system

Abstract

Provide a system. 【Solution means】 Means for inputting educational materials, Means for automatically generating teaching materials based on the input materials, Means for displaying or distributing the generated teaching materials, Means for inputting and storing the academic performance data of students, Means for analyzing the stored academic performance data and visualizing learning trends, Means for automatically preparing and transmitting information to guardians, Means for managing schedules related to educational activities and supporting efficient time scheduling, Means for proposing a guidance approach according to the learning situation of individual students, A system including the above.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the educational field, the work done by teachers, such as administrative work, teaching material preparation, grade management, and parent communication, is overloaded, so the quality of education may decline. Due to this situation, teachers cannot ensure the time for meticulous guidance to individual students, and the equality and quality improvement of educational opportunities are hindered.

Means for Solving the Problems

[0005] The present invention aims to reduce the workload of teachers and improve the quality of education by providing a system that inputs educational materials, automatically generates teaching materials from them, and securely manages student performance data. Specifically, it includes means for inputting educational materials based on the curriculum, means for displaying or distributing the generated teaching materials, means for visualizing performance data in real time, means for automatically sending information to parents, means for efficiently managing schedules related to educational activities, and means for proposing instructional approaches according to students' learning progress.

[0006] "Educational materials" refer to information and data prepared for use in lessons and learning support, and include textbooks, curricula, workbooks, and explanatory books.

[0007] "Material generation" is the process of creating and formalizing educational materials that can be used in classes and learning activities, based on the input educational materials and curriculum information.

[0008] "Performance data" refers to a collection of information regarding students' academic performance, including test scores, evaluation results, and progress.

[0009] "Visualization" is the process of representing data and information visually and presenting them in formats such as graphs and tables to facilitate understanding and analysis.

[0010] "Information for parents" refers to various types of information that should be provided to parents, including information on students' learning progress and important announcements from the school.

[0011] "Automatic transmission" refers to the process of automatically sending emails or messages according to programmed conditions and timings, enabling communication without requiring human intervention.

[0012] "Schedule management" is the process of organizing and planning the schedules of tasks and events that need to be carried out in educational activities and related work.

[0013] "Proposing an instructional approach" is an activity that involves analyzing each student's learning situation and needs, and then presenting the optimal educational methods and strategies based on that data. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), etc.

[0018] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention is a system designed to streamline the diverse tasks that teachers perform in the educational setting. This system consists of a server and terminals, and provides various forms of support to teachers (users). Its functions are described below.

[0036] When users prepare teaching materials for a class, they use a terminal to input information about the class theme and the textbooks to be used. Based on this information, the server selects materials from its database that are consistent with the curriculum and automatically generates slides and handouts. The results are sent to the terminal, where the user can review the details and use them in class.

[0037] For grade management, users input students' test results using their devices. This data is sent to a server, where statistical methods are used to analyze and visualize grades. The server then sends reports to the devices indicating each student's level of understanding and the overall class trend, which users can utilize when providing guidance to students.

[0038] Furthermore, regarding communication with parents, the server automatically organizes student learning progress and information from the school, and sends emails to parents according to pre-configured conditions. This significantly reduces manual work by users and enables effective communication.

[0039] Furthermore, through the schedule management function, users input their class and administrative schedules, allowing the server to oversee the entire schedule and support efficient time management. The server detects overlaps and inconsistencies and suggests the optimal schedule, allowing users to focus on their educational activities with peace of mind.

[0040] In the individualized tutoring plan proposal, the server generates the optimal teaching approach based on an analysis of each student's academic performance and provides it to the user. The user can then use this as a reference to provide individualized support to each student.

[0041] Thus, this system significantly reduces the workload of teachers and contributes to improving the quality of education.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] Users input lesson topics, grade levels, and textbook information using their devices. This provides the system with the necessary basic data for teaching materials.

[0045] Step 2:

[0046] The server receives information entered from the terminal, searches the database for relevant teaching materials, and verifies that the information matches the curriculum before selecting the appropriate educational materials.

[0047] Step 3:

[0048] The server automatically generates slides and printouts based on the selected information. Templates are used to design teaching materials in a visually consistent format.

[0049] Step 4:

[0050] The server sends the generated learning materials to the user's device, allowing them to review and edit them. Users can request revisions to the content as needed.

[0051] Step 5:

[0052] Users enter students' test results using a terminal. This records the students' performance data in the system.

[0053] Step 6:

[0054] The terminal sends the entered performance data to the server. The server uses this data to perform statistical analysis and calculate the average score and the trend in understanding.

[0055] Step 7:

[0056] The server summarizes the analysis results in graphs and tables and sends them to the terminal in a visualized format. The user then uses this data to provide feedback to students and adjust lessons.

[0057] Step 8:

[0058] The server automatically prepares and sends emails to parents containing information about their child's learning progress and other important matters. The timing and content of these emails are adjusted according to the settings.

[0059] Step 9:

[0060] Users input their class and school work schedules using their terminals, and the server receives this information and manages the schedule. By efficiently coordinating schedules, it supports users in managing their time.

[0061] Step 10:

[0062] The server analyzes each student's academic performance data and proposes individualized tutoring plans based on the results. Users can then utilize these suggestions to provide personalized instruction to their students.

[0063] (Example 1)

[0064] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0065] In educational settings, teachers need to efficiently perform a wide range of tasks. However, tasks such as preparing teaching materials, managing grades, communicating with parents, managing schedules, and developing individualized instruction plans are complex and time-consuming, potentially negatively impacting the quality of education. This invention aims to alleviate the workload of teachers and improve the quality of education.

[0066] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0067] In this invention, the server includes means for inputting educational themes and related information, means for selecting educational resources from a database based on the input information and automatically generating teaching materials using a generation AI model, and means for transmitting and displaying the generated teaching materials on a terminal. This enables the streamlining of teachers' work processes and provides high-quality educational support.

[0068] An "educational theme" is a concept that indicates the content or focus to be taught in a particular class or lecture within an educational activity.

[0069] "Related information" refers to materials and data linked to the educational theme, as well as knowledge related to the textbooks used and the desired educational outcomes.

[0070] "Educational resources" refer to teaching materials, documents, datasets, and other materials available for conducting education.

[0071] A "database" refers to a system or collection of information and data used to efficiently store, retrieve, and manage large amounts of information and data. In this context, it serves the purpose of storing educational resources.

[0072] A "generative AI model" refers to an artificial intelligence model used to automatically generate content and data based on input information.

[0073] "Educational materials" refer to documents, materials, slides, multimedia content, etc., used for educational purposes, and are learning materials provided to learners in education.

[0074] "Evaluation data" refers to numerical data and information used to assess the learning outcomes and academic abilities of students or course participants.

[0075] An "environment capable of protecting information" refers to a system or infrastructure in which data and information are securely managed and protected from unauthorized external access.

[0076] This invention is a system designed to streamline the work of teachers in educational settings, and consists of a server and terminals. This system covers everything from inputting educational themes to creating teaching materials using a generative AI model, managing grades, providing information to parents, managing schedules, and formulating individualized instruction plans.

[0077] First, the user uses a terminal to input the lesson topic and related information. The educational database contains a wide range of educational resources, which the server then accesses. For example, if the user inputs "I want to teach the history of World War II," the server selects relevant educational resources. Here, a generative AI model is used to automatically generate educational slides and materials that meet the user's requirements. In this generation process, an example of a prompt might be "List the major events of World War II and create educational slides."

[0078] After the teaching materials are generated, the server sends them to the terminal for the user to view and edit. After reviewing the materials on the terminal, the user utilizes them in actual lessons. For grade management, the user inputs student evaluation data into the terminal, which the server receives. This evaluation data is managed in a secure environment, and the server performs statistical analysis based on it. The results are visualized on the terminal, allowing the user to use them to improve student guidance.

[0079] Furthermore, the server has a function that automatically sends information to parents according to set conditions, based on organized student learning status and school information. This significantly reduces manual work by users and promotes smooth communication with parents. In addition, regarding schedule management, users input schedules related to educational activities into their terminals, and the server organizes them, supporting efficient time management.

[0080] Thus, this system aims to significantly reduce the workload of teachers and improve the quality of education.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] The user enters an educational theme and related information into their device. This input includes themes and textbooks to be used, depending on the objectives of the lesson. Specifically, the user enters "History of World War II" into a form on the device and presses the submit button. The entered information is then sent from the device to the server.

[0084] Step 2:

[0085] The server receives the input data and selects relevant resources by referring to a database of educational resources. The server searches the database based on the keyword "World War II" and extracts suitable educational data. At this stage, the server starts processing the generative AI model using a prompt (e.g., "List the main events of World War II and create educational slides").

[0086] Step 3:

[0087] The server utilizes an AI model to automatically generate educational slides. This process automatically generates slide images and text based on the teaching material data extracted in the previous step. The generated slides are then processed into PDF format on the server. The server then sends these processed materials to the user's device.

[0088] Step 4:

[0089] The user reviews the learning materials received on their device. They open the PDF slides on their device, view the content, and make any necessary edits. Once editing is complete, the user saves the materials for use in class.

[0090] Step 5:

[0091] The user inputs student evaluation data into their device. Specifically, this involves entering each student's score and comments into a spreadsheet and uploading it to the server. This evaluation data is then sent to the server.

[0092] Step 6:

[0093] The server securely stores the received evaluation data and performs analysis using statistical methods. The server uses a computational model to calculate average scores, performance distributions, and other metrics, and visualizes the results as graphs and charts. This visualized data is then sent to the terminal after analysis.

[0094] Step 7:

[0095] Users can review the analysis results on their devices and use them to inform their educational policies and future lesson plans. Based on the finalized results, they can take necessary actions and adjust their teaching strategies.

[0096] (Application Example 1)

[0097] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0098] In today's educational environment, the workload of teachers and educational institutions is increasing due to the wide range of tasks they must perform. Creating educational materials, managing student evaluation data, communicating with parents, and scheduling learning activities are all challenging to perform efficiently. Furthermore, integrated management tools are needed to realize educational support throughout the community. Overcoming these challenges and providing more effective educational support is essential.

[0099] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0100] In this invention, the server includes means for inputting educational information, means for automatically generating educational resources based on the input information, and means for proposing teaching methods tailored to the learning progress of individual students. This reduces the workload of educators and enables efficient educational support throughout the community.

[0101] "Educational information" is a general term for data and materials used by teachers and educational institutions to create teaching materials and lesson plans.

[0102] "Educational resources" refer to physical or digital materials such as teaching materials, handouts, and slides used in the course of education.

[0103] "Participant evaluation data" refers to data that shows the results obtained by learners through tests and evaluations, and includes grades and feedback information.

[0104] "Information for parents" refers to announcements regarding the student's learning progress and school activities, and is intended to facilitate communication with parents.

[0105] "Educational support across the entire community" refers to a system that efficiently supports educational activities throughout a broad community, without relying on specific educational institutions.

[0106] "Integrated management means" refers to systems and methods for centrally managing multiple education-related activities, aiming to improve the efficiency of the educational process.

[0107] The system for realizing this invention is centered around a server and terminals. Its main functions include inputting and managing educational information, automatically generating educational resources, managing student evaluation data, sharing information with parents, and providing an integrated management system aimed at supporting education throughout the community.

[0108] The server aggregates educational information using GOOGLE FI® rebase and performs data analysis using TENSORFLOW®. Based on the input educational information, the server automatically generates educational resources and transmits the results to terminals, creating a system that educators can easily access and use.

[0109] The terminal is operated by the educator, collecting student evaluation data and transmitting it to the server in real time. The student evaluation data is stored in a secure virtual environment, and learning trends are visualized through appropriate processing, presented in a format easily understandable to the educator. Furthermore, information for parents is automatically organized and communicated based on pre-configured criteria.

[0110] As a concrete example, in the event of a specific event held in a region, this system can contribute to the realization of efficient education while reducing the burden on educational settings by creating and providing educational resources related to the event in advance to educators at each school.

[0111] An example of a prompt for a generative AI model would be, "Please suggest educational resources for efficiently sharing relevant information in a specific event." This would likely yield output tailored to specific needs.

[0112] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0113] Step 1:

[0114] Users input educational information using their devices. This includes data on lesson topics, reference materials, and teaching materials to be used. The entered information is sent from the device to the server and stored in Firebase.

[0115] Step 2:

[0116] The server automatically generates educational resources using a generative AI model based on the received educational information. Specifically, it processes the data using TensorFlow, searches for relevant teaching materials in a database, and outputs them as slides and handouts.

[0117] Step 3:

[0118] The generated educational resources are sent from the server to the terminal, making them available for user review. Users can view this information on their terminal and distribute it as printed or electronic data as needed.

[0119] Step 4:

[0120] The user enters student evaluation data into their device. This evaluation data includes test results and records of class participation, and is sent from the device to the server.

[0121] Step 5:

[0122] The server receives student evaluation data and processes it in real time. The data is stored in a secure virtual environment, and the evaluation data is analyzed through computational processing to generate graphs and charts that visualize learning trends.

[0123] Step 6:

[0124] The generated visualization data of learning trends is sent from the server to the terminal, allowing the user to check each student's learning progress and use it to consider teaching methods.

[0125] Step 7:

[0126] The server automatically prepares information for parents based on configured conditions and sends it via email or a dedicated application. This includes updates on student progress and notifications of important school events.

[0127] Step 8:

[0128] For community-wide events, the server generates necessary educational resources in advance and provides relevant information to each terminal. This information is effectively utilized throughout the community to enhance educational support.

[0129] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0130] This invention combines an emotion engine with a system that supports various tasks faced by teachers in educational settings to provide more effective support. The system consists of a server, terminals, and an emotion engine, and is designed to enable teachers to conduct educational activities efficiently.

[0131] The user first uses a terminal to input information about the lesson theme and curriculum. The server receives this information and selects relevant teaching materials from its database. Then, it automatically generates teaching materials based on the selected information and sends the generated materials to the terminal. This allows the user to immediately use the teaching materials they need for their lesson.

[0132] Furthermore, when users input student grades, the server aggregates the data, analyzes the grades, and creates graphs. This information is provided to the terminal, allowing users to visualize the students' level of understanding. The emotion engine also analyzes the user's voice and facial expressions to recognize their emotional state. This allows the server to detect the stress and satisfaction the user feels during class, and to receive and process this feedback.

[0133] For example, if the emotion engine detects that a user is stressed, the server will suggest readjusting the lesson plan to help the user continue their educational activities in a healthy manner. It can also dynamically change the content of the learning materials based on the user's emotional state. This further improves the quality of education.

[0134] By utilizing the emotion engine in this invention, users can receive not only simple preparation of teaching materials and management of grades, but also advanced educational support that responds to their individual emotional states. This system reduces the burden on users and enables more effective and humane education in educational settings.

[0135] The following describes the processing flow.

[0136] Step 1:

[0137] Users input lesson topics, grade levels, and textbook information through their devices. This provides the system with the necessary educational material data.

[0138] Step 2:

[0139] The server receives information entered from the terminal, searches the database, and selects the appropriate educational materials. Identifying materials that align with the curriculum is crucial.

[0140] Step 3:

[0141] The server automatically generates slides and handouts for lessons using the selected materials. It applies templates to create visually meaningful teaching materials.

[0142] Step 4:

[0143] The server sends the generated learning materials to the terminal and provides an interface for the user to review the content and edit it as needed.

[0144] Step 5:

[0145] Users use their devices to input student test results and learning performance data. This allows evaluation information to be stored in a database.

[0146] Step 6:

[0147] The terminal sends the entered performance data to the server, which then statistically analyzes the data. The results are organized in the form of average scores, comprehension levels, and so on.

[0148] Step 7:

[0149] The server visualizes the analysis results in the form of graphs and tables and provides them to the terminal. Users can then use this information to understand learning trends and incorporate them into their instruction.

[0150] Step 8:

[0151] The server receives user voice and facial expression data via an emotion engine and analyzes their emotional state. It then generates feedback based on stress levels and concentration levels.

[0152] Step 9:

[0153] Based on the emotion engine's analysis of the user's emotions, the server suggests adjustments to the lesson content. This includes changing the difficulty level of the teaching materials and adjusting the pace of the lesson.

[0154] Step 10:

[0155] To reduce user stress, the server suggests activities for relaxation and a change of pace, supporting users in engaging in educational activities in a healthy manner.

[0156] (Example 2)

[0157] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0158] To reduce the workload of teachers in educational settings and provide more effective and individualized education, efficient preparation of teaching materials, performance management, analysis of learning progress, and adjustment of teaching methods based on these analyses are essential. Furthermore, a function is needed to address teachers' emotional states and dynamically adjust lesson plans. A system is required that can meet these needs while ensuring safe and efficient work processes.

[0159] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0160] In this invention, the server includes means for inputting educational content, means for automatically generating teaching materials based on the input content, and means for inputting and saving learner performance data. This enables improved work efficiency for teachers and advanced educational support, as well as flexible responses to the needs of individual learners and teachers.

[0161] "Educational content" refers to teaching materials and resources used in educational activities, and is a collection of information used by teachers for educational purposes.

[0162] "Terminal" refers to an information processing device operated by a user, and specifically includes devices such as personal computers and tablets.

[0163] "Learner" refers to anyone receiving education in the educational process, including students.

[0164] "Performance data" refers to information that records learners' learning outcomes, including test results and evaluations.

[0165] The "Internet" refers to an information network connected via public communication networks, enabling information sharing and communication among users.

[0166] "Curriculum" refers to a standardized educational program within an educational institution, and is a system of learning content provided as a curriculum.

[0167] A "schedule" refers to a plan of events and activities to be held within a specific period, and is created to support the efficient progress of educational activities.

[0168] "Emotional state" refers to the user's psychological and sensory state, including psychological changes such as stress and satisfaction.

[0169] The embodiments for carrying out the invention are described below.

[0170] This system is designed to support teachers' work in educational settings and consists of a server, terminals, and an emotion engine. Users input educational information using the terminals, and the system generates teaching materials and manages and analyzes grades via the server. The emotion engine also analyzes the user's emotional state and adjusts educational activities accordingly.

[0171] The server executes computer programs to process the received data. Python and related generative AI models are used for the automatic generation of educational materials. Specific functions include searching for educational materials from a database using Elasticsearch® and data analysis using Pandas and Matplotlib. The terminal displays information entered by the user and the received educational materials.

[0172] Users input information related to the lesson theme and curriculum into their terminals, sending data to the server. Based on this information, the server automatically generates teaching materials and sends them to the terminals. This allows users to immediately begin their educational activities.

[0173] Furthermore, by utilizing the emotion engine to analyze the user's emotional state, the server can suggest adjustments to the lesson plan based on that feedback. This allows teachers to conduct educational activities that take their own psychological state into account.

[0174] As a concrete example, when teaching "plant growth" in an elementary school science class, the user can input the lesson plan into the terminal, and the system can automatically generate the relevant teaching materials. An example of a prompt message to the generation AI model would be, "Please generate teaching materials on the topic of 'plant growth' for a 5th-grade elementary school science class. The materials should include illustrations and videos, and should be able to be taught in 20 minutes or less." This allows for the easy preparation of appropriate lesson content.

[0175] This system not only reduces the burden on teachers but also provides innovative educational technologies to improve the quality of education.

[0176] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0177] Step 1:

[0178] Users input lesson topics and curriculum information using their devices. This information includes the lesson objectives, desired learning outcomes, and the format of the materials to be used (text, images, videos, etc.). The entered data is sent to the server.

[0179] Step 2:

[0180] The server searches the database based on the information received from the user and selects relevant educational materials. Specifically, it uses ElasticSearch to search for educational materials in the database and passes the results to the material generation AI model. The input used in this step is the lesson theme and curriculum information provided by the user, and the output is a list of materials required by the material generation AI model.

[0181] Step 3:

[0182] The server automatically generates lesson materials by combining selected materials using an AI model for material generation. The generation process uses programming languages ​​such as Python to process the selected materials with the AI ​​model and generate optimal lesson materials. The input is the material list obtained in step 2, and the output is the completed lesson material.

[0183] Step 4:

[0184] The server sends the completed teaching materials to the terminal. The user can then review the received materials on the terminal and proceed with preparing for the lesson. The terminal displays the received materials to the user and downloads them as needed.

[0185] Step 5:

[0186] Users input student performance data collected during class into their terminals. This includes test results and project evaluations. The entered performance data is then sent to the server.

[0187] Step 6:

[0188] The server performs data analysis based on the received performance data. The analysis uses Python's Pandas and Matplotlib libraries to aggregate and visualize the data. The input is the performance data entered by the user, and the output is a visualized representation of the learner's trends.

[0189] Step 7:

[0190] The server operates an emotion engine to analyze the user's voice and facial expressions. User emotion data (such as stress levels and satisfaction) is input, and feedback is generated based on the analysis results. Speech recognition software and image processing libraries are used for emotion analysis.

[0191] Step 8:

[0192] Based on the analysis results, the server makes suggestions to the user regarding adjustments to the lesson plan. For example, if the user is experiencing high stress levels, it may suggest slowing down the pace of the lesson. This allows the user to create an optimal learning environment.

[0193] (Application Example 2)

[0194] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0195] In modern education, there is a need for individualized support tailored to each student's learning style and emotional state. In particular, when learners are experiencing emotional stress, or conversely, are highly engaged and excited, flexible adjustments to teaching materials and methods are essential. However, traditional educational support systems struggle to provide this emotional flexibility, placing a significant burden on educators. Therefore, there is a need for an educational support system that can detect students' emotional states and provide appropriate educational activities.

[0196] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0197] In this invention, the server includes means for inputting educational materials, means for detecting the learner's emotional state using emotion analysis technology and dynamically changing the content of the materials, and means for making suggestions for adjusting educational activities based on the emotional state. This makes it possible for educators to easily provide appropriate educational activities that correspond to the learner's emotional state.

[0198] "Means for inputting educational materials" refers to devices or methods for incorporating information and data necessary for education into a system.

[0199] "Means for automatically generating educational materials based on input materials" refers to a device or method that automatically creates educational materials for learners based on input educational information.

[0200] "Means for displaying or distributing generated teaching materials" refers to devices or methods for showing, electronically or physically, the created teaching materials to learners.

[0201] "Means for inputting and saving student performance data" refers to a device or method for inputting information regarding students' learning outcomes into a system and saving it for later use.

[0202] "Means for analyzing stored performance data and visualizing learning trends" refers to a device or method that analyzes recorded performance information and processes it into a format that can be easily understood at a glance.

[0203] "Means for automatically preparing and transmitting information to parents" refers to devices or methods that automatically collect educational information and provide it to parents.

[0204] "Means for managing schedules related to educational activities and supporting efficient time management" refers to devices or methods that organize educational schedules and assist in effective time allocation.

[0205] "Means of proposing instructional approaches tailored to the learning situation of individual students" refers to a device or method that presents the optimal instructional method based on each student's learning progress.

[0206] "Means for detecting a learner's emotional state using emotion analysis technology and dynamically changing the content of learning materials" refers to a device or method that analyzes a learner's emotions and adjusts the content of learning materials according to the situation.

[0207] "Means for making suggestions to adjust educational activities based on emotional state" refers to a device or method that provides advice for adjusting educational methods in accordance with the learner's emotions.

[0208] To realize this invention, a system specifically designed for educational settings will be used. This system consists of three main elements: a server, a terminal, and a user. Each element plays a specific role, thereby achieving effective educational support.

[0209] The server accepts input for educational materials and automatically generates teaching materials based on the input themes using a generative AI model. This generation process creates materials optimized to fit the educational curriculum. The server then sends the generated materials to devices, allowing users to view or distribute them. Furthermore, the server aggregates student performance data, securely stores it in a cloud environment, and provides real-time visualization of this data.

[0210] The terminal primarily functions as a user interface. Educators, as users, can review and show generated learning materials to learners through this terminal. The terminal also incorporates sentiment analysis technology, detecting learners' emotional states through audio and video and sending this information to the server. This allows the content of the learning materials to be dynamically adjusted according to the situation.

[0211] The user, acting as a teacher or educational support staff, operates the entire system. The user inputs educational materials into the system and manages subsequent educational activities. For example, if the user inputs student grades, the system analyzes and visualizes learning trends based on that data. Furthermore, if the server detects that a learner is experiencing stress, the user can receive suggestions from the server and adjust the lesson plan accordingly.

[0212] As a concrete example, when a user inputs the theme "basic arithmetic," the generative AI model generates arithmetic learning materials based on that theme, and if the learner is experiencing stress, it suggests slowing down the learning pace. This process can be achieved by using the following prompt example: "Generate educational materials for children based on the input theme. Also, adjust according to the emotional state, and slow down the learning speed if the learner is experiencing stress."

[0213] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0214] Step 1:

[0215] Users input educational materials using a terminal. This input includes information about the lesson theme and the curriculum it covers. The terminal prepares the data by sending this information to the server in digital format.

[0216] Step 2:

[0217] The server automatically generates educational materials using a generative AI model based on the received educational materials. Optimized materials are created based on the input theme. The generative AI model algorithmically processes the materials corresponding to each subject and outputs them in various formats (e.g., PDF or video materials).

[0218] Step 3:

[0219] The server sends the generated learning materials to the terminal, which then displays them to the user. The user can review the displayed materials and make modifications as needed. The materials are then distributed to learners in an appropriate format.

[0220] Step 4:

[0221] Users input student performance data using their devices. This performance information is based on the results of regular tests and in-class activities, and is transferred from the device to the server.

[0222] Step 5:

[0223] The server analyzes stored performance data and statistically visualizes learning trends. Specifically, it securely stores data in a cloud environment, performs statistical analysis and graph creation, and generates performance trends in real time.

[0224] Step 6:

[0225] The emotion analysis technology installed on the device collects emotional data from the learner's voice and facial expressions and sends it to a server. This data is used as input to determine whether the learner is experiencing stress.

[0226] Step 7:

[0227] The server analyzes the received emotional data and suggests changes to teaching materials or adjustments to the lesson plan based on its content. For example, it might notify the user of adjustments such as, "The generative AI model suggests slowing down the learning speed if stress levels are high."

[0228] Step 8:

[0229] Users receive suggestions from the server and adjust educational activities as needed. This allows for flexible responses to learners' emotional states and provides an effective learning experience.

[0230] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0231] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0232] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0233] [Second Embodiment]

[0234] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0235] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0236] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0237] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0238] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0239] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0240] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0241] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0242] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0243] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0244] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0245] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0246] This invention is a system designed to streamline the diverse tasks that teachers perform in the educational setting. This system consists of a server and terminals, and provides various forms of support to teachers (users). Its functions are described below.

[0247] When users prepare teaching materials for a class, they use a terminal to input information about the class theme and the textbooks to be used. Based on this information, the server selects materials from its database that are consistent with the curriculum and automatically generates slides and handouts. The results are sent to the terminal, where the user can review the details and use them in class.

[0248] For grade management, users input students' test results using their devices. This data is sent to a server, where statistical methods are used to analyze and visualize grades. The server then sends reports to the devices indicating each student's level of understanding and the overall class trend, which users can utilize when providing guidance to students.

[0249] Furthermore, regarding communication with parents, the server automatically organizes student learning progress and information from the school, and sends emails to parents according to pre-configured conditions. This significantly reduces manual work by users and enables effective communication.

[0250] Furthermore, through the schedule management function, users input their class and administrative schedules, allowing the server to oversee the entire schedule and support efficient time management. The server detects overlaps and inconsistencies and suggests the optimal schedule, allowing users to focus on their educational activities with peace of mind.

[0251] In the individualized tutoring plan proposal, the server generates the optimal teaching approach based on an analysis of each student's academic performance and provides it to the user. The user can then use this as a reference to provide individualized support to each student.

[0252] Thus, this system significantly reduces the workload of teachers and contributes to improving the quality of education.

[0253] The following describes the processing flow.

[0254] Step 1:

[0255] Users input lesson topics, grade levels, and textbook information using their devices. This provides the system with the necessary basic data for teaching materials.

[0256] Step 2:

[0257] The server receives information entered from the terminal, searches the database for relevant teaching materials, and verifies that the information matches the curriculum before selecting the appropriate educational materials.

[0258] Step 3:

[0259] The server automatically generates slides and printouts based on the selected information. Templates are used to design teaching materials in a visually consistent format.

[0260] Step 4:

[0261] The server sends the generated learning materials to the user's device, allowing them to review and edit them. Users can request revisions to the content as needed.

[0262] Step 5:

[0263] Users enter students' test results using a terminal. This records the students' performance data in the system.

[0264] Step 6:

[0265] The terminal sends the entered performance data to the server. The server uses this data to perform statistical analysis and calculate the average score and the trend in understanding.

[0266] Step 7:

[0267] The server summarizes the analysis results in graphs and tables and sends them to the terminal in a visualized format. The user then uses this data to provide feedback to students and adjust lessons.

[0268] Step 8:

[0269] The server automatically prepares and sends emails to parents containing information about their child's learning progress and other important matters. The timing and content of these emails are adjusted according to the settings.

[0270] Step 9:

[0271] Users input their class and school work schedules using their terminals, and the server receives this information and manages the schedule. By efficiently coordinating schedules, it supports users in managing their time.

[0272] Step 10:

[0273] The server analyzes each student's academic performance data and proposes individualized tutoring plans based on the results. Users can then utilize these suggestions to provide personalized instruction to their students.

[0274] (Example 1)

[0275] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0276] In educational settings, teachers need to efficiently perform a wide range of tasks. However, tasks such as preparing teaching materials, managing grades, communicating with parents, managing schedules, and developing individualized instruction plans are complex and time-consuming, potentially negatively impacting the quality of education. This invention aims to alleviate the workload of teachers and improve the quality of education.

[0277] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0278] In this invention, the server includes means for inputting educational themes and related information, means for selecting educational resources from a database based on the input information and automatically generating teaching materials using a generation AI model, and means for transmitting and displaying the generated teaching materials on a terminal. This enables the streamlining of teachers' work processes and provides high-quality educational support.

[0279] An "educational theme" is a concept that indicates the content or focus to be taught in a particular class or lecture within an educational activity.

[0280] "Relevant information" refers to materials, data, textbooks used, and knowledge related to the educational theme, textbooks to be used, and educational outcomes to be achieved.

[0281] "Educational resources" refer to teaching materials, materials, datasets, etc. that can be used for implementing education.

[0282] "Database" refers to a system or collection for efficiently storing, retrieving, and managing a large amount of information and data, and here it has the role of storing educational resources.

[0283] "Generative AI model" refers to an artificial intelligence model used to automatically generate content and data based on input information.

[0284] "Teaching materials" refer to documents, materials, slides, multimedia content, etc. used for educational purposes, which are learning materials provided to learners in education.

[0285] "Evaluation data" refers to numerical values and information for evaluating the learning achievements and academic abilities of students and course participants.

[0286] "An environment where information protection is possible" refers to a system or infrastructure equipped with a protection function for securely managing data and information and preventing unauthorized access from the outside.

[0287] The present invention is a system for streamlining the work of teachers in the educational field, which is composed of a server and a terminal. This system covers from the input of an educational theme to the creation of teaching materials using a generative AI model, grade management, information provision to guardians, schedule management, and formulation of an individual guidance plan.

[0288] First, the user uses a terminal to input the lesson topic and related information. The educational database contains a wide range of educational resources, which the server then accesses. For example, if the user inputs "I want to teach the history of World War II," the server selects relevant educational resources. Here, a generative AI model is used to automatically generate educational slides and materials that meet the user's requirements. In this generation process, an example of a prompt might be "List the major events of World War II and create educational slides."

[0289] After the teaching materials are generated, the server sends them to the terminal for the user to view and edit. After reviewing the materials on the terminal, the user utilizes them in actual lessons. For grade management, the user inputs student evaluation data into the terminal, which the server receives. This evaluation data is managed in a secure environment, and the server performs statistical analysis based on it. The results are visualized on the terminal, allowing the user to use them to improve student guidance.

[0290] Furthermore, the server has a function that automatically sends information to parents according to set conditions, based on organized student learning status and school information. This significantly reduces manual work by users and promotes smooth communication with parents. In addition, regarding schedule management, users input schedules related to educational activities into their terminals, and the server organizes them, supporting efficient time management.

[0291] Thus, this system aims to significantly reduce the workload of teachers and improve the quality of education.

[0292] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0293] Step 1:

[0294] The user enters an educational theme and related information into their device. This input includes themes and textbooks to be used, depending on the objectives of the lesson. Specifically, the user enters "History of World War II" into a form on the device and presses the submit button. The entered information is then sent from the device to the server.

[0295] Step 2:

[0296] The server receives the input data and selects relevant resources by referring to a database of educational resources. The server searches the database based on the keyword "World War II" and extracts suitable educational data. At this stage, the server starts processing the generative AI model using a prompt (e.g., "List the main events of World War II and create educational slides").

[0297] Step 3:

[0298] The server utilizes an AI model to automatically generate educational slides. This process automatically generates slide images and text based on the teaching material data extracted in the previous step. The generated slides are then processed into PDF format on the server. The server then sends these processed materials to the user's device.

[0299] Step 4:

[0300] The user reviews the learning materials received on their device. They open the PDF slides on their device, view the content, and make any necessary edits. Once editing is complete, the user saves the materials for use in class.

[0301] Step 5:

[0302] The user inputs student evaluation data into their device. Specifically, this involves entering each student's score and comments into a spreadsheet and uploading it to the server. This evaluation data is then sent to the server.

[0303] Step 6:

[0304] The server stores the received evaluation data in a secure environment and performs analysis using statistical methods. The server calculates the average score, grade distribution, etc. using a computational model and visualizes the results as graphs or charts. These visualized data are transmitted to the terminal after analysis.

[0305] Step 7:

[0306] The user checks the analysis results on the terminal and uses them for educational policies and the next class plan. Based on the confirmed results, necessary responses and adjustments to the guiding principles can be made.

[0307] (Application Example 1)

[0308] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0309] In the modern educational environment, the tasks that teachers and educational institutions should perform are diverse, and their burden is increasing. It is difficult to efficiently carry out tasks such as creating educational materials, managing evaluation data of learners, communicating with parents, and scheduling learning activities. Also, an integrated management means for realizing educational support across the entire local community is required. It is required to overcome these issues and provide more effective educational support.

[0310] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0311] In this invention, the server includes means for inputting educational information, means for automatically generating educational resources based on the input information, and means for proposing a guiding method according to the learning situation of each learner. Thereby, it becomes possible to reduce the workload of educators and realize efficient educational support across the entire local community.

[0312] "Educational information" is a general term for data and materials used by teachers and educational institutions to create teaching materials and lesson plans.

[0313] "Educational resources" refer to physical or digital materials such as teaching materials, handouts, and slides used in the course of education.

[0314] "Participant evaluation data" refers to data that shows the results obtained by learners through tests and evaluations, and includes grades and feedback information.

[0315] "Information for parents" refers to announcements regarding the student's learning progress and school activities, and is intended to facilitate communication with parents.

[0316] "Educational support across the entire community" refers to a system that efficiently supports educational activities throughout a broad community, without relying on specific educational institutions.

[0317] "Integrated management means" refers to systems and methods for centrally managing multiple education-related activities, aiming to improve the efficiency of the educational process.

[0318] The system for realizing this invention is centered around a server and terminals. Its main functions include inputting and managing educational information, automatically generating educational resources, managing student evaluation data, sharing information with parents, and providing an integrated management system aimed at supporting education throughout the community.

[0319] The server aggregates educational information using Google® Firebase and performs data analysis using TensorFlow. Based on the input educational information, the server automatically generates educational resources and transmits the results to the terminal, creating a system that educators can easily review and use.

[0320] The terminal is operated by the educator, collecting student evaluation data and transmitting it to the server in real time. The student evaluation data is stored in a secure virtual environment, and learning trends are visualized through appropriate processing, presented in a format easily understandable to the educator. Furthermore, information for parents is automatically organized and communicated based on pre-configured criteria.

[0321] As a concrete example, in the event of a specific event held in a region, this system can contribute to the realization of efficient education while reducing the burden on educational settings by creating and providing educational resources related to the event in advance to educators at each school.

[0322] An example of a prompt for a generative AI model would be, "Please suggest educational resources for efficiently sharing relevant information in a specific event." This would likely yield output tailored to specific needs.

[0323] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0324] Step 1:

[0325] Users input educational information using their devices. This includes data on lesson topics, reference materials, and teaching materials to be used. The entered information is sent from the device to the server and stored in Firebase.

[0326] Step 2:

[0327] The server automatically generates educational resources using a generative AI model based on the received educational information. Specifically, it processes the data using TensorFlow, searches for relevant teaching materials in a database, and outputs them as slides and handouts.

[0328] Step 3:

[0329] The generated educational resources are sent from the server to the terminal, making them available for user review. Users can view this information on their terminal and distribute it as printed or electronic data as needed.

[0330] Step 4:

[0331] The user enters student evaluation data into their device. This evaluation data includes test results and records of class participation, and is sent from the device to the server.

[0332] Step 5:

[0333] The server receives student evaluation data and processes it in real time. The data is stored in a secure virtual environment, and the evaluation data is analyzed through computational processing to generate graphs and charts that visualize learning trends.

[0334] Step 6:

[0335] The generated visualization data of learning trends is sent from the server to the terminal, allowing the user to check each student's learning progress and use it to consider teaching methods.

[0336] Step 7:

[0337] The server automatically prepares information for parents based on configured conditions and sends it via email or a dedicated application. This includes updates on student progress and notifications of important school events.

[0338] Step 8:

[0339] For community-wide events, the server generates necessary educational resources in advance and provides relevant information to each terminal. This information is effectively utilized throughout the community to enhance educational support.

[0340] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0341] This invention combines an emotion engine with a system that supports various tasks faced by teachers in educational settings to provide more effective support. The system consists of a server, terminals, and an emotion engine, and is designed to enable teachers to conduct educational activities efficiently.

[0342] The user first uses a terminal to input information about the lesson theme and curriculum. The server receives this information and selects relevant teaching materials from its database. Then, it automatically generates teaching materials based on the selected information and sends the generated materials to the terminal. This allows the user to immediately use the teaching materials they need for their lesson.

[0343] Furthermore, when users input student grades, the server aggregates the data, analyzes the grades, and creates graphs. This information is provided to the terminal, allowing users to visualize the students' level of understanding. The emotion engine also analyzes the user's voice and facial expressions to recognize their emotional state. This allows the server to detect the stress and satisfaction the user feels during class, and to receive and process this feedback.

[0344] For example, if the emotion engine detects that a user is stressed, the server will suggest readjusting the lesson plan to help the user continue their educational activities in a healthy manner. It can also dynamically change the content of the learning materials based on the user's emotional state. This further improves the quality of education.

[0345] By utilizing the emotion engine in this invention, users can receive not only simple preparation of teaching materials and management of grades, but also advanced educational support that responds to their individual emotional states. This system reduces the burden on users and enables more effective and humane education in educational settings.

[0346] The following describes the processing flow.

[0347] Step 1:

[0348] Users input lesson topics, grade levels, and textbook information through their devices. This provides the system with the necessary educational material data.

[0349] Step 2:

[0350] The server receives information entered from the terminal, searches the database, and selects the appropriate educational materials. Identifying materials that align with the curriculum is crucial.

[0351] Step 3:

[0352] The server automatically generates slides and handouts for lessons using the selected materials. It applies templates to create visually meaningful teaching materials.

[0353] Step 4:

[0354] The server sends the generated learning materials to the terminal and provides an interface for the user to review the content and edit it as needed.

[0355] Step 5:

[0356] Users use their devices to input student test results and learning performance data. This allows evaluation information to be stored in a database.

[0357] Step 6:

[0358] The terminal sends the entered performance data to the server, which then statistically analyzes the data. The results are organized in the form of average scores, comprehension levels, and so on.

[0359] Step 7:

[0360] The server visualizes the analysis results in the form of graphs and tables and provides them to the terminal. Users can then use this information to understand learning trends and incorporate them into their instruction.

[0361] Step 8:

[0362] The server receives user voice and facial expression data via an emotion engine and analyzes their emotional state. It then generates feedback based on stress levels and concentration levels.

[0363] Step 9:

[0364] Based on the emotion engine's analysis of the user's emotions, the server suggests adjustments to the lesson content. This includes changing the difficulty level of the teaching materials and adjusting the pace of the lesson.

[0365] Step 10:

[0366] To reduce user stress, the server suggests activities for relaxation and a change of pace, supporting users in engaging in educational activities in a healthy manner.

[0367] (Example 2)

[0368] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0369] To reduce the workload of teachers in educational settings and provide more effective and individualized education, efficient preparation of teaching materials, performance management, analysis of learning progress, and adjustment of teaching methods based on these analyses are essential. Furthermore, a function is needed to address teachers' emotional states and dynamically adjust lesson plans. A system is required that can meet these needs while ensuring safe and efficient work processes.

[0370] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0371] In this invention, the server includes means for inputting educational content, means for automatically generating teaching materials based on the input content, and means for inputting and saving learner performance data. This enables improved work efficiency for teachers and advanced educational support, as well as flexible responses to the needs of individual learners and teachers.

[0372] "Educational content" refers to teaching materials and resources used in educational activities, and is a collection of information used by teachers for educational purposes.

[0373] "Terminal" refers to an information processing device operated by a user, and specifically includes devices such as personal computers and tablets.

[0374] "Learner" refers to anyone receiving education in the educational process, including students.

[0375] "Performance data" refers to information that records learners' learning outcomes, including test results and evaluations.

[0376] The "Internet" refers to an information network connected via public communication networks, enabling information sharing and communication among users.

[0377] "Curriculum" refers to a standardized educational program within an educational institution, and is a system of learning content provided as a curriculum.

[0378] A "schedule" refers to a plan of events and activities to be held within a specific period, and is created to support the efficient progress of educational activities.

[0379] "Emotional state" refers to the user's psychological and sensory state, including psychological changes such as stress and satisfaction.

[0380] The embodiments for carrying out the invention are described below.

[0381] This system is designed to support teachers' work in educational settings and consists of a server, terminals, and an emotion engine. Users input educational information using the terminals, and the system generates teaching materials and manages and analyzes grades via the server. The emotion engine also analyzes the user's emotional state and adjusts educational activities accordingly.

[0382] The server executes computer programs to process the received data. Python and related generative AI models are used for the automatic generation of educational materials. Specific functions include searching for educational materials from a database using Elasticsearch and data analysis using Pandas and Matplotlib. The terminal displays information entered by the user and the received educational materials.

[0383] Users input information related to the lesson theme and curriculum into their terminals, sending data to the server. Based on this information, the server automatically generates teaching materials and sends them to the terminals. This allows users to immediately begin their educational activities.

[0384] Furthermore, by utilizing the emotion engine to analyze the user's emotional state, the server can suggest adjustments to the lesson plan based on that feedback. This allows teachers to conduct educational activities that take their own psychological state into account.

[0385] As a concrete example, when teaching "plant growth" in an elementary school science class, the user can input the lesson plan into the terminal, and the system can automatically generate the relevant teaching materials. An example of a prompt message to the generation AI model would be, "Please generate teaching materials on the topic of 'plant growth' for a 5th-grade elementary school science class. The materials should include illustrations and videos, and should be able to be taught in 20 minutes or less." This allows for the easy preparation of appropriate lesson content.

[0386] This system not only reduces the burden on teachers but also provides innovative educational technologies to improve the quality of education.

[0387] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0388] Step 1:

[0389] Users input lesson topics and curriculum information using their devices. This information includes the lesson objectives, desired learning outcomes, and the format of the materials to be used (text, images, videos, etc.). The entered data is sent to the server.

[0390] Step 2:

[0391] The server searches the database based on the information received from the user and selects relevant educational materials. Specifically, it uses ElasticSearch to search for educational materials in the database and passes the results to the material generation AI model. The input used in this step is the lesson theme and curriculum information provided by the user, and the output is a list of materials required by the material generation AI model.

[0392] Step 3:

[0393] The server automatically generates lesson materials by combining selected materials using an AI model for material generation. The generation process uses programming languages ​​such as Python to process the selected materials with the AI ​​model and generate optimal lesson materials. The input is the material list obtained in step 2, and the output is the completed lesson material.

[0394] Step 4:

[0395] The server sends the completed teaching materials to the terminal. The user can then review the received materials on the terminal and proceed with preparing for the lesson. The terminal displays the received materials to the user and downloads them as needed.

[0396] Step 5:

[0397] Users input student performance data collected during class into their terminals. This includes test results and project evaluations. The entered performance data is then sent to the server.

[0398] Step 6:

[0399] The server performs data analysis based on the received performance data. The analysis uses Python's Pandas and Matplotlib libraries to aggregate and visualize the data. The input is the performance data entered by the user, and the output is a visualized representation of the learner's trends.

[0400] Step 7:

[0401] The server operates an emotion engine to analyze the user's voice and facial expressions. User emotion data (such as stress levels and satisfaction) is input, and feedback is generated based on the analysis results. Speech recognition software and image processing libraries are used for emotion analysis.

[0402] Step 8:

[0403] Based on the analysis results, the server makes suggestions to the user regarding adjustments to the lesson plan. For example, if the user is experiencing high stress levels, it may suggest slowing down the pace of the lesson. This allows the user to create an optimal learning environment.

[0404] (Application Example 2)

[0405] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0406] In modern education, there is a need for individualized support tailored to each student's learning style and emotional state. In particular, when learners are experiencing emotional stress, or conversely, are highly engaged and excited, flexible adjustments to teaching materials and methods are essential. However, traditional educational support systems struggle to provide this emotional flexibility, placing a significant burden on educators. Therefore, there is a need for an educational support system that can detect students' emotional states and provide appropriate educational activities.

[0407] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0408] In this invention, the server includes means for inputting educational materials, means for detecting the learner's emotional state using emotion analysis technology and dynamically changing the content of the materials, and means for making suggestions for adjusting educational activities based on the emotional state. This makes it possible for educators to easily provide appropriate educational activities that correspond to the learner's emotional state.

[0409] "Means for inputting educational materials" refers to devices or methods for incorporating information and data necessary for education into a system.

[0410] "Means for automatically generating educational materials based on input materials" refers to a device or method that automatically creates educational materials for learners based on input educational information.

[0411] "Means for displaying or distributing generated teaching materials" refers to devices or methods for showing, electronically or physically, the created teaching materials to learners.

[0412] "Means for inputting and saving student performance data" refers to a device or method for inputting information regarding students' learning outcomes into a system and saving it for later use.

[0413] "Means for analyzing stored performance data and visualizing learning trends" refers to a device or method that analyzes recorded performance information and processes it into a format that can be easily understood at a glance.

[0414] "Means for automatically preparing and transmitting information to parents" refers to devices or methods that automatically collect educational information and provide it to parents.

[0415] "Means for managing schedules related to educational activities and supporting efficient time management" refers to devices or methods that organize educational schedules and assist in effective time allocation.

[0416] "Means of proposing instructional approaches tailored to the learning situation of individual students" refers to a device or method that presents the optimal instructional method based on each student's learning progress.

[0417] "Means for detecting a learner's emotional state using emotion analysis technology and dynamically changing the content of learning materials" refers to a device or method that analyzes a learner's emotions and adjusts the content of learning materials according to the situation.

[0418] "Means for making suggestions to adjust educational activities based on emotional state" refers to a device or method that provides advice for adjusting educational methods in accordance with the learner's emotions.

[0419] To realize this invention, a system specifically designed for educational settings will be used. This system consists of three main elements: a server, a terminal, and a user. Each element plays a specific role, thereby achieving effective educational support.

[0420] The server accepts input for educational materials and automatically generates teaching materials based on the input themes using a generative AI model. This generation process creates materials optimized to fit the educational curriculum. The server then sends the generated materials to devices, allowing users to view or distribute them. Furthermore, the server aggregates student performance data, securely stores it in a cloud environment, and provides real-time visualization of this data.

[0421] The terminal primarily functions as a user interface. Educators, as users, can review and show generated learning materials to learners through this terminal. The terminal also incorporates sentiment analysis technology, detecting learners' emotional states through audio and video and sending this information to the server. This allows the content of the learning materials to be dynamically adjusted according to the situation.

[0422] The user, acting as a teacher or educational support staff, operates the entire system. The user inputs educational materials into the system and manages subsequent educational activities. For example, if the user inputs student grades, the system analyzes and visualizes learning trends based on that data. Furthermore, if the server detects that a learner is experiencing stress, the user can receive suggestions from the server and adjust the lesson plan accordingly.

[0423] As a concrete example, when a user inputs the theme "basic arithmetic," the generative AI model generates arithmetic learning materials based on that theme, and if the learner is experiencing stress, it suggests slowing down the learning pace. This process can be achieved by using the following prompt example: "Generate educational materials for children based on the input theme. Also, adjust according to the emotional state, and slow down the learning speed if the learner is experiencing stress."

[0424] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0425] Step 1:

[0426] Users input educational materials using a terminal. This input includes information about the lesson theme and the curriculum it covers. The terminal prepares the data by sending this information to the server in digital format.

[0427] Step 2:

[0428] The server automatically generates educational materials using a generative AI model based on the received educational materials. Optimized materials are created based on the input theme. The generative AI model algorithmically processes the materials corresponding to each subject and outputs them in various formats (e.g., PDF or video materials).

[0429] Step 3:

[0430] The server sends the generated learning materials to the terminal, which then displays them to the user. The user can review the displayed materials and make modifications as needed. The materials are then distributed to learners in an appropriate format.

[0431] Step 4:

[0432] Users input student performance data using their devices. This performance information is based on the results of regular tests and in-class activities, and is transferred from the device to the server.

[0433] Step 5:

[0434] The server analyzes stored performance data and statistically visualizes learning trends. Specifically, it securely stores data in a cloud environment, performs statistical analysis and graph creation, and generates performance trends in real time.

[0435] Step 6:

[0436] The emotion analysis technology installed on the device collects emotional data from the learner's voice and facial expressions and sends it to a server. This data is used as input to determine whether the learner is experiencing stress.

[0437] Step 7:

[0438] The server analyzes the received emotional data and suggests changes to teaching materials or adjustments to the lesson plan based on its content. For example, it might notify the user of adjustments such as, "The generative AI model suggests slowing down the learning speed if stress levels are high."

[0439] Step 8:

[0440] Users receive suggestions from the server and adjust educational activities as needed. This allows for flexible responses to learners' emotional states and provides an effective learning experience.

[0441] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0442] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0443] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0444] [Third Embodiment]

[0445] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0446] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0447] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0448] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0449] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0450] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0451] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0452] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0453] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0454] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0455] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0456] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0457] This invention is a system designed to streamline the diverse tasks that teachers perform in the educational setting. This system consists of a server and terminals, and provides various forms of support to teachers (users). Its functions are described below.

[0458] When users prepare teaching materials for a class, they use a terminal to input information about the class theme and the textbooks to be used. Based on this information, the server selects materials from its database that are consistent with the curriculum and automatically generates slides and handouts. The results are sent to the terminal, where the user can review the details and use them in class.

[0459] For grade management, users input students' test results using their devices. This data is sent to a server, where statistical methods are used to analyze and visualize grades. The server then sends reports to the devices indicating each student's level of understanding and the overall class trend, which users can utilize when providing guidance to students.

[0460] Furthermore, regarding communication with parents, the server automatically organizes student learning progress and information from the school, and sends emails to parents according to pre-configured conditions. This significantly reduces manual work by users and enables effective communication.

[0461] Furthermore, through the schedule management function, users input their class and administrative schedules, allowing the server to oversee the entire schedule and support efficient time management. The server detects overlaps and inconsistencies and suggests the optimal schedule, allowing users to focus on their educational activities with peace of mind.

[0462] In the individualized tutoring plan proposal, the server generates the optimal teaching approach based on an analysis of each student's academic performance and provides it to the user. The user can then use this as a reference to provide individualized support to each student.

[0463] Thus, this system significantly reduces the workload of teachers and contributes to improving the quality of education.

[0464] The following describes the processing flow.

[0465] Step 1:

[0466] Users input lesson topics, grade levels, and textbook information using their devices. This provides the system with the necessary basic data for teaching materials.

[0467] Step 2:

[0468] The server receives information entered from the terminal, searches the database for relevant teaching materials, and verifies that the information matches the curriculum before selecting the appropriate educational materials.

[0469] Step 3:

[0470] The server automatically generates slides and printouts based on the selected information. Templates are used to design teaching materials in a visually consistent format.

[0471] Step 4:

[0472] The server sends the generated learning materials to the user's device, allowing them to review and edit them. Users can request revisions to the content as needed.

[0473] Step 5:

[0474] Users enter students' test results using a terminal. This records the students' performance data in the system.

[0475] Step 6:

[0476] The terminal sends the entered performance data to the server. The server uses this data to perform statistical analysis and calculate the average score and the trend in understanding.

[0477] Step 7:

[0478] The server summarizes the analysis results in graphs and tables and sends them to the terminal in a visualized format. The user then uses this data to provide feedback to students and adjust lessons.

[0479] Step 8:

[0480] The server automatically prepares and sends emails to parents containing information about their child's learning progress and other important matters. The timing and content of these emails are adjusted according to the settings.

[0481] Step 9:

[0482] Users input their class and school work schedules using their terminals, and the server receives this information and manages the schedule. By efficiently coordinating schedules, it supports users in managing their time.

[0483] Step 10:

[0484] The server analyzes each student's academic performance data and proposes individualized tutoring plans based on the results. Users can then utilize these suggestions to provide personalized instruction to their students.

[0485] (Example 1)

[0486] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0487] In educational settings, teachers need to efficiently perform a wide range of tasks. However, tasks such as preparing teaching materials, managing grades, communicating with parents, managing schedules, and developing individualized instruction plans are complex and time-consuming, potentially negatively impacting the quality of education. This invention aims to alleviate the workload of teachers and improve the quality of education.

[0488] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0489] In this invention, the server includes means for inputting educational themes and related information, means for selecting educational resources from a database based on the input information and automatically generating teaching materials using a generation AI model, and means for transmitting and displaying the generated teaching materials on a terminal. This enables the streamlining of teachers' work processes and provides high-quality educational support.

[0490] An "educational theme" is a concept that indicates the content or focus to be taught in a particular class or lecture within an educational activity.

[0491] "Related information" refers to materials and data linked to the educational theme, as well as knowledge related to the textbooks used and the desired educational outcomes.

[0492] "Educational resources" refer to teaching materials, documents, datasets, and other materials available for conducting education.

[0493] A "database" refers to a system or collection of information and data used to efficiently store, retrieve, and manage large amounts of information and data. In this context, it serves the purpose of storing educational resources.

[0494] A "generative AI model" refers to an artificial intelligence model used to automatically generate content and data based on input information.

[0495] "Educational materials" refer to documents, materials, slides, multimedia content, etc., used for educational purposes, and are learning materials provided to learners in education.

[0496] "Evaluation data" refers to numerical data and information used to assess the learning outcomes and academic abilities of students or course participants.

[0497] An "environment capable of protecting information" refers to a system or infrastructure in which data and information are securely managed and protected from unauthorized external access.

[0498] This invention is a system designed to streamline the work of teachers in educational settings, and consists of a server and terminals. This system covers everything from inputting educational themes to creating teaching materials using a generative AI model, managing grades, providing information to parents, managing schedules, and formulating individualized instruction plans.

[0499] First, the user uses a terminal to input the lesson topic and related information. The educational database contains a wide range of educational resources, which the server then accesses. For example, if the user inputs "I want to teach the history of World War II," the server selects relevant educational resources. Here, a generative AI model is used to automatically generate educational slides and materials that meet the user's requirements. In this generation process, an example of a prompt might be "List the major events of World War II and create educational slides."

[0500] After the teaching materials are generated, the server sends them to the terminal for the user to view and edit. After reviewing the materials on the terminal, the user utilizes them in actual lessons. For grade management, the user inputs student evaluation data into the terminal, which the server receives. This evaluation data is managed in a secure environment, and the server performs statistical analysis based on it. The results are visualized on the terminal, allowing the user to use them to improve student guidance.

[0501] Furthermore, the server has a function that automatically sends information to parents according to set conditions, based on organized student learning status and school information. This significantly reduces manual work by users and promotes smooth communication with parents. In addition, regarding schedule management, users input schedules related to educational activities into their terminals, and the server organizes them, supporting efficient time management.

[0502] Thus, this system aims to significantly reduce the workload of teachers and improve the quality of education.

[0503] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0504] Step 1:

[0505] The user enters an educational theme and related information into their device. This input includes themes and textbooks to be used, depending on the objectives of the lesson. Specifically, the user enters "History of World War II" into a form on the device and presses the submit button. The entered information is then sent from the device to the server.

[0506] Step 2:

[0507] The server receives the input data and selects relevant resources by referring to a database of educational resources. The server searches the database based on the keyword "World War II" and extracts suitable educational data. At this stage, the server starts processing the generative AI model using a prompt (e.g., "List the main events of World War II and create educational slides").

[0508] Step 3:

[0509] The server utilizes an AI model to automatically generate educational slides. This process automatically generates slide images and text based on the teaching material data extracted in the previous step. The generated slides are then processed into PDF format on the server. The server then sends these processed materials to the user's device.

[0510] Step 4:

[0511] The user reviews the learning materials received on their device. They open the PDF slides on their device, view the content, and make any necessary edits. Once editing is complete, the user saves the materials for use in class.

[0512] Step 5:

[0513] The user inputs student evaluation data into their device. Specifically, this involves entering each student's score and comments into a spreadsheet and uploading it to the server. This evaluation data is then sent to the server.

[0514] Step 6:

[0515] The server securely stores the received evaluation data and performs analysis using statistical methods. The server uses a computational model to calculate average scores, performance distributions, and other metrics, and visualizes the results as graphs and charts. This visualized data is then sent to the terminal after analysis.

[0516] Step 7:

[0517] Users can review the analysis results on their devices and use them to inform their educational policies and future lesson plans. Based on the finalized results, they can take necessary actions and adjust their teaching strategies.

[0518] (Application Example 1)

[0519] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0520] In today's educational environment, the workload of teachers and educational institutions is increasing due to the wide range of tasks they must perform. Creating educational materials, managing student evaluation data, communicating with parents, and scheduling learning activities are all challenging to perform efficiently. Furthermore, integrated management tools are needed to realize educational support throughout the community. Overcoming these challenges and providing more effective educational support is essential.

[0521] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0522] In this invention, the server includes means for inputting educational information, means for automatically generating educational resources based on the input information, and means for proposing teaching methods tailored to the learning progress of individual students. This reduces the workload of educators and enables efficient educational support throughout the community.

[0523] "Educational information" is a general term for data and materials used by teachers and educational institutions to create teaching materials and lesson plans.

[0524] "Educational resources" refer to physical or digital materials such as teaching materials, handouts, and slides used in the course of education.

[0525] "Participant evaluation data" refers to data that shows the results obtained by learners through tests and evaluations, and includes grades and feedback information.

[0526] "Information for parents" refers to announcements regarding the student's learning progress and school activities, and is intended to facilitate communication with parents.

[0527] "Educational support across the entire community" refers to a system that efficiently supports educational activities throughout a broad community, without relying on specific educational institutions.

[0528] "Integrated management means" refers to systems and methods for centrally managing multiple education-related activities, aiming to improve the efficiency of the educational process.

[0529] The system for realizing this invention is centered around a server and terminals. Its main functions include inputting and managing educational information, automatically generating educational resources, managing student evaluation data, sharing information with parents, and providing an integrated management system aimed at supporting education throughout the community.

[0530] The server aggregates educational information using Google Firebase and performs data analysis using TensorFlow. Based on the input educational information, the server automatically generates educational resources and transmits the results to the terminal, creating a system that educators can easily review and use.

[0531] The terminal is operated by the educator, collecting student evaluation data and transmitting it to the server in real time. The student evaluation data is stored in a secure virtual environment, and learning trends are visualized through appropriate processing, presented in a format easily understandable to the educator. Furthermore, information for parents is automatically organized and communicated based on pre-configured criteria.

[0532] As a concrete example, in the event of a specific event held in a region, this system can contribute to the realization of efficient education while reducing the burden on educational settings by creating and providing educational resources related to the event in advance to educators at each school.

[0533] An example of a prompt for a generative AI model would be, "Please suggest educational resources for efficiently sharing relevant information in a specific event." This would likely yield output tailored to specific needs.

[0534] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0535] Step 1:

[0536] Users input educational information using their devices. This includes data on lesson topics, reference materials, and teaching materials to be used. The entered information is sent from the device to the server and stored in Firebase.

[0537] Step 2:

[0538] The server automatically generates educational resources using a generative AI model based on the received educational information. Specifically, it processes the data using TensorFlow, searches for relevant teaching materials in a database, and outputs them as slides and handouts.

[0539] Step 3:

[0540] The generated educational resources are sent from the server to the terminal, making them available for user review. Users can view this information on their terminal and distribute it as printed or electronic data as needed.

[0541] Step 4:

[0542] The user enters student evaluation data into their device. This evaluation data includes test results and records of class participation, and is sent from the device to the server.

[0543] Step 5:

[0544] The server receives student evaluation data and processes it in real time. The data is stored in a secure virtual environment, and the evaluation data is analyzed through computational processing to generate graphs and charts that visualize learning trends.

[0545] Step 6:

[0546] The generated visualization data of learning trends is sent from the server to the terminal, allowing the user to check each student's learning progress and use it to consider teaching methods.

[0547] Step 7:

[0548] The server automatically prepares information for parents based on configured conditions and sends it via email or a dedicated application. This includes updates on student progress and notifications of important school events.

[0549] Step 8:

[0550] For community-wide events, the server generates necessary educational resources in advance and provides relevant information to each terminal. This information is effectively utilized throughout the community to enhance educational support.

[0551] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0552] This invention combines an emotion engine with a system that supports various tasks faced by teachers in educational settings to provide more effective support. The system consists of a server, terminals, and an emotion engine, and is designed to enable teachers to conduct educational activities efficiently.

[0553] The user first uses a terminal to input information about the lesson theme and curriculum. The server receives this information and selects relevant teaching materials from its database. Then, it automatically generates teaching materials based on the selected information and sends the generated materials to the terminal. This allows the user to immediately use the teaching materials they need for their lesson.

[0554] Furthermore, when users input student grades, the server aggregates the data, analyzes the grades, and creates graphs. This information is provided to the terminal, allowing users to visualize the students' level of understanding. The emotion engine also analyzes the user's voice and facial expressions to recognize their emotional state. This allows the server to detect the stress and satisfaction the user feels during class, and to receive and process this feedback.

[0555] For example, if the emotion engine detects that a user is stressed, the server will suggest readjusting the lesson plan to help the user continue their educational activities in a healthy manner. It can also dynamically change the content of the learning materials based on the user's emotional state. This further improves the quality of education.

[0556] By utilizing the emotion engine in this invention, users can receive not only simple preparation of teaching materials and management of grades, but also advanced educational support that responds to their individual emotional states. This system reduces the burden on users and enables more effective and humane education in educational settings.

[0557] The following describes the processing flow.

[0558] Step 1:

[0559] Users input lesson topics, grade levels, and textbook information through their devices. This provides the system with the necessary educational material data.

[0560] Step 2:

[0561] The server receives information entered from the terminal, searches the database, and selects the appropriate educational materials. Identifying materials that align with the curriculum is crucial.

[0562] Step 3:

[0563] The server automatically generates slides and handouts for lessons using the selected materials. It applies templates to create visually meaningful teaching materials.

[0564] Step 4:

[0565] The server sends the generated learning materials to the terminal and provides an interface for the user to review the content and edit it as needed.

[0566] Step 5:

[0567] Users use their devices to input student test results and learning performance data. This allows evaluation information to be stored in a database.

[0568] Step 6:

[0569] The terminal sends the entered performance data to the server, which then statistically analyzes the data. The results are organized in the form of average scores, comprehension levels, and so on.

[0570] Step 7:

[0571] The server visualizes the analysis results in the form of graphs and tables and provides them to the terminal. Users can then use this information to understand learning trends and incorporate them into their instruction.

[0572] Step 8:

[0573] The server receives user voice and facial expression data via an emotion engine and analyzes their emotional state. It then generates feedback based on stress levels and concentration levels.

[0574] Step 9:

[0575] Based on the emotion engine's analysis of the user's emotions, the server suggests adjustments to the lesson content. This includes changing the difficulty level of the teaching materials and adjusting the pace of the lesson.

[0576] Step 10:

[0577] To reduce user stress, the server suggests activities for relaxation and a change of pace, supporting users in engaging in educational activities in a healthy manner.

[0578] (Example 2)

[0579] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0580] To reduce the workload of teachers in educational settings and provide more effective and individualized education, efficient preparation of teaching materials, performance management, analysis of learning progress, and adjustment of teaching methods based on these analyses are essential. Furthermore, a function is needed to address teachers' emotional states and dynamically adjust lesson plans. A system is required that can meet these needs while ensuring safe and efficient work processes.

[0581] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0582] In this invention, the server includes means for inputting educational content, means for automatically generating teaching materials based on the input content, and means for inputting and saving learner performance data. This enables improved work efficiency for teachers and advanced educational support, as well as flexible responses to the needs of individual learners and teachers.

[0583] "Educational content" refers to teaching materials and resources used in educational activities, and is a collection of information used by teachers for educational purposes.

[0584] "Terminal" refers to an information processing device operated by a user, and specifically includes devices such as personal computers and tablets.

[0585] "Learner" refers to anyone receiving education in the educational process, including students.

[0586] "Performance data" refers to information that records learners' learning outcomes, including test results and evaluations.

[0587] The "Internet" refers to an information network connected via public communication networks, enabling information sharing and communication among users.

[0588] "Curriculum" refers to a standardized educational program within an educational institution, and is a system of learning content provided as a curriculum.

[0589] A "schedule" refers to a plan of events and activities to be held within a specific period, and is created to support the efficient progress of educational activities.

[0590] "Emotional state" refers to the user's psychological and sensory state, including psychological changes such as stress and satisfaction.

[0591] The embodiments for carrying out the invention are described below.

[0592] This system is designed to support teachers' work in educational settings and consists of a server, terminals, and an emotion engine. Users input educational information using the terminals, and the system generates teaching materials and manages and analyzes grades via the server. The emotion engine also analyzes the user's emotional state and adjusts educational activities accordingly.

[0593] The server executes computer programs to process the received data. Python and related generative AI models are used for the automatic generation of educational materials. Specific functions include searching for educational materials from a database using Elasticsearch and data analysis using Pandas and Matplotlib. The terminal displays information entered by the user and the received educational materials.

[0594] Users input information related to the lesson theme and curriculum into their terminals, sending data to the server. Based on this information, the server automatically generates teaching materials and sends them to the terminals. This allows users to immediately begin their educational activities.

[0595] Furthermore, by utilizing the emotion engine to analyze the user's emotional state, the server can suggest adjustments to the lesson plan based on that feedback. This allows teachers to conduct educational activities that take their own psychological state into account.

[0596] As a concrete example, when teaching "plant growth" in an elementary school science class, the user can input the lesson plan into the terminal, and the system can automatically generate the relevant teaching materials. An example of a prompt message to the generation AI model would be, "Please generate teaching materials on the topic of 'plant growth' for a 5th-grade elementary school science class. The materials should include illustrations and videos, and should be able to be taught in 20 minutes or less." This allows for the easy preparation of appropriate lesson content.

[0597] This system not only reduces the burden on teachers but also provides innovative educational technologies to improve the quality of education.

[0598] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0599] Step 1:

[0600] Users input lesson topics and curriculum information using their devices. This information includes the lesson objectives, desired learning outcomes, and the format of the materials to be used (text, images, videos, etc.). The entered data is sent to the server.

[0601] Step 2:

[0602] The server searches the database based on the information received from the user and selects relevant educational materials. Specifically, it uses ElasticSearch to search for educational materials in the database and passes the results to the material generation AI model. The input used in this step is the lesson theme and curriculum information provided by the user, and the output is a list of materials required by the material generation AI model.

[0603] Step 3:

[0604] The server automatically generates lesson materials by combining selected materials using an AI model for material generation. The generation process uses programming languages ​​such as Python to process the selected materials with the AI ​​model and generate optimal lesson materials. The input is the material list obtained in step 2, and the output is the completed lesson material.

[0605] Step 4:

[0606] The server sends the completed teaching materials to the terminal. The user can then review the received materials on the terminal and proceed with preparing for the lesson. The terminal displays the received materials to the user and downloads them as needed.

[0607] Step 5:

[0608] Users input student performance data collected during class into their terminals. This includes test results and project evaluations. The entered performance data is then sent to the server.

[0609] Step 6:

[0610] The server performs data analysis based on the received performance data. The analysis uses Python's Pandas and Matplotlib libraries to aggregate and visualize the data. The input is the performance data entered by the user, and the output is a visualized representation of the learner's trends.

[0611] Step 7:

[0612] The server operates an emotion engine to analyze the user's voice and facial expressions. User emotion data (such as stress levels and satisfaction) is input, and feedback is generated based on the analysis results. Speech recognition software and image processing libraries are used for emotion analysis.

[0613] Step 8:

[0614] Based on the analysis results, the server makes suggestions to the user regarding adjustments to the lesson plan. For example, if the user is experiencing high stress levels, it may suggest slowing down the pace of the lesson. This allows the user to create an optimal learning environment.

[0615] (Application Example 2)

[0616] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0617] In modern education, there is a need for individualized support tailored to each student's learning style and emotional state. In particular, when learners are experiencing emotional stress, or conversely, are highly engaged and excited, flexible adjustments to teaching materials and methods are essential. However, traditional educational support systems struggle to provide this emotional flexibility, placing a significant burden on educators. Therefore, there is a need for an educational support system that can detect students' emotional states and provide appropriate educational activities.

[0618] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0619] In this invention, the server includes means for inputting educational materials, means for detecting the learner's emotional state using emotion analysis technology and dynamically changing the content of the materials, and means for making suggestions for adjusting educational activities based on the emotional state. This makes it possible for educators to easily provide appropriate educational activities that correspond to the learner's emotional state.

[0620] "Means for inputting educational materials" refers to devices or methods for incorporating information and data necessary for education into a system.

[0621] "Means for automatically generating educational materials based on input materials" refers to a device or method that automatically creates educational materials for learners based on input educational information.

[0622] "Means for displaying or distributing generated teaching materials" refers to devices or methods for showing, electronically or physically, the created teaching materials to learners.

[0623] "Means for inputting and saving student performance data" refers to a device or method for inputting information regarding students' learning outcomes into a system and saving it for later use.

[0624] "Means for analyzing stored performance data and visualizing learning trends" refers to a device or method that analyzes recorded performance information and processes it into a format that can be easily understood at a glance.

[0625] "Means for automatically preparing and transmitting information to parents" refers to devices or methods that automatically collect educational information and provide it to parents.

[0626] "Means for managing schedules related to educational activities and supporting efficient time management" refers to devices or methods that organize educational schedules and assist in effective time allocation.

[0627] "Means of proposing instructional approaches tailored to the learning situation of individual students" refers to a device or method that presents the optimal instructional method based on each student's learning progress.

[0628] "Means for detecting a learner's emotional state using emotion analysis technology and dynamically changing the content of learning materials" refers to a device or method that analyzes a learner's emotions and adjusts the content of learning materials according to the situation.

[0629] "Means for making suggestions to adjust educational activities based on emotional state" refers to a device or method that provides advice for adjusting educational methods in accordance with the learner's emotions.

[0630] To realize this invention, a system specifically designed for educational settings will be used. This system consists of three main elements: a server, a terminal, and a user. Each element plays a specific role, thereby achieving effective educational support.

[0631] The server accepts input for educational materials and automatically generates teaching materials based on the input themes using a generative AI model. This generation process creates materials optimized to fit the educational curriculum. The server then sends the generated materials to devices, allowing users to view or distribute them. Furthermore, the server aggregates student performance data, securely stores it in a cloud environment, and provides real-time visualization of this data.

[0632] The terminal primarily functions as a user interface. Educators, as users, can review and show generated learning materials to learners through this terminal. The terminal also incorporates sentiment analysis technology, detecting learners' emotional states through audio and video and sending this information to the server. This allows the content of the learning materials to be dynamically adjusted according to the situation.

[0633] The user, acting as a teacher or educational support staff, operates the entire system. The user inputs educational materials into the system and manages subsequent educational activities. For example, if the user inputs student grades, the system analyzes and visualizes learning trends based on that data. Furthermore, if the server detects that a learner is experiencing stress, the user can receive suggestions from the server and adjust the lesson plan accordingly.

[0634] As a concrete example, when a user inputs the theme "basic arithmetic," the generative AI model generates arithmetic learning materials based on that theme, and if the learner is experiencing stress, it suggests slowing down the learning pace. This process can be achieved by using the following prompt example: "Generate educational materials for children based on the input theme. Also, adjust according to the emotional state, and slow down the learning speed if the learner is experiencing stress."

[0635] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0636] Step 1:

[0637] Users input educational materials using a terminal. This input includes information about the lesson theme and the curriculum it covers. The terminal prepares the data by sending this information to the server in digital format.

[0638] Step 2:

[0639] The server automatically generates educational materials using a generative AI model based on the received educational materials. Optimized materials are created based on the input theme. The generative AI model algorithmically processes the materials corresponding to each subject and outputs them in various formats (e.g., PDF or video materials).

[0640] Step 3:

[0641] The server sends the generated learning materials to the terminal, which then displays them to the user. The user can review the displayed materials and make modifications as needed. The materials are then distributed to learners in an appropriate format.

[0642] Step 4:

[0643] Users input student performance data using their devices. This performance information is based on the results of regular tests and in-class activities, and is transferred from the device to the server.

[0644] Step 5:

[0645] The server analyzes stored performance data and statistically visualizes learning trends. Specifically, it securely stores data in a cloud environment, performs statistical analysis and graph creation, and generates performance trends in real time.

[0646] Step 6:

[0647] The emotion analysis technology installed on the device collects emotional data from the learner's voice and facial expressions and sends it to a server. This data is used as input to determine whether the learner is experiencing stress.

[0648] Step 7:

[0649] The server analyzes the received emotional data and suggests changes to teaching materials or adjustments to the lesson plan based on its content. For example, it might notify the user of adjustments such as, "The generative AI model suggests slowing down the learning speed if stress levels are high."

[0650] Step 8:

[0651] Users receive suggestions from the server and adjust educational activities as needed. This allows for flexible responses to learners' emotional states and provides an effective learning experience.

[0652] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0653] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0654] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0655] [Fourth Embodiment]

[0656] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0657] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0658] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0659] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0660] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0661] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0662] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0663] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0664] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0665] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0666] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0667] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0668] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0669] This invention is a system designed to streamline the diverse tasks that teachers perform in the educational setting. This system consists of a server and terminals, and provides various forms of support to teachers (users). Its functions are described below.

[0670] When users prepare teaching materials for a class, they use a terminal to input information about the class theme and the textbooks to be used. Based on this information, the server selects materials from its database that are consistent with the curriculum and automatically generates slides and handouts. The results are sent to the terminal, where the user can review the details and use them in class.

[0671] For grade management, users input students' test results using their devices. This data is sent to a server, where statistical methods are used to analyze and visualize grades. The server then sends reports to the devices indicating each student's level of understanding and the overall class trend, which users can utilize when providing guidance to students.

[0672] Furthermore, regarding communication with parents, the server automatically organizes student learning progress and information from the school, and sends emails to parents according to pre-configured conditions. This significantly reduces manual work by users and enables effective communication.

[0673] Furthermore, through the schedule management function, users input their class and administrative schedules, allowing the server to oversee the entire schedule and support efficient time management. The server detects overlaps and inconsistencies and suggests the optimal schedule, allowing users to focus on their educational activities with peace of mind.

[0674] In the individualized tutoring plan proposal, the server generates the optimal teaching approach based on an analysis of each student's academic performance and provides it to the user. The user can then use this as a reference to provide individualized support to each student.

[0675] Thus, this system significantly reduces the workload of teachers and contributes to improving the quality of education.

[0676] The following describes the processing flow.

[0677] Step 1:

[0678] Users input lesson topics, grade levels, and textbook information using their devices. This provides the system with the necessary basic data for teaching materials.

[0679] Step 2:

[0680] The server receives information entered from the terminal, searches the database for relevant teaching materials, and verifies that the information matches the curriculum before selecting the appropriate educational materials.

[0681] Step 3:

[0682] The server automatically generates slides and printouts based on the selected information. Templates are used to design teaching materials in a visually consistent format.

[0683] Step 4:

[0684] The server sends the generated learning materials to the user's device, allowing them to review and edit them. Users can request revisions to the content as needed.

[0685] Step 5:

[0686] Users enter students' test results using a terminal. This records the students' performance data in the system.

[0687] Step 6:

[0688] The terminal sends the entered performance data to the server. The server uses this data to perform statistical analysis and calculate the average score and the trend in understanding.

[0689] Step 7:

[0690] The server summarizes the analysis results in graphs and tables and sends them to the terminal in a visualized format. The user then uses this data to provide feedback to students and adjust lessons.

[0691] Step 8:

[0692] The server automatically prepares and sends emails to parents containing information about their child's learning progress and other important matters. The timing and content of these emails are adjusted according to the settings.

[0693] Step 9:

[0694] Users input their class and school work schedules using their terminals, and the server receives this information and manages the schedule. By efficiently coordinating schedules, it supports users in managing their time.

[0695] Step 10:

[0696] The server analyzes each student's academic performance data and proposes individualized tutoring plans based on the results. Users can then utilize these suggestions to provide personalized instruction to their students.

[0697] (Example 1)

[0698] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0699] In educational settings, teachers need to efficiently perform a wide range of tasks. However, tasks such as preparing teaching materials, managing grades, communicating with parents, managing schedules, and developing individualized instruction plans are complex and time-consuming, potentially negatively impacting the quality of education. This invention aims to alleviate the workload of teachers and improve the quality of education.

[0700] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0701] In this invention, the server includes means for inputting educational themes and related information, means for selecting educational resources from a database based on the input information and automatically generating teaching materials using a generation AI model, and means for transmitting and displaying the generated teaching materials on a terminal. This enables the streamlining of teachers' work processes and provides high-quality educational support.

[0702] An "educational theme" is a concept that indicates the content or focus to be taught in a particular class or lecture within an educational activity.

[0703] "Related information" refers to materials and data linked to the educational theme, as well as knowledge related to the textbooks used and the desired educational outcomes.

[0704] "Educational resources" refer to teaching materials, documents, datasets, and other materials available for conducting education.

[0705] A "database" refers to a system or collection of information and data used to efficiently store, retrieve, and manage large amounts of information and data. In this context, it serves the purpose of storing educational resources.

[0706] A "generative AI model" refers to an artificial intelligence model used to automatically generate content and data based on input information.

[0707] "Educational materials" refer to documents, materials, slides, multimedia content, etc., used for educational purposes, and are learning materials provided to learners in education.

[0708] "Evaluation data" refers to numerical data and information used to assess the learning outcomes and academic abilities of students or course participants.

[0709] An "environment capable of protecting information" refers to a system or infrastructure in which data and information are securely managed and protected from unauthorized external access.

[0710] This invention is a system designed to streamline the work of teachers in educational settings, and consists of a server and terminals. This system covers everything from inputting educational themes to creating teaching materials using a generative AI model, managing grades, providing information to parents, managing schedules, and formulating individualized instruction plans.

[0711] First, the user uses a terminal to input the lesson topic and related information. The educational database contains a wide range of educational resources, which the server then accesses. For example, if the user inputs "I want to teach the history of World War II," the server selects relevant educational resources. Here, a generative AI model is used to automatically generate educational slides and materials that meet the user's requirements. In this generation process, an example of a prompt might be "List the major events of World War II and create educational slides."

[0712] After the teaching materials are generated, the server sends them to the terminal for the user to view and edit. After reviewing the materials on the terminal, the user utilizes them in actual lessons. For grade management, the user inputs student evaluation data into the terminal, which the server receives. This evaluation data is managed in a secure environment, and the server performs statistical analysis based on it. The results are visualized on the terminal, allowing the user to use them to improve student guidance.

[0713] Furthermore, the server has a function that automatically sends information to parents according to set conditions, based on organized student learning status and school information. This significantly reduces manual work by users and promotes smooth communication with parents. In addition, regarding schedule management, users input schedules related to educational activities into their terminals, and the server organizes them, supporting efficient time management.

[0714] Thus, this system aims to significantly reduce the workload of teachers and improve the quality of education.

[0715] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0716] Step 1:

[0717] The user enters an educational theme and related information into their device. This input includes themes and textbooks to be used, depending on the objectives of the lesson. Specifically, the user enters "History of World War II" into a form on the device and presses the submit button. The entered information is then sent from the device to the server.

[0718] Step 2:

[0719] The server receives the input data and selects relevant resources by referring to a database of educational resources. The server searches the database based on the keyword "World War II" and extracts suitable educational data. At this stage, the server starts processing the generative AI model using a prompt (e.g., "List the main events of World War II and create educational slides").

[0720] Step 3:

[0721] The server utilizes an AI model to automatically generate educational slides. This process automatically generates slide images and text based on the teaching material data extracted in the previous step. The generated slides are then processed into PDF format on the server. The server then sends these processed materials to the user's device.

[0722] Step 4:

[0723] The user reviews the learning materials received on their device. They open the PDF slides on their device, view the content, and make any necessary edits. Once editing is complete, the user saves the materials for use in class.

[0724] Step 5:

[0725] The user inputs student evaluation data into their device. Specifically, this involves entering each student's score and comments into a spreadsheet and uploading it to the server. This evaluation data is then sent to the server.

[0726] Step 6:

[0727] The server securely stores the received evaluation data and performs analysis using statistical methods. The server uses a computational model to calculate average scores, performance distributions, and other metrics, and visualizes the results as graphs and charts. This visualized data is then sent to the terminal after analysis.

[0728] Step 7:

[0729] Users can review the analysis results on their devices and use them to inform their educational policies and future lesson plans. Based on the finalized results, they can take necessary actions and adjust their teaching strategies.

[0730] (Application Example 1)

[0731] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0732] In today's educational environment, the workload of teachers and educational institutions is increasing due to the wide range of tasks they must perform. Creating educational materials, managing student evaluation data, communicating with parents, and scheduling learning activities are all challenging to perform efficiently. Furthermore, integrated management tools are needed to realize educational support throughout the community. Overcoming these challenges and providing more effective educational support is essential.

[0733] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0734] In this invention, the server includes means for inputting educational information, means for automatically generating educational resources based on the input information, and means for proposing teaching methods tailored to the learning progress of individual students. This reduces the workload of educators and enables efficient educational support throughout the community.

[0735] "Educational information" is a general term for data and materials used by teachers and educational institutions to create teaching materials and lesson plans.

[0736] "Educational resources" refer to physical or digital materials such as teaching materials, handouts, and slides used in the course of education.

[0737] "Participant evaluation data" refers to data that shows the results obtained by learners through tests and evaluations, and includes grades and feedback information.

[0738] "Information for parents" refers to announcements regarding the student's learning progress and school activities, and is intended to facilitate communication with parents.

[0739] "Educational support across the entire community" refers to a system that efficiently supports educational activities throughout a broad community, without relying on specific educational institutions.

[0740] "Integrated management means" refers to systems and methods for centrally managing multiple education-related activities, aiming to improve the efficiency of the educational process.

[0741] The system for realizing this invention is centered around a server and terminals. Its main functions include inputting and managing educational information, automatically generating educational resources, managing student evaluation data, sharing information with parents, and providing an integrated management system aimed at supporting education throughout the community.

[0742] The server aggregates educational information using Google Firebase and performs data analysis using TensorFlow. Based on the input educational information, the server automatically generates educational resources and transmits the results to the terminal, creating a system that educators can easily review and use.

[0743] The terminal is operated by the educator, collecting student evaluation data and transmitting it to the server in real time. The student evaluation data is stored in a secure virtual environment, and learning trends are visualized through appropriate processing, presented in a format easily understandable to the educator. Furthermore, information for parents is automatically organized and communicated based on pre-configured criteria.

[0744] As a concrete example, in the event of a specific event held in a region, this system can contribute to the realization of efficient education while reducing the burden on educational settings by creating and providing educational resources related to the event in advance to educators at each school.

[0745] An example of a prompt for a generative AI model would be, "Please suggest educational resources for efficiently sharing relevant information in a specific event." This would likely yield output tailored to specific needs.

[0746] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0747] Step 1:

[0748] Users input educational information using their devices. This includes data on lesson topics, reference materials, and teaching materials to be used. The entered information is sent from the device to the server and stored in Firebase.

[0749] Step 2:

[0750] The server automatically generates educational resources using a generative AI model based on the received educational information. Specifically, it processes the data using TensorFlow, searches for relevant teaching materials in a database, and outputs them as slides and handouts.

[0751] Step 3:

[0752] The generated educational resources are sent from the server to the terminal, making them available for user review. Users can view this information on their terminal and distribute it as printed or electronic data as needed.

[0753] Step 4:

[0754] The user enters student evaluation data into their device. This evaluation data includes test results and records of class participation, and is sent from the device to the server.

[0755] Step 5:

[0756] The server receives student evaluation data and processes it in real time. The data is stored in a secure virtual environment, and the evaluation data is analyzed through computational processing to generate graphs and charts that visualize learning trends.

[0757] Step 6:

[0758] The generated visualization data of learning trends is sent from the server to the terminal, allowing the user to check each student's learning progress and use it to consider teaching methods.

[0759] Step 7:

[0760] The server automatically prepares information for parents based on configured conditions and sends it via email or a dedicated application. This includes updates on student progress and notifications of important school events.

[0761] Step 8:

[0762] For community-wide events, the server generates necessary educational resources in advance and provides relevant information to each terminal. This information is effectively utilized throughout the community to enhance educational support.

[0763] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0764] This invention combines an emotion engine with a system that supports various tasks faced by teachers in educational settings to provide more effective support. The system consists of a server, terminals, and an emotion engine, and is designed to enable teachers to conduct educational activities efficiently.

[0765] The user first uses a terminal to input information about the lesson theme and curriculum. The server receives this information and selects relevant teaching materials from its database. Then, it automatically generates teaching materials based on the selected information and sends the generated materials to the terminal. This allows the user to immediately use the teaching materials they need for their lesson.

[0766] Furthermore, when users input student grades, the server aggregates the data, analyzes the grades, and creates graphs. This information is provided to the terminal, allowing users to visualize the students' level of understanding. The emotion engine also analyzes the user's voice and facial expressions to recognize their emotional state. This allows the server to detect the stress and satisfaction the user feels during class, and to receive and process this feedback.

[0767] For example, if the emotion engine detects that a user is stressed, the server will suggest readjusting the lesson plan to help the user continue their educational activities in a healthy manner. It can also dynamically change the content of the learning materials based on the user's emotional state. This further improves the quality of education.

[0768] By utilizing the emotion engine in this invention, users can receive not only simple preparation of teaching materials and management of grades, but also advanced educational support that responds to their individual emotional states. This system reduces the burden on users and enables more effective and humane education in educational settings.

[0769] The following describes the processing flow.

[0770] Step 1:

[0771] Users input lesson topics, grade levels, and textbook information through their devices. This provides the system with the necessary educational material data.

[0772] Step 2:

[0773] The server receives information entered from the terminal, searches the database, and selects the appropriate educational materials. Identifying materials that align with the curriculum is crucial.

[0774] Step 3:

[0775] The server automatically generates slides and handouts for lessons using the selected materials. It applies templates to create visually meaningful teaching materials.

[0776] Step 4:

[0777] The server sends the generated learning materials to the terminal and provides an interface for the user to review the content and edit it as needed.

[0778] Step 5:

[0779] Users use their devices to input student test results and learning performance data. This allows evaluation information to be stored in a database.

[0780] Step 6:

[0781] The terminal sends the entered performance data to the server, which then statistically analyzes the data. The results are organized in the form of average scores, comprehension levels, and so on.

[0782] Step 7:

[0783] The server visualizes the analysis results in the form of graphs and tables and provides them to the terminal. Users can then use this information to understand learning trends and incorporate them into their instruction.

[0784] Step 8:

[0785] The server receives user voice and facial expression data via an emotion engine and analyzes their emotional state. It then generates feedback based on stress levels and concentration levels.

[0786] Step 9:

[0787] Based on the emotion engine's analysis of the user's emotions, the server suggests adjustments to the lesson content. This includes changing the difficulty level of the teaching materials and adjusting the pace of the lesson.

[0788] Step 10:

[0789] To reduce user stress, the server suggests activities for relaxation and a change of pace, supporting users in engaging in educational activities in a healthy manner.

[0790] (Example 2)

[0791] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0792] To reduce the workload of teachers in educational settings and provide more effective and individualized education, efficient preparation of teaching materials, performance management, analysis of learning progress, and adjustment of teaching methods based on these analyses are essential. Furthermore, a function is needed to address teachers' emotional states and dynamically adjust lesson plans. A system is required that can meet these needs while ensuring safe and efficient work processes.

[0793] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0794] In this invention, the server includes means for inputting educational content, means for automatically generating teaching materials based on the input content, and means for inputting and saving learner performance data. This enables improved work efficiency for teachers and advanced educational support, as well as flexible responses to the needs of individual learners and teachers.

[0795] "Educational content" refers to teaching materials and resources used in educational activities, and is a collection of information used by teachers for educational purposes.

[0796] "Terminal" refers to an information processing device operated by a user, and specifically includes devices such as personal computers and tablets.

[0797] "Learner" refers to anyone receiving education in the educational process, including students.

[0798] "Performance data" refers to information that records learners' learning outcomes, including test results and evaluations.

[0799] The "Internet" refers to an information network connected via public communication networks, enabling information sharing and communication among users.

[0800] "Curriculum" refers to a standardized educational program within an educational institution, and is a system of learning content provided as a curriculum.

[0801] A "schedule" refers to a plan of events and activities to be held within a specific period, and is created to support the efficient progress of educational activities.

[0802] "Emotional state" refers to the user's psychological and sensory state, including psychological changes such as stress and satisfaction.

[0803] The embodiments for carrying out the invention are described below.

[0804] This system is designed to support teachers' work in educational settings and consists of a server, terminals, and an emotion engine. Users input educational information using the terminals, and the system generates teaching materials and manages and analyzes grades via the server. The emotion engine also analyzes the user's emotional state and adjusts educational activities accordingly.

[0805] The server executes computer programs to process the received data. Python and related generative AI models are used for the automatic generation of educational materials. Specific functions include searching for educational materials from a database using Elasticsearch and data analysis using Pandas and Matplotlib. The terminal displays information entered by the user and the received educational materials.

[0806] Users input information related to the lesson theme and curriculum into their terminals, sending data to the server. Based on this information, the server automatically generates teaching materials and sends them to the terminals. This allows users to immediately begin their educational activities.

[0807] Furthermore, by utilizing the emotion engine to analyze the user's emotional state, the server can suggest adjustments to the lesson plan based on that feedback. This allows teachers to conduct educational activities that take their own psychological state into account.

[0808] As a concrete example, when teaching "plant growth" in an elementary school science class, the user can input the lesson plan into the terminal, and the system can automatically generate the relevant teaching materials. An example of a prompt message to the generation AI model would be, "Please generate teaching materials on the topic of 'plant growth' for a 5th-grade elementary school science class. The materials should include illustrations and videos, and should be able to be taught in 20 minutes or less." This allows for the easy preparation of appropriate lesson content.

[0809] This system not only reduces the burden on teachers but also provides innovative educational technologies to improve the quality of education.

[0810] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0811] Step 1:

[0812] Users input lesson topics and curriculum information using their devices. This information includes the lesson objectives, desired learning outcomes, and the format of the materials to be used (text, images, videos, etc.). The entered data is sent to the server.

[0813] Step 2:

[0814] The server searches the database based on the information received from the user and selects relevant educational materials. Specifically, it uses ElasticSearch to search for educational materials in the database and passes the results to the material generation AI model. The input used in this step is the lesson theme and curriculum information provided by the user, and the output is a list of materials required by the material generation AI model.

[0815] Step 3:

[0816] The server automatically generates lesson materials by combining selected materials using an AI model for material generation. The generation process uses programming languages ​​such as Python to process the selected materials with the AI ​​model and generate optimal lesson materials. The input is the material list obtained in step 2, and the output is the completed lesson material.

[0817] Step 4:

[0818] The server sends the completed teaching materials to the terminal. The user can then review the received materials on the terminal and proceed with preparing for the lesson. The terminal displays the received materials to the user and downloads them as needed.

[0819] Step 5:

[0820] Users input student performance data collected during class into their terminals. This includes test results and project evaluations. The entered performance data is then sent to the server.

[0821] Step 6:

[0822] The server performs data analysis based on the received performance data. The analysis uses Python's Pandas and Matplotlib libraries to aggregate and visualize the data. The input is the performance data entered by the user, and the output is a visualized representation of the learner's trends.

[0823] Step 7:

[0824] The server operates an emotion engine to analyze the user's voice and facial expressions. User emotion data (such as stress levels and satisfaction) is input, and feedback is generated based on the analysis results. Speech recognition software and image processing libraries are used for emotion analysis.

[0825] Step 8:

[0826] Based on the analysis results, the server makes suggestions to the user regarding adjustments to the lesson plan. For example, if the user is experiencing high stress levels, it may suggest slowing down the pace of the lesson. This allows the user to create an optimal learning environment.

[0827] (Application Example 2)

[0828] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0829] In modern education, there is a need for individualized support tailored to each student's learning style and emotional state. In particular, when learners are experiencing emotional stress, or conversely, are highly engaged and excited, flexible adjustments to teaching materials and methods are essential. However, traditional educational support systems struggle to provide this emotional flexibility, placing a significant burden on educators. Therefore, there is a need for an educational support system that can detect students' emotional states and provide appropriate educational activities.

[0830] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0831] In this invention, the server includes means for inputting educational materials, means for detecting the learner's emotional state using emotion analysis technology and dynamically changing the content of the materials, and means for making suggestions for adjusting educational activities based on the emotional state. This makes it possible for educators to easily provide appropriate educational activities that correspond to the learner's emotional state.

[0832] "Means for inputting educational materials" refers to devices or methods for incorporating information and data necessary for education into a system.

[0833] "Means for automatically generating educational materials based on input materials" refers to a device or method that automatically creates educational materials for learners based on input educational information.

[0834] "Means for displaying or distributing generated teaching materials" refers to devices or methods for showing, electronically or physically, the created teaching materials to learners.

[0835] "Means for inputting and saving student performance data" refers to a device or method for inputting information regarding students' learning outcomes into a system and saving it for later use.

[0836] "Means for analyzing stored performance data and visualizing learning trends" refers to a device or method that analyzes recorded performance information and processes it into a format that can be easily understood at a glance.

[0837] "Means for automatically preparing and transmitting information to parents" refers to devices or methods that automatically collect educational information and provide it to parents.

[0838] "Means for managing schedules related to educational activities and supporting efficient time management" refers to devices or methods that organize educational schedules and assist in effective time allocation.

[0839] "Means of proposing instructional approaches tailored to the learning situation of individual students" refers to a device or method that presents the optimal instructional method based on each student's learning progress.

[0840] "Means for detecting a learner's emotional state using emotion analysis technology and dynamically changing the content of learning materials" refers to a device or method that analyzes a learner's emotions and adjusts the content of learning materials according to the situation.

[0841] "Means for making suggestions to adjust educational activities based on emotional state" refers to a device or method that provides advice for adjusting educational methods in accordance with the learner's emotions.

[0842] To realize this invention, a system specifically designed for educational settings will be used. This system consists of three main elements: a server, a terminal, and a user. Each element plays a specific role, thereby achieving effective educational support.

[0843] The server accepts input for educational materials and automatically generates teaching materials based on the input themes using a generative AI model. This generation process creates materials optimized to fit the educational curriculum. The server then sends the generated materials to devices, allowing users to view or distribute them. Furthermore, the server aggregates student performance data, securely stores it in a cloud environment, and provides real-time visualization of this data.

[0844] The terminal primarily functions as a user interface. Educators, as users, can review and show generated learning materials to learners through this terminal. The terminal also incorporates sentiment analysis technology, detecting learners' emotional states through audio and video and sending this information to the server. This allows the content of the learning materials to be dynamically adjusted according to the situation.

[0845] The user, acting as a teacher or educational support staff, operates the entire system. The user inputs educational materials into the system and manages subsequent educational activities. For example, if the user inputs student grades, the system analyzes and visualizes learning trends based on that data. Furthermore, if the server detects that a learner is experiencing stress, the user can receive suggestions from the server and adjust the lesson plan accordingly.

[0846] As a concrete example, when a user inputs the theme "basic arithmetic," the generative AI model generates arithmetic learning materials based on that theme, and if the learner is experiencing stress, it suggests slowing down the learning pace. This process can be achieved by using the following prompt example: "Generate educational materials for children based on the input theme. Also, adjust according to the emotional state, and slow down the learning speed if the learner is experiencing stress."

[0847] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0848] Step 1:

[0849] Users input educational materials using a terminal. This input includes information about the lesson theme and the curriculum it covers. The terminal prepares the data by sending this information to the server in digital format.

[0850] Step 2:

[0851] The server automatically generates educational materials using a generative AI model based on the received educational materials. Optimized materials are created based on the input theme. The generative AI model algorithmically processes the materials corresponding to each subject and outputs them in various formats (e.g., PDF or video materials).

[0852] Step 3:

[0853] The server sends the generated learning materials to the terminal, which then displays them to the user. The user can review the displayed materials and make modifications as needed. The materials are then distributed to learners in an appropriate format.

[0854] Step 4:

[0855] Users input student performance data using their devices. This performance information is based on the results of regular tests and in-class activities, and is transferred from the device to the server.

[0856] Step 5:

[0857] The server analyzes stored performance data and statistically visualizes learning trends. Specifically, it securely stores data in a cloud environment, performs statistical analysis and graph creation, and generates performance trends in real time.

[0858] Step 6:

[0859] The emotion analysis technology installed on the device collects emotional data from the learner's voice and facial expressions and sends it to a server. This data is used as input to determine whether the learner is experiencing stress.

[0860] Step 7:

[0861] The server analyzes the received emotional data and suggests changes to teaching materials or adjustments to the lesson plan based on its content. For example, it might notify the user of adjustments such as, "The generative AI model suggests slowing down the learning speed if stress levels are high."

[0862] Step 8:

[0863] Users receive suggestions from the server and adjust educational activities as needed. This allows for flexible responses to learners' emotional states and provides an effective learning experience.

[0864] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0865] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0866] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0867] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0868] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0869] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0870] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0871] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0872] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0873] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0874] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0875] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0876] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0877] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0878] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0879] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0880] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0881] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0882] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0883] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0884] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0885] The following is further disclosed regarding the embodiments described above.

[0886] (Claim 1)

[0887] A means of inputting educational materials,

[0888] A means of automatically generating teaching materials based on input materials,

[0889] Means for displaying or distributing the generated teaching materials,

[0890] A means for inputting and saving student performance data,

[0891] A means of analyzing saved performance data and visualizing learning trends,

[0892] A means of automatically preparing and sending information to parents,

[0893] A means of managing schedules related to educational activities and supporting efficient time planning,

[0894] A means of proposing instructional approaches tailored to the learning situation of each individual student,

[0895] A system that includes this.

[0896] (Claim 2)

[0897] The system according to claim 1, which selects educational materials based on the curriculum and optimizes the material generation process.

[0898] (Claim 3)

[0899] The system according to claim 1, which securely manages and visualizes student performance data in a cloud environment in real time.

[0900] "Example 1"

[0901] (Claim 1)

[0902] A means of inputting educational themes and related information,

[0903] A means of selecting educational resources from a database based on input information and automatically generating teaching materials using a generative AI model,

[0904] A means of sending and displaying the generated teaching materials on a device,

[0905] A means for inputting and recording student evaluation data,

[0906] A means of analyzing recorded evaluation data and visualizing learning trends using statistical methods,

[0907] A means to organize students' learning progress and school information, and to automate the transmission of this information to parents,

[0908] A means to input educational activity schedules and support the streamlining of time management,

[0909] A means of proposing the optimal teaching strategy based on each student's learning data,

[0910] A system that includes this.

[0911] (Claim 2)

[0912] The system according to claim 1, which selects educational resources based on an educational plan and streamlines the process of generating teaching materials.

[0913] (Claim 3)

[0914] The system according to claim 1, which manages evaluation data in an environment that allows for information protection and enables immediate visualization.

[0915] "Application Example 1"

[0916] (Claim 1)

[0917] A means of entering educational information,

[0918] A means for automatically generating educational resources based on input information,

[0919] Means for displaying or distributing the generated educational resources,

[0920] A means for inputting and saving participant evaluation data,

[0921] A means of analyzing saved evaluation data and visualizing learning trends,

[0922] A means of automatically preparing and transmitting information to parents,

[0923] A means of managing schedules related to learning activities and supporting efficient time management,

[0924] A means of proposing teaching methods tailored to the learning progress of each individual student,

[0925] A means of comprehensively managing educational curricula and events to realize educational support throughout the community,

[0926] A system that includes this.

[0927] (Claim 2)

[0928] The system according to claim 1, which selects educational information based on a plan and optimizes the educational resource generation process.

[0929] (Claim 3)

[0930] The system according to claim 1, which securely manages and visualizes participant evaluation data in a virtual environment in real time.

[0931] "Example 2 of combining an emotion engine"

[0932] (Claim 1)

[0933] A means of inputting educational content,

[0934] A means of automatically generating educational materials based on input content,

[0935] A means of displaying or distributing the generated teaching materials on a device,

[0936] A means for inputting and saving learner performance data,

[0937] A means of analyzing saved performance data and visualizing learning patterns,

[0938] A means of automatically preparing and sending information to parents,

[0939] A means of managing schedules related to educational activities and supporting efficient time management,

[0940] A means of proposing teaching methods tailored to each learner's learning situation,

[0941] A means of analyzing the user's emotional state and adjusting educational activities,

[0942] A system that includes this.

[0943] (Claim 2)

[0944] The system according to claim 1, which selects educational content based on the curriculum and optimizes the material generation process.

[0945] (Claim 3)

[0946] The system according to claim 1, which securely manages learner performance data on the internet and visualizes it in real time.

[0947] "Application example 2 when combining with an emotional engine"

[0948] (Claim 1)

[0949] A means of inputting educational materials,

[0950] A means of automatically generating teaching materials based on input materials,

[0951] Means for displaying or distributing the generated teaching materials,

[0952] A means for inputting and saving student performance data,

[0953] A means of analyzing saved performance data and visualizing learning trends,

[0954] A means of automatically preparing and sending information to parents,

[0955] A means of managing schedules related to educational activities and supporting efficient time planning,

[0956] A means of proposing instructional approaches tailored to the learning situation of each individual student,

[0957] A means of detecting learners' emotional states using emotion analysis technology and dynamically changing the content of learning materials,

[0958] A means of making suggestions for adjusting educational activities based on emotional states,

[0959] A system that includes this.

[0960] (Claim 2)

[0961] The system according to claim 1, which selects educational materials based on the curriculum and optimizes the material generation process.

[0962] (Claim 3)

[0963] The system according to claim 1, which securely manages and visualizes student performance data in a cloud environment in real time. [Explanation of symbols]

[0964] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of inputting educational materials, A means of automatically generating teaching materials based on input materials, Means for displaying or distributing the generated teaching materials, A means for inputting and saving student performance data, A means of analyzing saved performance data and visualizing learning trends, A means of automatically preparing and sending information to parents, A means of managing schedules related to educational activities and supporting efficient time planning, A means of proposing instructional approaches tailored to the learning situation of each individual student, A system that includes this.

2. The system according to claim 1, which selects educational materials based on the curriculum and optimizes the material generation process.

3. The system according to claim 1, which securely manages and visualizes student performance data in a cloud environment in real time.

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