] Specific operation: The server issues a query to the database using the received student ID and extracts the student's grade information.

[2109] Step 3:

[2110] Requested by: Server

[2111] Processing content: The server returns the grade information it has acquired to the teacher's terminal.

[2112] Input: Academic information for the student in question.

[2113] Data processing: Generate an HTTP response containing performance information.

[2114] Output: A response containing grade information is sent to the teacher's terminal.

[2115] Specific operation: The server sends the grade information obtained from the database to the teacher's terminal as an HTTP response.

[2116] Step 4:

[2117] Requester: User (teacher)

[2118] Processing details: Teachers check students' grade information on their smartphones or computers.

[2119] Input: Achievement information received from the server.

[2120] Data processing: Convert received grade information into a display format.

[2121] Output: Student grades are displayed on the screen.

[2122] Specific actions: The teacher checks the grade information displayed on the device and takes the necessary action.

[2123] Step 5:

[2124] Requester: User (student)

[2125] What happens: Students log in to an online learning platform from their home devices and download the learning materials provided by their teachers.

[2126] Input: Login information, request for materials.

[2127] Data processing: Authenticating login information and processing requests for learning materials.

[2128] Output: Teaching material data.

[2129] Specific operation: Students log in to their devices, search for the teaching materials uploaded by the teacher, and press the download button.

[2130] Step 6:

[2131] Requested by: Server

[2132] Processing content: The server provides teaching material data in response to student requests.

[2133] Input: Student materials request.

[2134] Data processing: Search for teaching material data and include it in the HTTP response.

[2135] Output: A response containing the teaching material data is sent to the student's device.

[2136] Specific operation: The server retrieves digital learning materials from the database and provides them to students in a downloadable format.

[2137] Step 7:

[2138] Requested by: Server

[2139] Processing content: The server inputs the submitted assignment into a generative AI model and performs automatic grading.

[2140] Input: Submitted assignment response data.

[2141] Data processing: The answer data is fed into the generative AI model to obtain the scoring results.

[2142] Output: Scoring results.

[2143] Specific operation: The server inputs the assignments submitted by the students into the generative AI model and generates the grading results.

[2144] Step 8:

[2145] Requested by: Server

[2146] Processing details: The server saves the grading results in a database and notifies the teacher's terminal.

[2147] Input:Scoring results.

[2148] Data processing: The grading results are stored in a database and notifications are sent to teachers.

[2149] Output: Saved grading results, notifications.

[2150] Specific operation: The server saves the generated grading results in a database and sends a notification to the teacher's terminal saying "The grading results have been updated."

[2151] Step 9:

[2152] Requester: User (teacher)

[2153] Processing details: Teachers check the grading results on their smartphones or computers.

[2154] Input: Notification from the server.

[2155] Data processing: Retrieve the scoring results from the database and convert them into a display format.

[2156] Output: The results are displayed on the screen.

[2157] Specific operation: The teacher clicks on the notification on the device and checks the grading results.

[2158] In this way, the present invention provides a system that can manage student information, provide digital teaching materials, automatically grade assignments, manage grades, and check progress on a smartphone in an integrated manner.

[2159] 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.

[2160] This invention relates to a system that combines the centralized management of student information, provision of digital teaching materials, shared document management, and electronic grading functions with an emotion engine that recognizes user emotions. This system is composed of three main elements: a server, a terminal, and a user. The emotion engine recognizes user emotions and reflects them in the system, with the aim of further improving the quality of education. We will now explain in detail how each element works together and how the invention is specifically implemented.

[2161] A centralized student information management system

[2162] server

[2163] The server centrally manages student grades, attendance information, and records, making them accessible to teachers. This allows teachers to quickly obtain the information they need. Furthermore, the emotion engine stores students' emotional information on the server, enabling comprehensive information management.

[2164] For example, if a teacher wants to check the grades and recent emotional state of a specific student, a request is sent from the device. The server retrieves the student's grades and emotional state from the database and returns them to the teacher's device.

[2165] Online Learning Platform

[2166] server

[2167] The server provides digital learning materials and assignments for users (teachers and students) to access. Teachers upload learning materials, and students can view and study them online. The emotion engine recognizes students' emotional state in real time during online learning, improving the effectiveness of their learning.

[2168] For example, when a teacher uploads a new assignment, the server stores the data and students download it to study. The emotion engine monitors students' emotions as they work on the assignment and provides feedback according to their learning progress.

[2169] Terminal

[2170] The terminal provides an interface for users to access the server and upload or download learning materials. It also has an emotion engine that recognizes users' emotions in real time.

[2171] Example: When a student logs into an online learning platform from their home device and downloads materials provided by their teacher to study, the emotion engine recognizes the student's emotional state and displays advice to optimize learning efficiency.

[2172] Shared Document Management System

[2173] server

[2174] The server provides a system that allows teachers to share teaching materials and lesson plans, and stores and updates the shared documents. The emotion engine strengthens the collaborative system among teachers by monitoring the viewing status of the shared documents and the emotional state of the viewers.

[2175] Example: Teacher A uploads a lesson plan he created to the server, and when Teacher B views the document, the emotion engine recognizes Teacher B's reaction and provides feedback.

[2176] Electronic Scoring System

[2177] server

[2178] The server automatically grades submitted exam questions and assignments and stores the results in a database. In addition, an emotion engine monitors the student's emotional state when answering questions and takes this into account as a factor that may affect the grade.

[2179] Example: When a teacher uploads exam answers scanned on a device, the server processes the answers in an electronic scoring system, and the emotion engine analyzes the student's emotional state and notifies the teacher of the results.

[2180] Terminal

[2181] The device provides an interface for teachers to upload exam and assignment answers and view the automated marking results. It also has an emotion engine that monitors the teacher's reactions and emotional state.

[2182] Example: When a teacher uses a device at home to scan an answer sheet, send it to a server, and receive the results of automatic grading, the emotion engine recognizes the teacher's emotional state and makes suggestions to reduce stress.

[2183] Example

[2184] Example 1: Student performance management and emotion monitoring

[2185] 1. Send a request to view student grades from the teacher's device.

[2186] 2. The server retrieves the student's grades and emotional state from the database.

[2187] 3. The server sends the grade information and emotional state to the teacher's terminal, and the teacher checks the information.

[2188] Example 2: Online classes and emotional feedback

[2189] 1. The teacher uploads the teaching materials from the device to the server.

[2190] 2. The server stores the learning materials and makes them accessible to students.

[2191] 3. Students download the learning materials to their devices and proceed with their studies.

[2192] 4. The emotion engine monitors students' emotional state in real time while they are learning and provides appropriate feedback.

[2193] Example 3: Electronic scoring and sentiment analysis

[2194] 1. The teacher sends the exam answer sheet from the terminal to the server.

[2195] 2. The server uses an electronic scoring system to automatically score the tests.

[2196] 3. The emotion engine analyzes the student's emotional state when answering and reflects this in the scoring results.

[2197] 4. The server sends the scoring results and emotion analysis results to the teacher's terminal, where the teacher can check them.

[2198] The system of the present invention significantly reduces the workload of teachers and enables them to effectively utilize their expertise. The introduction of an emotion engine provides feedback based on the user's emotional state, further improving the quality and efficiency of education.

[2199] The processing flow will be explained below.

[2200] A centralized student information management system

[2201] Process flow: Viewing student grades and emotional information

[2202] Step 1:

[2203] A user (teacher) sends a request from a terminal to view the grades and emotional information of a specific student.

[2204] Step 2:

[2205] The terminal forwards the request to the server.

[2206] Step 3:

[2207] A server accesses a database containing student performance and emotional information.

[2208] Step 4:

[2209] The server retrieves the student's grade information and emotion information from the database.

[2210] Step 5:

[2211] The server transmits the acquired performance information and emotion information to the terminal.

[2212] Step 6:

[2213] The terminal displays the received information on the screen, and the user (teacher) checks it.

[2214] Online Learning Platform

[2215] Process flow: Uploading teaching materials and monitoring emotions

[2216] Step 1:

[2217] The user (teacher) selects the teaching material file and sends an upload request from the terminal.

[2218] Step 2:

[2219] The terminal uploads the selected educational material file to the server.

[2220] Step 3:

[2221] The server stores the received teaching material file in a data storage.

[2222] Step 4:

[2223] The server sends a notification to the device that the upload is complete.

[2224] Step 5:

[2225] A user (student) sends a request to access the online learning platform from a terminal.

[2226] Step 6:

[2227] The terminal accesses the server and sends a request to acquire a list of available learning materials.

[2228] Step 7:

[2229] The server retrieves a list of available learning materials from the database and sends it to the terminal.

[2230] Step 8:

[2231] The terminal displays a list of teaching materials on the screen, which the user (student) can view.

[2232] Step 9:

[2233] The emotion engine analyzes the user's (student's) facial expressions and voice in real time to recognize their emotional state.

[2234] Step 10:

[2235] The emotion engine sends feedback to the device based on the recognized emotional state to improve learning efficiency.

[2236] Shared Document Management System

[2237] Process flow: Sharing lesson plans and emotional feedback

[2238] Step 1:

[2239] The user (teacher) selects a lesson plan document and sends a sharing request from their device.

[2240] Step 2:

[2241] The device uploads the document to the server.

[2242] Step 3:

[2243] The server saves the document in a shared folder and updates the sharing settings.

[2244] Step 4:

[2245] The server sends a notification of completion of sharing to the terminal.

[2246] Step 5:

[2247] Another user (teacher) sends a request from their device to find a shared lesson plan document.

[2248] Step 6:

[2249] The terminal accesses the shared folder and sends a request to the server to search for the document.

[2250] Step 7:

[2251] The server retrieves the document from the shared folder and sends it to the terminal.

[2252] Step 8:

[2253] The terminal displays the received document on the screen, and the user (teacher) views it.

[2254] Step 9:

[2255] The emotion engine analyzes the user's (teacher's) facial expressions and voice in real time and recognizes their reactions to shared documents.

[2256] Step 10:

[2257] The emotion engine sends feedback and improvement suggestions to the device based on the recognized emotional state.

[2258] Electronic Scoring System

[2259] Process flow: Automatic marking of assignments and sentiment analysis

[2260] Step 1:

[2261] The user (teacher) scans the students' answer sheets and sends a request from the terminal to upload them to the electronic marking system.

[2262] Step 2:

[2263] The device uploads the scanned image of the answer sheet to the server.

[2264] Step 3:

[2265] The server converts the received image data into text data using optical character recognition (OCR) technology.

[2266] Step 4:

[2267] The server applies an automatic scoring algorithm based on the text data.

[2268] Step 5:

[2269] The emotion engine analyzes the facial expressions and voice of students during their responses and generates emotional information.

[2270] Step 6:

[2271] The server stores the scoring results and emotion information in a database.

[2272] Step 7:

[2273] The server sends a notification including the grading results and emotion information to the teacher's terminal.

[2274] Step 8:

[2275] The terminal displays the received scoring results and emotion information on the screen, and the user (teacher) checks them.

[2276] Step 9:

[2277] The emotion engine analyzes teachers' reactions in real time and provides feedback and stress-reducing suggestions as appropriate.

[2278] Example 2

[2279] 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."

[2280] While traditional education systems require centralized management of student information and efficient online learning, they lack functionality such as emotion recognition and real-time feedback, making it difficult to maximize student learning outcomes. Furthermore, there are limited means to streamline teacher work, and strengthening cooperation among teachers and improving the accuracy of automated grading of exams and assignments are also issues.

[2281] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2282] In this invention, the server includes an information management means, an online learning means, a sharing management means, a scoring means, and an emotion recognition means. This makes it possible to:

[2283] 1. Students' grades, attendance, history and emotional information can be managed in an integrated manner.

[2284] 2. Efficient online learning can be achieved through the uploading, viewing, and editing of teaching materials, as well as real-time monitoring of students' emotional states.

[2285] 3. Teachers can strengthen collaboration and share teaching materials and lesson plans more efficiently.

[2286] 4. Exams and assignments can be graded automatically, and emotion recognition can be used to reflect emotional information in the grading results.

[2287] The "information management means" is a system including a database that comprehensively manages student grades, attendance information, history, and emotional information.

[2288] "Online learning means" means a system that includes functions for providing educational materials digitally and enabling students to learn online, and allows for the uploading, viewing, and modification of educational materials, as well as real-time monitoring of students' emotional state.

[2289] A "shared management tool" is a system that allows teachers to share teaching materials and lesson plans with each other.

[2290] A "grading tool" is a system that automatically grades exams and assignments.

[2291] The "emotion recognition means" is a system that recognizes the user's emotions in real time and reflects them in education.

[2292] This invention relates to a system that combines the functions of unified student information management, digital teaching materials provision, shared document management, and electronic grading with an emotion recognition engine that recognizes user emotions in real time. This system includes three main elements: a server, a terminal, and a user, and these elements work in conjunction with each other.

[2293] Hardware and software used

[2294] The system mainly uses the following hardware and software:

[2295] Server: Database and emotion recognition engine (e.g., SQL database, emotion recognition algorithm implemented in Python)

[2296] Device: The interface through which the user accesses the device (e.g., PC, tablet, dedicated application)

[2297] Users: Teachers and students

[2298] A centralized student information management system

[2299] server

[2300] The server maintains a database that comprehensively manages student grades, attendance, history, and emotional information. Upon request from a teacher, it retrieves the relevant student data and returns it to the teacher's device.

[2301] Example: When a teacher wants to check the grade information and emotional state of a particular student from his / her terminal, the server retrieves the information from the database and sends it to the teacher's terminal.

[2302] Online Learning Platform

[2303] server

[2304] The server digitally stores teaching materials uploaded by teachers and makes them available for students to access online. An emotion recognition engine also recognizes students' emotional state while they are studying and provides appropriate feedback.

[2305] Example: When a teacher uploads new learning materials, the server stores them and makes them available for students to view. An emotion recognition engine monitors students' emotional state while they are learning and generates feedback according to their learning progress.

[2306] Terminal

[2307] The device provides an interface for students to access online learning platforms, download learning materials, and study. It also includes an emotion recognition engine that can recognize users' emotions in real time.

[2308] Example: When a student is downloading learning materials from their home device and studying, an emotion recognition engine analyzes the student's emotional state and displays advice on how to relax if stress levels are rising.

[2309] Shared Document Management System

[2310] server

[2311] The server allows teachers to upload, save, and update shared documents. The emotion recognition engine monitors the viewing status of shared documents and the emotional state of the viewer, and provides feedback.

[2312] Example: When Teacher A uploads a shared document to the server and Teacher B views it, an emotion recognition engine analyzes Teacher B's reaction and provides Teacher A with feedback based on the reaction.

[2313] Electronic Scoring System

[2314] server

[2315] The server automatically grades test answers and assignments, storing the results in a database. An emotion recognition engine also analyzes the emotional state of students when they answer questions and reflects this in the grades.

[2316] Example: When a teacher scans an answer sheet and sends it to a server, the electronic scoring system automatically scores it and sends the results and sentiment analysis results to the teacher's device.

[2317] Terminal

[2318] The device provides an interface for teachers to upload exam and assignment answers and receive automated grading results. It also includes an emotion recognition engine that monitors teachers' reactions and emotional state.

[2319] Example: When a teacher scans an answer sheet using a device at home and sends it to a server, and receives the grading results and emotion analysis results, the emotion recognition engine monitors the teacher's stress level and suggests relaxation methods if necessary.

[2320] Example

[2321] Prompt Sentence Examples

[2322] "Please detail the procedures for faculty to monitor students' academic performance and emotional state."

[2323] "Please explain specific ways in which you can monitor students' emotional states in online learning platforms."

[2324] "Please show us specifically how you will perform sentiment analysis in your electronic scoring system and reflect it in the results."

[2325] This system will reduce the workload of teachers and maximize the learning effect of students. The introduction of an emotion recognition engine will enable real-time feedback, which is expected to further improve the quality of education.

[2326] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2327] A centralized student information management system

[2328] Step 1:

[2329] A teacher sends a request to view a student's grades on a terminal. The input is the teacher's identification information for the student (student ID, name, etc.). The terminal generates this request and sends it to the server. The output is the request data sent to the server.

[2330] Step 2:

[2331] The server receives the request and retrieves the student's grades and emotional state from the database. The input is the request data from the teacher. The server executes the database query to retrieve the grade information and emotional state information. The output is the retrieved data of the student's grades and emotional state.

[2332] Step 3:

[2333] The server returns the acquired information to the teacher's terminal. The input is the student's grades and emotional state data acquired by the server. The server structures this data and sends it to the teacher's terminal. The output is the grade information and emotional information acquired by the teacher.

[2334] Step 4:

[2335] The teacher checks the information on the terminal. The input is the grade information and emotional state data sent from the server. The teacher displays and checks the received information through the terminal interface. The output is information that the teacher uses to make decisions.

[2336] Online Learning Platform

[2337] Step 1:

[2338] The teacher uploads the teaching material from the terminal. The input is the digital teaching material file and related metadata (title, description, etc.). The terminal collects this data and sends it to the server. The output is the uploaded data to the server.

[2339] Step 2:

[2340] The server stores the teaching materials and sets them up so that students can access them. The input is the teaching material data and metadata sent by the teacher. The server stores this in a database and sets permissions so that students can access it. The output is the teaching materials stored and accessible.

[2341] Step 3:

[2342] Students download learning materials to their devices and progress with their studies. The input is the student sending a download request and the learning material data stored on the server. The device generates a request and retrieves the learning material from the server. The output is the learning material data downloaded to the student's device.

[2343] Step 4:

[2344] The emotion engine monitors students' emotional states in real time and provides feedback. The input is data such as the student's facial expressions, voice volume, and tone of voice obtained from the device's camera and microphone. The emotion engine analyzes this data and estimates the student's emotional state. The output is advice and recommendations presented to the student as real-time feedback.

[2345] Shared Document Management System

[2346] Step 1:

[2347] The teacher uploads a shared document from a terminal. The input is the shared document file and related metadata. The terminal sends these to the server. The output is the uploaded data to the server.

[2348] Step 2:

[2349] The server saves the document and sets it up so that other teachers can access it. The input is the shared document data sent by the teacher. The server saves it in a database and sets permissions so that other teachers can access it. The output is the saved document and access right setting data.

[2350] Step 3:

[2351] Another teacher views the document on their device. The input is a view request and the document data stored on the server. The device generates a request and retrieves the document from the server. The output is the document data displayed on the teacher's device.

[2352] Step 4:

[2353] The emotion engine monitors the viewer's emotional state and provides feedback. The input is data such as the teacher's facial expression, voice volume, and tone obtained from the device's camera and microphone. The emotion engine analyzes this data and estimates the teacher's emotional state. The output is advice and recommendations that are presented to the teacher as feedback during viewing.

[2354] Electronic Scoring System

[2355] Step 1:

[2356] The teacher sends the exam answer sheet from the terminal. The input is a digital file of the scanned exam answer sheet. The terminal sends this to the server. The output is the exam answer data sent to the server.

[2357] Step 2:

[2358] The server uses an electronic marking system to perform marking. The input is test answer data. The server calls the electronic marking system and automatically performs marking. The output is marking result data.

[2359] Step 3:

[2360] The emotion engine analyzes the emotional state of the student when answering. The input is facial expression and voice data recorded when answering. The emotion engine analyzes this and estimates the emotional state. The output is emotion analysis result data.

[2361] Step 4:

[2362] The server sends the scoring results and sentiment analysis results to the teacher's terminal. The input is the scoring result data and sentiment analysis result data. The server structures these and sends them to the teacher's terminal. The output is the scoring results and sentiment analysis results received by the teacher.

[2363] Step 5:

[2364] The teacher checks the grading results and sentiment analysis results on the terminal. The input is the grading results and sentiment analysis results received from the server. The teacher displays and checks this information on the terminal. The output is information that the teacher can use to make decisions.

[2365] (Application example 2)

[2366] 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."

[2367] Existing educational systems manage students' grades and learning progress without considering their emotional state, making it difficult to provide optimal instruction and feedback to individual students. Furthermore, general online shopping sites lack a means to provide a personalized shopping experience that reflects users' emotional state. There is a need to address these issues, improve the quality and efficiency of education, and enhance the user experience of online shopping.

[2368] 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.

[2369] In this invention, the server includes an information management means, a learning means, a shared document management means, a scoring means, and an emotion-aware shopping assistant means, thereby enabling a comprehensive education and shopping experience that takes into account the user's emotions.

[2370] "Information management means" refers to the part of the system that centrally manages students' grades, attendance information, and records, and allows teachers to access this information.

[2371] "Learning tools" are the system's capabilities to provide learning materials digitally and enable students to learn online.

[2372] The "shared document management tool" is part of a system that provides the ability for teachers to share teaching materials and lesson plans and edit them collaboratively.

[2373] A "grading tool" is a system that has the function of automatically grading test questions and assignments and providing the results to teachers.

[2374] The "emotion recognition shopping assistant means" is a system function that analyzes the user's facial expressions and voice to recognize their emotions, and then makes product recommendations and promotions based on this.

[2375] The system for implementing this invention mainly comprises a server, a terminal, and a user. Each of these components will be described in detail below.

[2376] Information management means

[2377] The information management system is provided by a server and is a system that centrally manages student grades, attendance information, and records. Teachers can access this information using their terminals and quickly obtain the data they need. The data is stored and managed in a database on the server.

[2378] Learning tools

[2379] Learning tools are provided by a server. The server provides learning materials and assignments in digital format, and students can study online using their devices. Teachers upload learning materials to the server, and students download them to study. The system is also equipped with an emotion engine that provides feedback based on students' emotional state.

[2380] Shared document management tools

[2381] The shared document management system is provided by a server and allows teachers to share teaching materials and lesson plans. Teachers can upload documents from their devices, and other teachers can view and edit them collaboratively. The emotion engine also monitors the emotional state of viewers and provides effective feedback.

[2382] Scoring method

[2383] The grading method is a function in which the server automatically grades submitted exam questions and assignments. When teachers scan and upload answer sheets from their devices, the server processes them with an electronic grading system. In addition, an emotion engine monitors the students' emotional state when answering, and this is also reflected in the grading results.

[2384] Emotion-aware shopping assistant

[2385] The emotion-aware shopping assistant uses the user's terminal or smart device (e.g., smartphone or tablet) to analyze the user's facial expressions and voice to recognize emotions. Based on the recognized emotions, the server provides appropriate product recommendations and promotions. This allows the user to have an individualized shopping experience.

[2386] Hardware and software used

[2387] Hardware used: smartphone, tablet, PC, camera

[2388] Software used: Python, Flask, OpenCV, TextBlob

[2389] Processing flow

[2390] The specific process flow is implemented based on the following steps:

[2391] 1. Obtain the user's camera video and audio input.

[2392] 2. The captured video is analyzed using OpenCV and the face_recognition library to analyze the user's facial expressions and recognize their emotional state.

[2393] 3. The voice input (or text) is analyzed with the TextBlob library to determine the user's sentiment as text.

[2394] 4. Based on the results of sentiment and text analysis, the server recommends appropriate products and promotions to the user.

[2395] Specific examples

[2396] 1. When a user opens an online shopping app on their smartphone, if the camera recognizes the user's face and determines that they are "Happy," the app will recommend "new fashion items that perfectly match their current mood."

[2397] 2. When a user asks "What are your recent recommendations?" using voice input, TextBlob analyzes the voice text, and if it is determined to be "positive," it suggests products with many positive reviews.

[2398] Prompt Sentence Examples

[2399] 1. "Analyze this user's facial expressions and voice to determine their emotional state."

[2400] 2. "What promotion should I offer if the user has a smiling face?"

[2401] This provides a holistic education and purchasing experience that takes into account the user's emotions.

[2402] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2403] Step 1:

[2404] The user launches the application on their device (smartphone or tablet).

[2405] Input: Launching an app on a smartphone or tablet.

[2406] Output: The app starts and goes to the initial screen.

[2407] Step 2:

[2408] The device's camera captures the user's face and obtains video data in real time.

[2409] Input: Camera image (user's face).

[2410] Output: Captured video frames.

[2411] Step 3:

[2412] The video data acquired by the device is analyzed using OpenCV and the face_recognition library to recognize the user's facial expressions.

[2413] Input: Captured video frames.

[2414] Output: Recognized facial expression data (e.g. smile, sadness).

[2415] Step 4:

[2416] The user speaks and the device captures the speech and converts it into text.

[2417] Input: Audio data.

[2418] Output: Audio converted to text data.

[2419] Step 5:

[2420] The device uses the TextBlob library to analyze the sentiment of the text converted from the audio data.

[2421] Input: Text data.

[2422] Output: Sentiment analysis result (e.g. positive, negative).

[2423] Step 6:

[2424] The device sends facial expression data and text analysis results to the server.

[2425] Input: facial expression data, emotion analysis results.

[2426] Output: Sending data to the server.

[2427] Step 7:

[2428] The server determines product recommendations and promotions based on the received data according to the user's emotional state.

[2429] Input: facial expression data, emotion analysis results.

[2430] Output: Recommendation data, promotion data.

[2431] Step 8:

[2432] The server transmits recommendation data and promotion data to the terminal.

[2433] Input: Recommendation data, Promotion data.

[2434] Output: Sending data to a terminal.

[2435] Step 9:

[2436] The device displays the received recommendations and promotions to the user.

[2437] Input: Recommendation data, Promotion data.

[2438] Output: Recommendations and promotion information displayed in a user interface.

[2439] 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.

[2440] 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.

[2441] 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.

[2442] 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.

[2443] 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.

[2444] 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.

[2445] 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).

[2446] 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, ba...

Claims

1. A school information management system that centrally manages student information and makes it accessible to teachers; Online learning means to provide educational materials digitally and enable students to learn online; A shared document management tool that allows teachers to share teaching materials and lesson plans with each other, an electronic marking means for automatically marking exam questions and assignments; A system including:

2. 2. The system according to claim 1, wherein the school information management means for managing student information in a unified manner and making it accessible to teachers includes a database for managing student grades, attendance information, and histories in an integrated manner.

3. 10. The system of claim 1, wherein the online learning means for providing educational materials digitally and enabling students to learn online includes functionality for enabling uploading, viewing, and modification of educational materials.

Images