System

Abstract

A system is provided.SOLUTION: An educational system comprising: means for automatically generating a curriculum based on an educational goal using a generation AI; means for generating moving image content and inserting an educational test into a moving image; means for distributing the generated moving image content to user terminals; means for automatically scoring user answers and feeding back learning results; and means for managing a plurality of educational goal settings and providing curriculum of other educational institutions.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In today's educational environment, issues such as teacher recruitment, overtime, and the survival of schools themselves are becoming increasingly serious. Students also face problems such as boring classes and limited opportunities to learn. Furthermore, amid a widening educational gap, it is becoming increasingly difficult to provide high-quality education. There is a need to improve this situation and provide efficient, high-quality education to as many students as possible. Another issue emerging is the inability of students to take the curriculum of other educational institutions of their choice. [Means for solving the problem]

[0005] The present invention is a system that stores a vast amount of teaching material data in a database and uses generative AI to automatically generate curricula based on educational goals set by each educational institution. In particular, it includes a means for automatically generating video content and inserting educational tests into the videos. The system also has functions for distributing the generated video content to user devices, automatically scoring user answers, and providing feedback on learning results. Furthermore, it includes a means for managing multiple educational goal settings and enabling the provision of curricula from other educational institutions, allowing students to take the curricula of their choice. To enhance interactivity, the system also includes a means for providing real-time feedback within the video content and a function for users to post comments, analyzing the collected comments, and incorporating them into the curriculum. This improves the quality of education while reducing the burden on teachers and increasing the efficiency of education itself.

[0006] "Teaching Materials Data" refers to textbooks, past exam papers, slides, lecture notes, and other learning materials used for educational purposes.

[0007] "Generative AI" refers to algorithms or systems that use artificial intelligence technology to automatically generate purposeful content based on specific input data.

[0008] "Curriculum" refers to a plan that defines the content and sequence of learning to be undertaken at a particular educational institution or course of study.

[0009] "Video content" refers to media materials containing video and audio that provide learning content visually and audibly.

[0010] An "educational test" refers to a set of questions or problems used to assess a learner's understanding or proficiency.

[0011] "User terminal" refers to an electronic device used by a learner, such as a computer, smartphone, or tablet.

[0012] "Automatic scoring" refers to the process of using artificial intelligence or algorithms to automatically evaluate submitted answers and generate scores and feedback.

[0013] "Feedback" refers to information such as learning results and areas for improvement that are provided to learners.

[0014] "Interactivity" refers to the interactive nature of the educational content and the learner, and specifically includes real-time question and answer and comment functions.

[0015] "Curriculum management" refers to the process of integrating and organizing multiple educational goal settings and curricula, and providing and modifying them as needed.

[0016] "Curriculum of other educational institutions" refers to the content of educational programs and learning plans established by educational institutions other than the one to which the learner is currently enrolled. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0025] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0038] This invention is a teacher replacement AI system that uses artificial intelligence (AI) and interactive video content to improve the quality of education. This system has the ability to collect a huge amount of teaching material data and use generative AI to automatically generate a curriculum based on the educational goals set by each educational institution. Below, we will explain each major component of this system and how it works.

[0039] 1. Curriculum setting and data collection

[0040] User (School Administrator):

[0041] School administrators input educational goals (learning objectives and curriculum requirements) and upload teaching material data such as textbooks, past exam questions, and other teaching materials.

[0042] Device:

[0043] The terminal transmits the information input by the school administrator to the server and uploads the teaching material data to the server.

[0044] server:

[0045] The server receives the educational goal settings and teaching material data, analyzes them, and stores them in a database. Specifically, it performs text analysis to extract keywords and important points.

[0046] 2. Curriculum generation and animation

[0047] server:

[0048] The server uses AI to automatically generate a curriculum based on educational goals. Video content is then created based on the generated curriculum. Slides are generated based on text information, and narration is added using a speech synthesis engine. Educational test questions are also inserted into the video to add interactivity.

[0049] 3. Video content and test distribution

[0050] server:

[0051] The server uploads the generated video content and educational tests to the streaming server and generates links for each. The links are organized by semester and subject and provided to students' devices.

[0052] 4. Students listen and take the test

[0053] User (student):

[0054] Students click on the provided link to watch the video content, answer the test questions inserted in the video, and send their answers from their device to the server.

[0055] 5. Feedback on learning results

[0056] server:

[0057] The server automatically scores the answers received and analyzes the accuracy rate and level of understanding. The learning results are then fed back to the student's dashboard, which displays the score, mistakes made, and topics requiring additional study.

[0058] 6. Customization and participation in other educational institutions' curricula

[0059] User (student):

[0060] Students can select and take courses from other educational institutions by searching for the relevant grade, subject, and educational institution, and then watching videos and taking tests based on the provided curriculum.

[0061] server:

[0062] The server provides videos and tests for the selected curriculum and records the student's learning progress.

[0063] Specific examples

[0064] For example, suppose an educational administrator at School A sets up a "second-semester mathematics curriculum" and uploads related textbooks and past exam questions. The server receives this and uses generative AI to automatically generate lectures such as "Fundamentals of Equations" and "Probability Calculations." Test questions are inserted at the end of each chapter in the generated videos to check comprehension. Students watch these videos on their devices and answer each test. The server automatically grades the answers and provides feedback in real time. In some cases, students can also take an excellent mathematics curriculum from another school, School B, and the server provides them with corresponding videos and tests.

[0065] In this way, the educational system of the present invention supports efficient learning while improving the quality of education, and also contributes to eliminating educational disparities.

[0066] The processing flow will be explained below.

[0067] Step 1:

[0068] User (School Administrator):

[0069] The user (school administrator) inputs educational goals (learning objectives and curriculum requirements) into the system. Specifically, they enter information such as the grade, subject, learning objectives for the semester, and key learning items, and then send it to the system.

[0070] Step 2:

[0071] User (School Administrator):

[0072] Users (school administrators) select textbooks, past exam papers, and other teaching material data and upload them to the system, which is then added to the system's teaching material database.

[0073] Step 3:

[0074] Device:

[0075] The terminal transmits the educational goal setting sent by the user and the uploaded teaching material data to the server.

[0076] Step 4:

[0077] server:

[0078] The server analyzes the received educational goal settings and teaching material data and stores them in a database. Specifically, it performs text analysis, extracts keywords and important points, and converts them into a format that is easy to search.

[0079] Step 5:

[0080] server:

[0081] The server uses generative AI to automatically generate a curriculum based on educational goals, including setting the learning sequence and selecting learning topics.

[0082] Step 6:

[0083] server:

[0084] The server then creates video content based on the generated curriculum. Specifically, it generates slides based on text information and adds narration using a speech synthesis engine. At the same time, it sets up educational test questions at the end of each topic.

[0085] Step 7:

[0086] server:

[0087] The server uploads the generated videos and tests to a streaming server and generates viewing links, organized by semester and subject.

[0088] Step 8:

[0089] server:

[0090] The server distributes the viewing link to the user terminal. Specifically, it sends the viewing link to the terminal of the registered student, allowing them to start learning.

[0091] Step 9:

[0092] User (student):

[0093] The user (student) clicks on the provided link to watch the video, answers the test questions inserted in the video while watching, and sends the answers to the system.

[0094] Step 10:

[0095] Device:

[0096] The terminal sends the user's (student's) answers to the server, which then sends the answers in real time and automatically grades them.

[0097] Step 11:

[0098] server:

[0099] The server automatically scores the received answers and analyzes the accuracy rate and level of understanding. The results are fed back to the user's (student's) dashboard as learning results.

[0100] Step 12:

[0101] User (student):

[0102] Students can check their learning results on the dashboard and re-learn topics they have not fully understood. They can also select and take courses from other educational institutions if they wish.

[0103] Step 13:

[0104] server:

[0105] The server provides selected users with videos and tests from other educational institutions' curricula and records their learning progress, allowing users to take high-quality curricula from other educational institutions and improve the quality of their education.

[0106] Through this series of steps, the system can provide an efficient and high-quality learning environment, reduce the burden on teachers, and contribute to eliminating educational disparities.

[0107] Example 1

[0108] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0109] In conventional educational systems, the provision of teaching materials and feedback on learning results was not done in real time, resulting in issues with student learning efficiency. It was also difficult to automatically generate curricula based on educational goals, and it was difficult to share resources across multiple educational institutions. Furthermore, content that lacked interactivity made it difficult to maintain students' interest, which tended to reduce learning effectiveness.

[0110] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0111] In this invention, the server includes a means for storing a large amount of teaching material data in a database, a means for automatically generating a curriculum based on educational goals using a generative AI, a means for inputting prompts into a generative AI model and creating video content based on the curriculum, a means for inserting educational tests into the videos, a means for distributing the generated video content and educational tests to a user terminal, a means for automatically scoring user answers and providing real-time feedback on learning results, and a means for managing multiple educational goal settings and enabling the provision of curricula from other educational institutions. This enables real-time feedback on learning results, automatic generation of a curriculum based on educational goals, and resource sharing among multiple educational institutions. Furthermore, highly interactive content can maintain student interest and improve learning effectiveness.

[0112] "Vast amounts of educational material data" refers to the large amount of electronic data used for education, such as textbooks, past exam questions, and supplementary materials.

[0113] A "database" refers to a system for efficiently storing, managing, searching, and using information.

[0114] "Generative AI" refers to artificial intelligence that automatically generates natural language, images, curriculum, and more based on input data.

[0115] An "educational goal" refers to a specific objective or purpose that a student should achieve through a particular learning process.

[0116] "Curriculum" refers to learning content and educational programs that are systematically constructed based on educational goals.

[0117] A "generative AI model" refers to an artificial intelligence algorithm that learns from diverse data and generates new data and content based on that knowledge.

[0118] A "prompt sentence" refers to an input sentence that elicits a specific response or output from a generative AI model.

[0119] "Video Content" refers to educational materials in video format created for educational purposes.

[0120] "Educational test" refers to an assessment tool that includes questions designed to assess a learner's understanding and knowledge retention.

[0121] "User terminal" refers to electronic devices such as PCs, smartphones, and tablets that learners and educational institution administrators use to access and operate the system.

[0122] "Automatic scoring" refers to the process by which a system automatically evaluates and scores submitted test answers.

[0123] "Real-time feedback" refers to responding immediately to a user's actions and answers, and providing learning results and evaluations immediately.

[0124] "Setting multiple educational goals" refers to the ability of different learners and grade levels to have different educational goals and to manage these multiple goals simultaneously.

[0125] "Curriculum of other educational institutions" refers to educational programs and learning content offered at other schools or educational facilities.

[0126] This invention is a teacher replacement AI system that uses artificial intelligence (AI) and interactive video content to improve the quality of education. Specific implementation methods of this system are described below.

[0127] Curriculum setting and data collection

[0128] User (School Administrator):

[0129] School administrators log in to the system and enter educational goals (learning objectives and curriculum requirements) into an input form on a terminal. They also upload related educational material data, such as textbooks, past exam questions, and supplementary materials, to the system. Specifically, they use a web browser to perform operations from the management dashboard.

[0130] Device:

[0131] The device receives the user's input information and uploaded files and sends them to the server. The device can be a PC, tablet, smartphone, etc. This information is temporarily stored on the device, encrypted, and then sent to the server.

[0132] server:

[0133] The server receives the educational goals and teaching material data sent from the device. The received data is then analyzed to extract educational keywords and key points, which are then stored in a database. The software used includes a natural language processing (NLP) engine, which analyzes a PDF file, such as "math textbook.pdf," to extract keywords like "equation" and "probability."

[0134] Curriculum generation and animation

[0135] server:

[0136] The server automatically generates a curriculum using a generative AI model (such as GPT-3 or BERT) based on the analyzed data and the input educational goals. A prompt is input into the generative AI model to generate an appropriate curriculum. An example of a prompt is, "Generate an environmental science curriculum for second-year high school students based on the following Sustainable Development Goals (SDGs). Provide the following materials as teaching material data: textbook (title: Earth Environmental Science, 2nd Edition), past exam questions (period: past five years), and other supplementary materials (title: Science for a Sustainable Future). The curriculum should also include interactive test questions."

[0137] Video content is created based on the generated curriculum. Specifically, slides are generated using presentation software, narration is added using a speech synthesis engine (e.g., Google Cloud Text-to-Speech), and educational test questions are added to the video to make it interactive.

[0138] Video content and test delivery

[0139] server:

[0140] The server uploads the created video content and educational tests to the streaming server, generates links for each piece of content, organizes them by semester and subject, and stores them in a database, allowing students to easily access the content.

[0141] Students listen and take the test

[0142] User (student):

[0143] Students click on the provided link on their device (PC, tablet, smartphone) to watch the video content. The video also includes educational tests, and they can answer interactive tests in real time according to their learning progress.

[0144] Feedback on learning results

[0145] server:

[0146] The server uses software to automatically score the test answers submitted by students. The automatic scoring is done using machine learning algorithms (e.g., Scikit-learn) to instantly analyze the percentage of correct answers and level of understanding. The results are immediately fed back to the student's dashboard, and further study advice is provided depending on the level of understanding.

[0147] Customization and access to other educational institutions' curricula

[0148] User (student):

[0149] Students can select and take courses offered by other educational institutions by searching for the relevant grade, subject, and educational institution name, and then taking the provided curriculum videos and tests.

[0150] server:

[0151] The server provides videos and tests for selected curriculum and records students' learning progress, allowing them to improve the quality of their education and contributing to eliminating educational disparities.

[0152] The educational system of the present invention supports efficient learning while improving the quality of education, and is of great help in eliminating educational disparities.

[0153] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0154] Step 1: Setting up the curriculum and inputting teaching material data

[0155] User (School Administrator):

[0156] School administrators log in to the system and input educational goals (learning objectives and curriculum requirements) into an input form on their terminal. They also upload related educational material data, such as textbooks, past exam papers, and supplementary materials, to the system. The input information and uploaded data become input. The system then receives the educational goals and educational material data.

[0157] Specific behavior:

[0158] Access the management dashboard and enter your educational goals (e.g., "Second semester math curriculum").

[0159] Upload files such as textbooks (e.g., "Mathematics textbook.pdf") and past exam questions (e.g., "Past exam questions.zip").

[0160] Step 2: Send data from the device to the server

[0161] Device:

[0162] The information entered by the user and the files uploaded are temporarily stored inside the device. This information is then encrypted and securely sent to the server. The input is the user's input information and uploaded data, and the output is the encrypted data to be sent.

[0163] Specific behavior:

[0164] The device encrypts educational goals and teaching material data.

[0165] The encrypted data is sent to the server.

[0166] Step 3: Receiving and analyzing the teaching material data

[0167] server:

[0168] The server receives the educational goals and teaching material data sent from the device. It performs text analysis on the received data and extracts educational keywords and important points. The results of this analysis are input, and the information stored in the database is output.

[0169] Specific behavior:

[0170] The server receives "MathematicsTextbook.pdf".

[0171] Using software (NLP engine), keywords such as "equation" and "probability" are extracted.

[0172] The extracted information is stored in a database.

[0173] Step 4: The curriculum generation process

[0174] server:

[0175] The server automatically generates a curriculum using a generative AI model based on the analyzed data and the input educational goals. At this time, a prompt sentence is input into the generative AI model, and an appropriate curriculum is output.

[0176] Specific behavior:

[0177] Enter a prompt into the generative AI model: "Generate an environmental science curriculum for second-year high school students based on the following Sustainable Development Goals (SDGs). Provide the following materials as teaching material data: textbook (title: Earth Environmental Science, 2nd Edition), past exam papers (period: past five years), and other supplementary materials (title: Science for a Sustainable Future). The curriculum should also include interactive test questions."

[0178] Receive and save the generated curriculum.

[0179] Step 5: Create video content

[0180] server:

[0181] The server creates video content based on the generated curriculum. Slides are generated using presentation software, and narration is added using a speech synthesis engine. Educational test questions are also interactively inserted into the video. The input is the generated curriculum, and the output is the completed video content.

[0182] Specific behavior:

[0183] Create slides: "Basics of Equations," "Calculating Probability," etc.

[0184] Add narration using a text-to-speech engine.

[0185] Educational tests are included for each chapter.

[0186] Step 6: Deliver content and tests

[0187] server:

[0188] The generated video content and educational tests are uploaded to a streaming server, and links are generated for each piece of content. These links are organized by semester and subject and stored in a database. The input is the completed video content, and the output is the provided link.

[0189] Specific behavior:

[0190] Upload the video file (e.g. "Basics of Equations.mp4" or "Probability Calculations.mp4") to the streaming server.

[0191] Each video link is generated and stored in an organized database.

[0192] Step 7: Students watch and take the test

[0193] User (student):

[0194] Students click the provided link on their device (PC, tablet, smartphone) to watch the video content and answer the interactive educational test inserted in the video. The input is the provided link and the student's viewing behavior, and the output is the submitted test answer.

[0195] Specific behavior:

[0196] The student clicks on the provided link: https: / / example.com / equations and watches the video.

[0197] Answer the test questions that appear while watching the video and submit your answers.

[0198] Step 8: Marking and feedback on answers

[0199] server:

[0200] The server uses an automatic scoring algorithm to evaluate test answers submitted by students. It analyzes the accuracy rate and level of understanding and provides real-time feedback to the student's dashboard. The input is the submitted test answers, and the output is the analysis results and feedback.

[0201] Specific behavior:

[0202] Test answers are graded using machine learning algorithms (e.g., Scikit-learn).

[0203] Correct answer rate and level of understanding are analyzed, and learning results are displayed on a dashboard.

[0204] Step 9: Selecting a curriculum from another institution

[0205] User (student):

[0206] Students can select and take courses offered by other educational institutions by searching for the target grade, subject, and educational institution name, watching videos based on the offered curriculum, and taking tests. The input is the search query, and the output is a link to the selected curriculum.

[0207] Specific behavior:

[0208] A student uses the search form to search for "School B's 3rd semester physics curriculum" and selects to take the course.

[0209] Step 10: Delivering curriculum and recording learning progress

[0210] server:

[0211] The server provides videos and tests for the selected curriculum and records the student's learning progress. The input is the link to the selected curriculum, and the output is the provided learning materials and recorded progress data.

[0212] Specific behavior:

[0213] We provided students with a video link and test for the "Physics curriculum for the third term at School B" that they selected.

[0214] Record student learning progress and display it on a dashboard.

[0215] (Application example 1)

[0216] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0217] Traditional educational systems require a lot of manual work, from setting up and generating curriculum to creating video content, and then distributing and providing feedback to students, making it difficult to provide efficient and effective education. Furthermore, low interactivity meant that students' motivation and comprehension were not sufficiently improved. Furthermore, it was difficult to provide real-time feedback or share curricula from other educational institutions, which could exacerbate educational disparities.

[0218] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0219] In this invention, the server includes means for storing a huge amount of teaching material data in a database, means for automatically generating a curriculum based on educational goals using a generation AI, means for generating video content and inserting educational tests into the videos, means for distributing the generated video content to user terminals, means for automatically scoring user answers and providing feedback on learning results, means for managing multiple educational goal settings and enabling the provision of curricula from other educational institutions, and means for real-time lecture viewing and interactive testing using smart wearable devices. This enables the provision of efficient and effective education and improves students' motivation to learn and their level of understanding.

[0220] "Teaching material data" refers to digital textbooks, past exam papers, and other learning materials used by teachers and educational institutions for educational purposes.

[0221] "Generative AI" refers to a system that uses artificial intelligence technology to automatically generate curriculum and educational content based on input data.

[0222] "Automatic curriculum generation" refers to the process in which generative AI automatically creates learning plans and course content based on the educational goals set by educational institutions.

[0223] "Video content" refers to educational multimedia files that combine audio, video, slides, etc.

[0224] "Educational tests" are questions created for educational purposes that are displayed within video content and used to gauge students' understanding.

[0225] "Delivery means" refers to the technology used to deliver video content and tests generated using the Internet or cloud services to each user's device.

[0226] "Automatic scoring" refers to the function in which the system analyzes the user's answers, determines whether they are correct, and assigns a score.

[0227] "Feedback" refers to the function of providing real-time information such as students' level of understanding and areas for improvement based on their learning results.

[0228] "Smart wearable devices" refer to interactive electronic devices that can be worn and used by a user, examples of which include smart glasses and smart watches.

[0229] "Real-time lecture viewing" refers to the function that allows students to attend lectures in real time using smart wearable devices.

[0230] An "interactive test" is a test format in which participants answer questions asked while watching a video on the spot using technologies such as voice recognition and eye tracking.

[0231] "Other educational institution curriculum" refers to the learning plans and course content offered by other schools or educational institutions that students can select and take.

[0232] This invention provides a teacher replacement system that uses generative AI models and interactive video content to improve the quality of education. This system stores a huge amount of teaching material data in a database, uses generative AI to automatically generate a curriculum based on educational goals, creates video content and educational tests, and distributes them to user devices. Furthermore, it is possible to watch lectures in real time and take interactive tests using smart wearable devices.

[0233] 1. Management of teaching material data

[0234] The server receives a huge amount of educational material data, such as textbooks and past exam questions, uploaded by school administrators and stores it in a database, which ensures that it is always accessible.

[0235] 2. Automatic curriculum generation

[0236] The server uses generative AI to automatically generate a curriculum based on the received teaching material data and educational goals. In this process, text analysis technology is used to extract important keywords and key points, and educational content is then constructed based on these.

[0237] 3. Creating video content and educational tests

[0238] The server creates video content based on the automatically generated curriculum. It generates slides based on text information, adds narration using a speech synthesis engine, and inserts educational test questions to add interactivity to the video.

[0239] 4. Content Delivery

[0240] The server uploads the generated video content and educational tests to the streaming server and distributes them to user devices.Using smart wearable devices, users can watch lectures in real time and take interactive tests.

[0241] 5. Automatic grading and feedback

[0242] The server automatically grades the user's answers and provides real-time feedback on the learning results to the user's device or smart wearable device. It also suggests additional learning based on the user's individual progress.

[0243] Specific examples

[0244] For example, suppose an educational administrator at School A sets up a "second-semester mathematics curriculum" and uploads related textbooks and past exam questions. The server receives this and uses generative AI to automatically generate lectures such as "Fundamentals of Equations" and "Probability Calculations." Test questions are inserted into the generated videos at the end of each chapter to check comprehension. Students watch these videos using smart glasses and answer each test using eye tracking and voice recognition. The server automatically grades the answers and provides feedback in real time.

[0245] Furthermore, an example of a prompt is, "Read the following passage and answer the question: Describe the automated generation and delivery of educational content. Question: What technologies are used to generate educational content?"

[0246] Specific hardware used includes smart wearable devices such as smart glasses and smart watches, and software used includes OpenCV, Transformers (Hugging Face), gTTS, and playsound.

[0247] Through the above structure and process, this educational system is able to provide efficient and effective education and improve students' motivation to learn and their level of understanding.

[0248] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0249] Step 1:

[0250] The server stores the educational material data (textbooks, past exam questions, etc.) uploaded by the school administrator in a database. The input is the data uploaded by the school administrator, and the output is the educational material data stored in the database. Specifically, the server receives the data and performs text analysis, extracts important keywords and points, and stores them in the database.

[0251] Step 2:

[0252] The server uses generative AI to automatically generate a curriculum based on educational goals. The input is stored teaching material data and educational goal settings, and the output is an automatically generated curriculum. Specifically, the generative AI model analyzes the data and generates lesson plans that suit the educational goals.

[0253] Step 3:

[0254] The server generates video content based on the automatically generated curriculum and inserts interactive educational tests into the videos. The input is the automatically generated curriculum, and the output is the video content and educational tests. Specifically, the server generates slides based on text information, adds narration using a speech synthesis engine, and inserts test questions at appropriate points.

[0255] Step 4:

[0256] The server uploads the generated video content to a streaming server and distributes it to user terminals. The input is the generated video content, and the output is a distribution link that is generated and provided to the user terminal. Specifically, the server uploads video files and provides a dedicated access point for each user.

[0257] Step 5:

[0258] Users use smart wearable devices to watch lectures in real time and take interactive tests within the videos. The input is the distribution link and the smart wearable device, and the output is the user's test answers. Specifically, users answer the tests using eye tracking and voice recognition while watching the videos.

[0259] Step 6:

[0260] The server automatically scores the user's answers and provides feedback on the learning results in real time. The input is the user's test answers, and the output is the scoring results and feedback information. Specifically, the server analyzes the answer data, performs automatic scoring, and provides feedback based on the score and level of understanding.

[0261] Step 7:

[0262] The server manages multiple educational goal settings and enables the provision of curricula from other educational institutions. The input is the curriculum data from other educational institutions and the user's curriculum selection, and the output is the video and test for the selected curriculum. Specifically, the server retrieves the selected curriculum from the database and delivers it to the user.

[0263] Step 8:

[0264] The user selects and takes a curriculum from another educational institution. The input is the user's curriculum selection, and the output is learning content and test answers based on the curriculum from the other educational institution. Specifically, the user searches for the target grade, subject, and educational institution name, views the provided curriculum, and takes the test.

[0265] The above are the specific processing steps of the system program that realizes this application example.

[0266] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0267] This invention is a teacher replacement AI system that uses artificial intelligence (AI), interactive video content, and emotion recognition technology to improve the quality of education. The system collects a huge amount of teaching material data and uses generative AI to automatically generate a curriculum based on the educational goals set by each educational institution. It also has an emotion engine that recognizes users' emotions in real time and personalizes the learning experience. Below, we will explain each major component of the system and how it works.

[0268] 1. Curriculum setting and data collection

[0269] User (School Administrator):

[0270] Users (school administrators) input educational goals (learning objectives and curriculum requirements) into the system and upload teaching material data such as textbooks, past exam questions, and other teaching materials.

[0271] Device:

[0272] The terminal transmits the information input by the school administrator to the server and uploads the teaching material data to the server.

[0273] server:

[0274] The server receives the educational goal settings and teaching material data, analyzes them, and stores them in a database. Specifically, it performs text analysis, extracts keywords and important points, and converts them into a format that is easy to search.

[0275] 2. Curriculum generation and animation

[0276] server:

[0277] The server uses generative AI to automatically generate a curriculum based on educational goals, including setting the learning sequence and selecting learning topics.

[0278] server:

[0279] The server then creates video content based on the generated curriculum. Specifically, it generates slides based on text information and adds narration using a speech synthesis engine. At the same time, it sets up educational test questions at the end of each topic.

[0280] 3. Real-time feedback from an emotion engine

[0281] server:

[0282] The server uses an emotion engine to recognize the user's emotions in real time, adjust the difficulty of educational tests based on the emotion data, and provide feedback according to the user's learning progress. The emotion engine identifies the user's emotions using facial expression analysis, voice analysis, behavior analysis, etc.

[0283] 4. Video content and test distribution

[0284] server:

[0285] The server uploads the generated video content and educational tests to the streaming server and generates links for each. These links are organized by semester and subject.

[0286] server:

[0287] The server distributes the viewing link to the user terminal. Specifically, it sends the viewing link to the terminal of the registered student, allowing them to start learning.

[0288] 5. Student viewing and testing

[0289] User (student):

[0290] The user (student) clicks on the provided link to watch the video, answers the test questions inserted in the video while watching, and sends the answers to the system.

[0291] 6. Feedback on learning results

[0292] server:

[0293] The server automatically scores the received answers and analyzes the accuracy rate and level of understanding. The results are fed back to the user's (student's) dashboard as learning results. Specifically, the score, mistakes, topics requiring additional study, etc. are displayed. Emotional data is also reflected in the learning results, personalizing the learning experience.

[0294] 7. Customization and participation in other educational institutions' curricula

[0295] User (student):

[0296] Users (students) can select and take courses from other educational institutions by searching for the relevant grade, subject, and educational institution name, and then watching videos and taking tests based on the provided curriculum.

[0297] server:

[0298] The server provides selected users with videos and tests from other educational institutions' curricula and records their learning progress.

[0299] Specific examples

[0300] For example, suppose an educational administrator at School A sets up a "second-semester mathematics curriculum" and uploads related textbooks and past exam questions. The server receives this and uses generative AI to automatically generate lectures such as "Fundamentals of Equations" and "Probability Calculations." Test questions are inserted at the end of each chapter to check comprehension. Users (students) watch these videos on their devices and answer each test. The server automatically scores the answers and provides real-time feedback. At the same time, an emotion engine recognizes the user's (student's) current emotions and adjusts the difficulty level or sends encouraging messages to further personalize the learning experience. In some cases, students can also take an excellent mathematics curriculum from another school, School B, and the server provides videos and tests accordingly.

[0301] In this way, the educational system of the present invention supports efficient learning while improving the quality of education, reduces the burden on teachers, and contributes to eliminating educational disparities.The introduction of an emotion engine is designed to make the user's learning experience more comfortable and effective.

[0302] The processing flow will be explained below.

[0303] Step 1:

[0304] User (School Administrator):

[0305] The user (school administrator) inputs educational goals (learning objectives and curriculum requirements) into the system. Specifically, they input information such as the grade, subject, learning objectives for the semester, and key learning items, and then send this information to the system.

[0306] Step 2:

[0307] User (School Administrator):

[0308] Users (school administrators) select textbooks, past exam papers, and other educational material data and upload them to the system. The uploaded data becomes the basis for generating educational content.

[0309] Step 3:

[0310] Device:

[0311] The terminal transmits the educational goal setting sent from the school administrator and the uploaded teaching material data to the server.

[0312] Step 4:

[0313] server:

[0314] The server receives the educational goal settings and teaching material data and stores them in a database. Specifically, it extracts, organizes, and stores keywords and important points related to the educational goals.

[0315] Step 5:

[0316] server:

[0317] The server uses generative AI to automatically generate a curriculum based on the received educational goal settings, including selecting the necessary topics and setting the learning sequence.

[0318] Step 6:

[0319] server:

[0320] The server creates video content based on the generated curriculum. Specifically, it generates slides based on text information and adds narration using a speech synthesis engine. At this time, it is also possible to use an emotion engine to gauge the user's emotional reactions and insert messages to boost motivation at appropriate times.

[0321] Step 7:

[0322] server:

[0323] The server inserts interactive test questions into the video, providing questions and problems at key points in the video to check comprehension, and adjusts the difficulty of the test based on the user's emotional data.

[0324] Step 8:

[0325] server:

[0326] The server uploads the generated video content and tests to a streaming server and generates viewing links, organized by semester and subject.

[0327] Step 9:

[0328] server:

[0329] The server distributes the viewing link to the user's device. The link is sent to the device of the registered student to promote learning.

[0330] Step 10:

[0331] User (student):

[0332] The user (student) clicks on the provided link to watch the video. While watching, they answer test questions inserted in the video and send their answers to the system. The system recognizes emotions from the user's behavior and facial expressions while watching, and provides appropriate motivational and encouraging messages.

[0333] Step 11:

[0334] Device:

[0335] The device sends the user's (student's) answers to the server, along with emotional data in real time, for automatic grading.

[0336] Step 12:

[0337] server:

[0338] The server automatically scores the received answers and analyzes the accuracy rate and level of understanding. The results are fed back to the user's (student's) dashboard as learning results. Emotional data is also included in the feedback to personalize the learning experience.

[0339] Step 13:

[0340] User (student):

[0341] Students can check their learning results on the dashboard and re-learn topics they have not fully understood. They can also select and take courses from other educational institutions if they wish.

[0342] Step 14:

[0343] server:

[0344] The server provides selected users with videos and tests from other educational institutions' curricula and records their learning progress. By allowing users to take high-quality curricula from other educational institutions, the quality of education is improved.

[0345] Through this series of steps, the system provides an efficient and high-quality learning environment, reducing the burden on teachers while enabling education that meets the needs of each learner. The introduction of an emotion engine makes it possible to maintain learner motivation and provide a personalized learning experience.

[0346] Example 2

[0347] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0348] Conventional educational systems place a heavy burden on individual teachers, making it difficult to provide personalized education that takes into account individual learning styles and progress. They also struggle with real-time feedback using emotion recognition and the flexible use of curricula from other educational institutions. Furthermore, there is a lack of technology to efficiently manage large amounts of teaching material data and automatically generate optimal curricula.

[0349] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0350] In this invention, the server includes means for storing a huge amount of teaching material data in a database, means for automatically generating a curriculum based on educational goals using a generative AI model, means for generating slides from text information and generating video content by adding narration using a speech synthesis engine, means for recognizing a user's emotions in real time using an emotion engine and providing feedback based on the user's learning progress, means for automatically scoring the user's answers and providing feedback on the learning results, and means for managing multiple educational goal settings and enabling the provision of curricula from other educational institutions. This makes it possible to provide personalized education according to each user's learning style and progress, thereby improving the quality of education.

[0351] "Huge amounts of educational material data" refers to a wide variety of educational materials and digital content, and the amount is extremely large, detailed, and comprehensive.

[0352] A "generative AI model" refers to a technology that uses artificial intelligence to automatically create curricula and learning plans based on user input data and requirements.

[0353] "Educational goals" are learning objectives and goals set by the user (school administrator), and serve as the basis for curriculum and lesson plans.

[0354] "Text information" refers to character data such as sentences and keywords contained in the teaching material data.

[0355] "Slides" are presentation-style materials used as part of educational content, and are primarily used to provide visual information.

[0356] A "speech synthesis engine" refers to a system or software that provides the technology to convert text data into artificially generated voice data.

[0357] "Video content" refers to educational video information provided through a combination of slides and audio narration.

[0358] An "emotion engine" refers to a technology that analyzes a user's facial expressions, voice, actions, etc. to recognize emotions and provide that information to the system.

[0359] "User terminal" refers to a device (e.g., PC, tablet, smartphone, etc.) that a user uses to access the educational system and view educational content or take tests.

[0360] A "streaming server" refers to a network server that distributes digital data such as video content and test questions in real time.

[0361] "Real-time awareness" refers to the system's ability to respond immediately to user input and actions, providing appropriate feedback and adjustments on the spot.

[0362] "Automatic scoring" refers to a technology in which the system automatically evaluates the answers submitted by the user and calculates the score and percentage of correct answers.

[0363] "Feedback" refers to information such as evaluations, advice, and corrections provided to users based on their learning progress and results.

[0364] "Educational goal setting" refers to the process in which a user registers predetermined learning goals in the system and creates a learning plan based on those goals.

[0365] "Curriculum of other educational institutions" refers to the learning plans and lesson contents provided by educational institutions other than the educational institution using the system.

[0366] "Personalization" refers to optimizing the educational content and feedback provided according to the characteristics and needs of each individual user.

[0367] This invention is an educational system that uses artificial intelligence (AI), interactive video content, and emotion recognition technology to improve the quality of education. The system collects a huge amount of educational material data and uses a generative AI model to automatically generate a curriculum based on the educational goals set by each educational institution. It also has an emotion engine that recognizes users' emotions in real time and personalizes the learning experience.

[0368] The hardware required to implement the system includes a server, a user terminal, and a streaming server. The software required includes a generative AI model (e.g., software dedicated to generative AI), a text analysis library (e.g., an NLP library), and a speech synthesis engine (e.g., a speech synthesis API).

[0369] First, the user (school administrator) enters educational goals into the system and uploads the corresponding teaching material data. The device then sends this information to the server. The server then analyzes the received educational goals and teaching material data. Specifically, it uses a Python NLP library to perform text analysis, extracting keywords and important points and storing them in a database.

[0370] The server then automatically generates a curriculum using a generative AI model. For example, GPT-4 is used as the generative AI model. The generated curriculum includes setting the learning order and selecting learning topics. The server then creates video content based on the curriculum. PowerPoint slides are generated from the text information and narration is added using a speech synthesis engine. These are then integrated using video editing software such as FFmpeg to generate the video content. At the same time, educational test questions are set at the end of each topic.

[0371] The generated video content is uploaded to a streaming server, and a viewing link is generated. The server distributes this link to the user's device. The user (student) uses the provided link to watch the video, answer the embedded test questions, and send the answers to the server. The server uses an auto-grader library to automatically grade the received answers. Feedback is displayed on the user's (student's) dashboard based on the correct answers and level of understanding. Emotional data generated by an emotion engine is also taken into account in the feedback.

[0372] The emotion engine uses Microsoft Azure Emotion API and other tools to analyze facial expressions, voice, and behavior in real time to recognize the user's emotions. For example, it can suggest taking a break if the user is tired, or adjust the difficulty of learning if the user is highly motivated.

[0373] The system also manages multiple educational goal settings and can provide curricula from other educational institutions. Users (students) can search for, view, and take courses from other educational institutions. The server provides videos and tests corresponding to the selected curriculum and records the student's learning progress.

[0374] Specific examples

[0375] For example, suppose an educational administrator at School A sets up a "second-semester mathematics curriculum" and uploads related textbooks and past exam questions. The server receives this and uses a generative AI model (e.g., GPT-4) to automatically generate lectures such as "Fundamentals of Equations" and "Probability Calculations." Test questions are inserted into the generated videos at the end of each chapter to check comprehension. Users (students) watch these videos on their devices and answer each test. The server automatically scores the answers and provides feedback in real time. At the same time, an emotion engine recognizes the user's (student's) current emotions and personalizes the learning experience by adjusting the difficulty level and sending encouraging messages.

[0376] Prompt Sentence Examples

[0377] "Generate a second-semester mathematics curriculum based on the following criteria. Coverage includes basic equations and probability calculations. Also, include test questions at the end of each chapter to assess understanding."

[0378] The introduction of this system is expected to improve the quality of education, support efficient learning, reduce the burden on teachers, and contribute to eliminating educational disparities.

[0379] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0380] Step 1:

[0381] User (school administrator)

[0382] Operation: A user logs in to the system, inputs an educational goal (e.g., "Second semester mathematics curriculum"), and uploads the corresponding teaching material data (textbooks, past exam questions) to the system.

[0383] Input: Educational goals, textbook file, past exam question file.

[0384] Output: The educational goals and teaching material data are uploaded and sent to the server.

[0385] Step 2:

[0386] Terminal

[0387] Operation: The device sends the entered educational goals and teaching material data to the server. When the user presses the upload button, the data is sent via an HTTP POST request.

[0388] Input: Educational goals, textbook files, and past exam files entered by the user into the terminal.

[0389] Output: The educational goals and teaching material data are sent to the server.

[0390] Step 3:

[0391] server

[0392] Operation: The server analyzes the received educational goals and teaching material data. It uses a Python NLP library (e.g., spaCy) to perform text analysis and extract keywords and key points. The analysis results are stored in a database.

[0393] Input: Educational goals, teaching material data (textbook files, past exam files).

[0394] Output: Analysis results (keywords, important points) are stored in a database.

[0395] Step 4:

[0396] server

[0397] Operation: The server automatically generates a curriculum using a generative AI model (e.g., GPT-4) based on the analysis results. A prompt sentence is input to the generative AI model to generate the curriculum.

[0398] Input: Analysis result, prompt statement.

[0399] Output: Auto-generated curriculum.

[0400] Step 5:

[0401] server

[0402] How it works: The server creates video content based on the generated curriculum, using text information to generate slides with Python's PPTX library, creating narration with Google Text-to-Speech API, and integrating them with FFmpeg.

[0403] Input: Auto-generated curriculum,text information.

[0404] Output: The generated video content.

[0405] Step 6:

[0406] server

[0407] Operation: The server uploads the generated video content and educational test to the streaming server and generates a viewing link, which is then sent to the user's device.

[0408] Input: Generated video content, educational tests.

[0409] Output: Viewing link.

[0410] Step 7:

[0411] User (student)

[0412] How it works: Users watch the video using the provided viewing link and answer the test questions inserted within the video. Their answers are then sent to the system.

[0413] Input: Viewing link, answers to test questions.

[0414] Output: User response data.

[0415] Step 8:

[0416] Terminal

[0417] Operation: The terminal sends the user's answer data to the server. When the user presses the "Send Answer" button, the answer data is sent via an HTTP POST request.

[0418] Input: User response data.

[0419] Output: The answer data is sent to the server.

[0420] Step 9:

[0421] server

[0422] How it works: The server automatically scores the received answer data and analyzes the level of understanding and the percentage of correct answers. It uses the Python auto-grader library to perform the scoring and analysis. It then provides real-time feedback to the user's dashboard. The feedback includes emotional data obtained using an emotion engine.

[0423] Input: Response data, emotion data.

[0424] Output: Marking results and feedback.

[0425] Step 10:

[0426] User (student)

[0427] How it works: Users can select and take courses from other educational institutions. They select their grade and subject on the system, watch videos based on the curriculum provided, and take tests.

[0428] Input: Institutional curriculum choices.

[0429] Output: Viewing and testing data.

[0430] Step 11:

[0431] server

[0432] How it works: The server provides users with selected curriculum videos and tests from other educational institutions, records their learning progress, and provides feedback.

[0433] Input: Institution curriculum, user progress data.

[0434] Output: curriculum videos, tests, progress feedback.

[0435] (Application example 2)

[0436] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0437] Traditional education systems often have uniform curricula and content, and do not adequately personalize content based on individual students' learning progress or emotions. They also lack interactive feedback and mechanisms for students to actively participate, making it difficult to maximize learning outcomes. Furthermore, they lack the flexibility to easily use curricula from other educational institutions.

[0438] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0439] In this invention, the server includes means for storing a huge amount of educational material data in a database, means for automatically generating a curriculum based on educational goals using a generation AI, means for generating video content and inserting educational tests into the videos, means for distributing the generated video content to user terminals, means for automatically scoring user answers and providing feedback on learning results, means for managing multiple educational goal settings and enabling the provision of curricula from other educational institutions, means including an emotion engine for recognizing user emotions in real time and adjusting the difficulty of educational tests based on that data, and means for providing an interactive educational experience related to the educational material. This makes it possible to provide a learning experience optimized for each user, thereby improving motivation to learn and understanding.

[0440] A "server" is a computing device that provides and manages data over a network.

[0441] A "database" is an information system for efficiently storing, managing, and searching large amounts of data.

[0442] "Generative AI" is a general term for artificial intelligence technology that automatically generates new information based on given conditions and data.

[0443] "Educational goals" are the objectives or results to be achieved through educational activities.

[0444] "Curriculum" means a set of educational content or learning plan.

[0445] "Video content" refers to dynamic video data that provides information through visual and audio means.

[0446] "Educational testing" refers to exams and quizzes used to assess a learner's understanding or proficiency.

[0447] "User terminal" refers to a computer or mobile device that is directly used by a user.

[0448] An "emotion engine" is a software technology that analyzes a user's facial expressions, voice, etc. and recognizes their emotional state.

[0449] An "interactive educational experience" is a learning activity in which users actively participate and interact with information.

[0450] This invention is an educational system that uses artificial intelligence (AI), interactive video content, and emotion recognition technology. This system collects a huge amount of educational material data and uses generative AI to automatically generate curricula based on the educational goals set by each educational institution. It also has an emotion engine that recognizes users' emotions in real time to personalize the learning experience.

[0451] The server stores a huge amount of teaching material data in a database, analyzes it, and converts it into an easily searchable format. The user (school administrator) inputs educational goals (learning objectives and curriculum requirements) into the system and uploads teaching material data such as books, past exam questions, and other teaching materials. The terminal sends this input information to the server, which analyzes it and stores it in the database. As a concrete example, a school administrator can set up a "second semester mathematics curriculum" and upload related books and past exam questions.

[0452] The server then uses generative AI to automatically generate a curriculum based on educational goals, and creates video content based on the generated curriculum. This video includes the setting of the learning order and the selection of learning topics, and narration is added using a speech synthesis engine. Educational test questions are set at the end of each topic. The generated video content is uploaded to a streaming server, and links organized by semester and subject are generated. These viewing links are distributed to registered user devices.

[0453] Users (students) click these links to watch the videos and answer the test questions inserted in the videos. The server automatically scores the answers and provides feedback on the learning results. Specifically, the user's (student's) dashboard displays the learning results, such as the score, mistakes made, and topics requiring additional study.

[0454] Furthermore, the present invention utilizes an emotion engine to recognize user emotions in real time and personalize the learning experience based on the emotion data. Specifically, the system uses facial, voice, and behavioral analysis to identify user emotions, and then adjusts the difficulty of educational tests and provides real-time feedback and encouraging messages based on the identified emotions. The system utilizes hardware and software such as OpenAI API, TensorFlow, OpenCV, and gTTS.

[0455] As a concrete example, imagine a situation where you want to send an encouraging message to a user (student) while they are viewing learning materials, such as "You will succeed." Examples of prompt sentences that can be used include the following:

[0456] "The student seems frustrated. Give encouraging words."

[0457] "Don't give up! You are doing great! Keep going and you will succeed."

[0458] In this way, the educational system of the present invention improves the quality of education, supports efficient learning, reduces the burden on teachers, and contributes to eliminating educational disparities.The introduction of an emotion engine is designed to make the user's learning experience more comfortable and effective.

[0459] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0460] Step 1:

[0461] The server receives educational goals (learning objectives and curriculum requirements) as input from the user (school administrator), and also uploads related educational material data (textbooks, past exam questions, etc.) to the database. This allows the educational goal settings and educational material data to be stored in the database. Specific operations include performing text analysis and extracting important keywords and points.

[0462] Step 2:

[0463] The server automatically generates a curriculum based on the generative AI model using the educational goals and teaching material data stored in the database. The server uses the educational goals and teaching material data as input and obtains the generated curriculum as output. Specific operations include setting the learning order and selecting learning topics.

[0464] Step 3:

[0465] The server generates video content based on the generated curriculum and inserts educational tests into the video. Using the generated curriculum as input, the server creates video content as output. Specifically, the server generates slides based on text information and adds narration using a speech synthesis engine (such as gTTS).

[0466] Step 4:

[0467] The server uploads the generated video content to the streaming server and generates a viewing link for each video. The generated video content is used as input and a viewing link is obtained as output. Specific operations include file upload processing and link generation.

[0468] Step 5:

[0469] The server distributes the viewing link to the user's device and allows the user (student) to begin learning. The viewing link is used as input and confirmation of link distribution is output. Specifically, the server sends the link to the user via email or a notification system.

[0470] Step 6:

[0471] The user (student) clicks on the provided link to watch the video and answers the test questions inserted in the video while watching. The viewing link and the user's answers are used as input, and the answer results are obtained as output. Specific operations include playing the video and submitting the test answers.

[0472] Step 7:

[0473] The server automatically scores the user's answers and provides feedback on the learning results. It uses the user's answer data as input and obtains feedback results as output. Specifically, it analyzes and automatically scores the answers, and displays the scores and analysis results of the level of understanding on a dashboard.

[0474] Step 8:

[0475] The server uses an emotion engine to recognize the user's emotions in real time and adjusts the level of difficulty and feedback based on that data. It uses the user's facial images and voice data as input, and obtains emotion analysis results and feedback as output. Specifically, it performs facial expression analysis (OpenCV) and voice analysis, and uses the OpenAI API to generate encouraging messages and other prompts.

[0476] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0477] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0478] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0479] [Second embodiment]

[0480] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0481] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0482] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0483] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0484] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0485] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0486] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0487] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0488] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0489] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0490] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0491] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0492] This invention is a teacher replacement AI system that uses artificial intelligence (AI) and interactive video content to improve the quality of education. This system has the ability to collect a huge amount of teaching material data and use generative AI to automatically generate a curriculum based on the educational goals set by each educational institution. Below, we will explain each major component of this system and how it works.

[0493] 1. Curriculum setting and data collection

[0494] User (School Administrator):

[0495] School administrators input educational goals (learning objectives and curriculum requirements) and upload teaching material data such as textbooks, past exam questions, and other teaching materials.

[0496] Device:

[0497] The terminal transmits the information input by the school administrator to the server and uploads the teaching material data to the server.

[0498] server:

[0499] The server receives the educational goal settings and teaching material data, analyzes them, and stores them in a database. Specifically, it performs text analysis to extract keywords and important points.

[0500] 2. Curriculum generation and animation

[0501] server:

[0502] The server uses AI to automatically generate a curriculum based on educational goals. Video content is then created based on the generated curriculum. Slides are generated based on text information, and narration is added using a speech synthesis engine. Educational test questions are also inserted into the video to add interactivity.

[0503] 3. Video content and test distribution

[0504] server:

[0505] The server uploads the generated video content and educational tests to the streaming server and generates links for each. The links are organized by semester and subject and provided to students' devices.

[0506] 4. Students listen and take the test

[0507] User (student):

[0508] Students click on the provided link to watch the video content, answer the test questions inserted in the video, and send their answers from their device to the server.

[0509] 5. Feedback on learning results

[0510] server:

[0511] The server automatically scores the answers received and analyzes the accuracy rate and level of understanding. The learning results are then fed back to the student's dashboard, which displays the score, mistakes made, and topics requiring additional study.

[0512] 6. Customization and participation in other educational institutions' curricula

[0513] User (student):

[0514] Students can select and take courses from other educational institutions by searching for the relevant grade, subject, and educational institution, and then watching videos and taking tests based on the provided curriculum.

[0515] server:

[0516] The server provides videos and tests for the selected curriculum and records the student's learning progress.

[0517] Specific examples

[0518] For example, suppose an educational administrator at School A sets up a "second-semester mathematics curriculum" and uploads related textbooks and past exam questions. The server receives this and uses generative AI to automatically generate lectures such as "Fundamentals of Equations" and "Probability Calculations." Test questions are inserted at the end of each chapter in the generated videos to check comprehension. Students watch these videos on their devices and answer each test. The server automatically grades the answers and provides feedback in real time. In some cases, students can also take an excellent mathematics curriculum from another school, School B, and the server provides them with corresponding videos and tests.

[0519] In this way, the educational system of the present invention supports efficient learning while improving the quality of education, and also contributes to eliminating educational disparities.

[0520] The processing flow will be explained below.

[0521] Step 1:

[0522] User (School Administrator):

[0523] The user (school administrator) inputs educational goals (learning objectives and curriculum requirements) into the system. Specifically, they enter information such as the grade, subject, learning objectives for the semester, and key learning items, and then send it to the system.

[0524] Step 2:

[0525] User (School Administrator):

[0526] Users (school administrators) select textbooks, past exam papers, and other teaching material data and upload them to the system, which is then added to the system's teaching material database.

[0527] Step 3:

[0528] Device:

[0529] The terminal transmits the educational goal setting sent by the user and the uploaded teaching material data to the server.

[0530] Step 4:

[0531] server:

[0532] The server analyzes the received educational goal settings and teaching material data and stores them in a database. Specifically, it performs text analysis, extracts keywords and important points, and converts them into a format that is easy to search.

[0533] Step 5:

[0534] server:

[0535] The server uses generative AI to automatically generate a curriculum based on educational goals, including setting the learning sequence and selecting learning topics.

[0536] Step 6:

[0537] server:

[0538] The server then creates video content based on the generated curriculum. Specifically, it generates slides based on text information and adds narration using a speech synthesis engine. At the same time, it sets up educational test questions at the end of each topic.

[0539] Step 7:

[0540] server:

[0541] The server uploads the generated videos and tests to a streaming server and generates viewing links, organized by semester and subject.

[0542] Step 8:

[0543] server:

[0544] The server distributes the viewing link to the user terminal. Specifically, it sends the viewing link to the terminal of the registered student, allowing them to start learning.

[0545] Step 9:

[0546] User (student):

[0547] The user (student) clicks on the provided link to watch the video, answers the test questions inserted in the video while watching, and sends the answers to the system.

[0548] Step 10:

[0549] Device:

[0550] The terminal sends the user's (student's) answers to the server, which then sends the answers in real time and automatically grades them.

[0551] Step 11:

[0552] server:

[0553] The server automatically scores the received answers and analyzes the accuracy rate and level of understanding. The results are fed back to the user's (student's) dashboard as learning results.

[0554] Step 12:

[0555] User (student):

[0556] Students can check their learning results on the dashboard and re-learn topics they have not fully understood. They can also select and take courses from other educational institutions if they wish.

[0557] Step 13:

[0558] server:

[0559] The server provides selected users with videos and tests from other educational institutions' curricula and records their learning progress, allowing users to take high-quality curricula from other educational institutions and improve the quality of their education.

[0560] Through this series of steps, the system can provide an efficient and high-quality learning environment, reduce the burden on teachers, and contribute to eliminating educational disparities.

[0561] Example 1

[0562] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0563] In conventional educational systems, the provision of teaching materials and feedback on learning results was not done in real time, resulting in issues with student learning efficiency. It was also difficult to automatically generate curricula based on educational goals, and it was difficult to share resources across multiple educational institutions. Furthermore, content that lacked interactivity made it difficult to maintain students' interest, which tended to reduce learning effectiveness.

[0564] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0565] In this invention, the server includes a means for storing a large amount of teaching material data in a database, a means for automatically generating a curriculum based on educational goals using a generative AI, a means for inputting prompts into a generative AI model and creating video content based on the curriculum, a means for inserting educational tests into the videos, a means for distributing the generated video content and educational tests to a user terminal, a means for automatically scoring user answers and providing real-time feedback on learning results, and a means for managing multiple educational goal settings and enabling the provision of curricula from other educational institutions. This enables real-time feedback on learning results, automatic generation of a curriculum based on educational goals, and resource sharing among multiple educational institutions. Furthermore, highly interactive content can maintain student interest and improve learning effectiveness.

[0566] "Vast amounts of educational material data" refers to the large amount of electronic data used for education, such as textbooks, past exam questions, and supplementary materials.

[0567] A "database" refers to a system for efficiently storing, managing, searching, and using information.

[0568] "Generative AI" refers to artificial intelligence that automatically generates natural language, images, curriculum, and more based on input data.

[0569] An "educational goal" refers to a specific objective or purpose that a student should achieve through a particular learning process.

[0570] "Curriculum" refers to learning content and educational programs that are systematically constructed based on educational goals.

[0571] A "generative AI model" refers to an artificial intelligence algorithm that learns from diverse data and generates new data and content based on that knowledge.

[0572] A "prompt sentence" refers to an input sentence that elicits a specific response or output from a generative AI model.

[0573] "Video Content" refers to educational materials in video format created for educational purposes.

[0574] "Educational test" refers to an assessment tool that includes questions designed to assess a learner's understanding and knowledge retention.

[0575] "User terminal" refers to electronic devices such as PCs, smartphones, and tablets that learners and educational institution administrators use to access and operate the system.

[0576] "Automatic scoring" refers to the process by which a system automatically evaluates and scores submitted test answers.

[0577] "Real-time feedback" refers to responding immediately to a user's actions and answers, and providing learning results and evaluations immediately.

[0578] "Setting multiple educational goals" refers to the ability of different learners and grade levels to have different educational goals and to manage these multiple goals simultaneously.

[0579] "Curriculum of other educational institutions" refers to educational programs and learning content offered at other schools or educational facilities.

[0580] This invention is a teacher replacement AI system that uses artificial intelligence (AI) and interactive video content to improve the quality of education. Specific implementation methods of this system are described below.

[0581] Curriculum setting and data collection

[0582] User (School Administrator):

[0583] School administrators log in to the system and enter educational goals (learning objectives and curriculum requirements) into an input form on a terminal. They also upload related educational material data, such as textbooks, past exam questions, and supplementary materials, to the system. Specifically, they use a web browser to perform operations from the management dashboard.

[0584] Device:

[0585] The device receives the user's input information and uploaded files and sends them to the server. The device can be a PC, tablet, smartphone, etc. This information is temporarily stored on the device, encrypted, and then sent to the server.

[0586] server:

[0587] The server receives the educational goals and teaching material data sent from the device. The received data is then analyzed to extract educational keywords and key points, which are then stored in a database. The software used includes a natural language processing (NLP) engine, which analyzes a PDF file, such as "math textbook.pdf," to extract keywords like "equation" and "probability."

[0588] Curriculum generation and animation

[0589] server:

[0590] The server automatically generates a curriculum using a generative AI model (such as GPT-3 or BERT) based on the analyzed data and the input educational goals. A prompt is input into the generative AI model to generate an appropriate curriculum. An example of a prompt is, "Generate an environmental science curriculum for second-year high school students based on the following Sustainable Development Goals (SDGs). Provide the following materials as teaching material data: textbook (title: Earth Environmental Science, 2nd Edition), past exam questions (period: past five years), and other supplementary materials (title: Science for a Sustainable Future). The curriculum should also include interactive test questions."

[0591] Video content is created based on the generated curriculum. Specifically, slides are generated using presentation software, narration is added using a speech synthesis engine (e.g., Google Cloud Text-to-Speech), and educational test questions are added to the video to make it interactive.

[0592] Video content and test delivery

[0593] server:

[0594] The server uploads the created video content and educational tests to the streaming server, generates links for each piece of content, organizes them by semester and subject, and stores them in a database, allowing students to easily access the content.

[0595] Students listen and take the test

[0596] User (student):

[0597] Students click on the provided link on their device (PC, tablet, smartphone) to watch the video content. The video also includes educational tests, and they can answer interactive tests in real time according to their learning progress.

[0598] Feedback on learning results

[0599] server:

[0600] The server uses software to automatically score the test answers submitted by students. The automatic scoring is done using machine learning algorithms (e.g., Scikit-learn) to instantly analyze the percentage of correct answers and level of understanding. The results are immediately fed back to the student's dashboard, and further study advice is provided depending on the level of understanding.

[0601] Customization and access to other educational institutions' curricula

[0602] User (student):

[0603] Students can select and take courses offered by other educational institutions by searching for the relevant grade, subject, and educational institution name, and then taking the provided curriculum videos and tests.

[0604] server:

[0605] The server provides videos and tests for selected curriculum and records students' learning progress, allowing them to improve the quality of their education and contributing to eliminating educational disparities.

[0606] The educational system of the present invention supports efficient learning while improving the quality of education, and is of great help in eliminating educational disparities.

[0607] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0608] Step 1: Setting up the curriculum and inputting teaching material data

[0609] User (School Administrator):

[0610] School administrators log in to the system and input educational goals (learning objectives and curriculum requirements) into an input form on their terminal. They also upload related educational material data, such as textbooks, past exam papers, and supplementary materials, to the system. The input information and uploaded data become input. The system then receives the educational goals and educational material data.

[0611] Specific behavior:

[0612] Access the management dashboard and enter your educational goals (e.g., "Second semester math curriculum").

[0613] Upload files such as textbooks (e.g., "Mathematics textbook.pdf") and past exam questions (e.g., "Past exam questions.zip").

[0614] Step 2: Send data from the device to the server

[0615] Device:

[0616] The information entered by the user and the files uploaded are temporarily stored inside the device. This information is then encrypted and securely sent to the server. The input is the user's input information and uploaded data, and the output is the encrypted data to be sent.

[0617] Specific behavior:

[0618] The device encrypts educational goals and teaching material data.

[0619] The encrypted data is sent to the server.

[0620] Step 3: Receiving and analyzing the teaching material data

[0621] server:

[0622] The server receives the educational goals and teaching material data sent from the device. It performs text analysis on the received data and extracts educational keywords and important points. The results of this analysis are input, and the information stored in the database is output.

[0623] Specific behavior:

[0624] The server receives "MathematicsTextbook.pdf".

[0625] Using software (NLP engine), keywords such as "equation" and "probability" are extracted.

[0626] The extracted information is stored in a database.

[0627] Step 4: The curriculum generation process

[0628] server:

[0629] The server automatically generates a curriculum using a generative AI model based on the analyzed data and the input educational goals. At this time, a prompt sentence is input into the generative AI model, and an appropriate curriculum is output.

[0630] Specific behavior:

[0631] Enter a prompt into the generative AI model: "Generate an environmental science curriculum for second-year high school students based on the following Sustainable Development Goals (SDGs). Provide the following materials as teaching material data: textbook (title: Earth Environmental Science, 2nd Edition), past exam papers (period: past five years), and other supplementary materials (title: Science for a Sustainable Future). The curriculum should also include interactive test questions."

[0632] Receive and save the generated curriculum.

[0633] Step 5: Create video content

[0634] server:

[0635] The server creates video content based on the generated curriculum. Slides are generated using presentation software, and narration is added using a speech synthesis engine. Educational test questions are also interactively inserted into the video. The input is the generated curriculum, and the output is the completed video content.

[0636] Specific behavior:

[0637] Create slides: "Basics of Equations," "Calculating Probability," etc.

[0638] Add narration using a text-to-speech engine.

[0639] Educational tests are included for each chapter.

[0640] Step 6: Deliver content and tests

[0641] server:

[0642] The generated video content and educational tests are uploaded to a streaming server, and links are generated for each piece of content. These links are organized by semester and subject and stored in a database. The input is the completed video content, and the output is the provided link.

[0643] Specific behavior:

[0644] Upload the video file (e.g. "Basics of Equations.mp4" or "Probability Calculations.mp4") to the streaming server.

[0645] Each video link is generated and stored in an organized database.

[0646] Step 7: Students watch and take the test

[0647] User (student):

[0648] Students click the provided link on their device (PC, tablet, smartphone) to watch the video content and answer the interactive educational test inserted in the video. The input is the provided link and the student's viewing behavior, and the output is the submitted test answer.

[0649] Specific behavior:

[0650] The student clicks on the provided link: https: / / example.com / equations and watches the video.

[0651] Answer the test questions that appear while watching the video and submit your answers.

[0652] Step 8: Marking and feedback on answers

[0653] server:

[0654] The server uses an automatic scoring algorithm to evaluate test answers submitted by students. It analyzes the accuracy rate and level of understanding and provides real-time feedback to the student's dashboard. The input is the submitted test answers, and the output is the analysis results and feedback.

[0655] Specific behavior:

[0656] Test answers are graded using machine learning algorithms (e.g., Scikit-learn).

[0657] Correct answer rate and level of understanding are analyzed, and learning results are displayed on a dashboard.

[0658] Step 9: Selecting a curriculum from another institution

[0659] User (student):

[0660] Students can select and take courses offered by other educational institutions by searching for the target grade, subject, and educational institution name, watching videos based on the offered curriculum, and taking tests. The input is the search query, and the output is a link to the selected curriculum.

[0661] Specific behavior:

[0662] A student uses the search form to search for "School B's 3rd semester physics curriculum" and selects to take the course.

[0663] Step 10: Delivering curriculum and recording learning progress

[0664] server:

[0665] The server provides videos and tests for the selected curriculum and records the student's learning progress. The input is the link to the selected curriculum, and the output is the provided learning materials and recorded progress data.

[0666] Specific behavior:

[0667] We provided students with a video link and test for the "Physics curriculum for the third term at School B" that they selected.

[0668] Record student learning progress and display it on a dashboard.

[0669] (Application example 1)

[0670] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0671] Traditional educational systems require a lot of manual work, from setting up and generating curriculum to creating video content, and then distributing and providing feedback to students, making it difficult to provide efficient and effective education. Furthermore, low interactivity meant that students' motivation and comprehension were not sufficiently improved. Furthermore, it was difficult to provide real-time feedback or share curricula from other educational institutions, which could exacerbate educational disparities.

[0672] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0673] In this invention, the server includes means for storing a huge amount of teaching material data in a database, means for automatically generating a curriculum based on educational goals using a generation AI, means for generating video content and inserting educational tests into the videos, means for distributing the generated video content to user terminals, means for automatically scoring user answers and providing feedback on learning results, means for managing multiple educational goal settings and enabling the provision of curricula from other educational institutions, and means for real-time lecture viewing and interactive testing using smart wearable devices. This enables the provision of efficient and effective education and improves students' motivation to learn and their level of understanding.

[0674] "Teaching material data" refers to digital textbooks, past exam papers, and other learning materials used by teachers and educational institutions for educational purposes.

[0675] "Generative AI" refers to a system that uses artificial intelligence technology to automatically generate curriculum and educational content based on input data.

[0676] "Automatic curriculum generation" refers to the process in which generative AI automatically creates learning plans and course content based on the educational goals set by educational institutions.

[0677] "Video content" refers to educational multimedia files that combine audio, video, slides, etc.

[0678] "Educational tests" are questions created for educational purposes that are displayed within video content and used to gauge students' understanding.

[0679] "Delivery means" refers to the technology used to deliver video content and tests generated using the Internet or cloud services to each user's device.

[0680] "Automatic scoring" refers to the function in which the system analyzes the user's answers, determines whether they are correct, and assigns a score.

[0681] "Feedback" refers to the function of providing real-time information such as students' level of understanding and areas for improvement based on their learning results.

[0682] "Smart wearable devices" refer to interactive electronic devices that can be worn and used by a user, examples of which include smart glasses and smart watches.

[0683] "Real-time lecture viewing" refers to the function that allows students to attend lectures in real time using smart wearable devices.

[0684] An "interactive test" is a test format in which participants answer questions asked while watching a video on the spot using technologies such as voice recognition and eye tracking.

[0685] "Other educational institution curriculum" refers to the learning plans and course content offered by other schools or educational institutions that students can select and take.

[0686] This invention provides a teacher replacement system that uses generative AI models and interactive video content to improve the quality of education. This system stores a huge amount of teaching material data in a database, uses generative AI to automatically generate a curriculum based on educational goals, creates video content and educational tests, and distributes them to user devices. Furthermore, it is possible to watch lectures in real time and take interactive tests using smart wearable devices.

[0687] 1. Management of teaching material data

[0688] The server receives a huge amount of educational material data, such as textbooks and past exam questions, uploaded by school administrators and stores it in a database, which ensures that it is always accessible.

[0689] 2. Automatic curriculum generation

[0690] The server uses generative AI to automatically generate a curriculum based on the received teaching material data and educational goals. In this process, text analysis technology is used to extract important keywords and key points, and educational content is then constructed based on these.

[0691] 3. Creating video content and educational tests

[0692] The server creates video content based on the automatically generated curriculum. It generates slides based on text information, adds narration using a speech synthesis engine, and inserts educational test questions to add interactivity to the video.

[0693] 4. Content Delivery

[0694] The server uploads the generated video content and educational tests to the streaming server and distributes them to user devices.Using smart wearable devices, users can watch lectures in real time and take interactive tests.

[0695] 5. Automatic grading and feedback

[0696] The server automatically grades the user's answers and provides real-time feedback on the learning results to the user's device or smart wearable device. It also suggests additional learning based on the user's individual progress.

[0697] Specific examples

[0698] For example, suppose an educational administrator at School A sets up a "second-semester mathematics curriculum" and uploads related textbooks and past exam questions. The server receives this and uses generative AI to automatically generate lectures such as "Fundamentals of Equations" and "Probability Calculations." Test questions are inserted into the generated videos at the end of each chapter to check comprehension. Students watch these videos using smart glasses and answer each test using eye tracking and voice recognition. The server automatically grades the answers and provides feedback in real time.

[0699] Furthermore, an example of a prompt is, "Read the following passage and answer the question: Describe the automated generation and delivery of educational content. Question: What technologies are used to generate educational content?"

[0700] Specific hardware used includes smart wearable devices such as smart glasses and smart watches, and software used includes OpenCV, Transformers (Hugging Face), gTTS, and playsound.

[0701] Through the above structure and process, this educational system is able to provide efficient and effective education and improve students' motivation to learn and their level of understanding.

[0702] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0703] Step 1:

[0704] The server stores the educational material data (textbooks, past exam questions, etc.) uploaded by the school administrator in a database. The input is the data uploaded by the school administrator, and the output is the educational material data stored in the database. Specifically, the server receives the data and performs text analysis, extracts important keywords and points, and stores them in the database.

[0705] Step 2:

[0706] The server uses generative AI to automatically generate a curriculum based on educational goals. The input is stored teaching material data and educational goal settings, and the output is an automatically generated curriculum. Specifically, the generative AI model analyzes the data and generates lesson plans that suit the educational goals.

[0707] Step 3:

[0708] The server generates video content based on the automatically generated curriculum and inserts interactive educational tests into the videos. The input is the automatically generated curriculum, and the output is the video content and educational tests. Specifically, the server generates slides based on text information, adds narration using a speech synthesis engine, and inserts test questions at appropriate points.

[0709] Step 4:

[0710] The server uploads the generated video content to a streaming server and distributes it to user terminals. The input is the generated video content, and the output is a distribution link that is generated and provided to the user terminal. Specifically, the server uploads video files and provides a dedicated access point for each user.

[0711] Step 5:

[0712] Users use smart wearable devices to watch lectures in real time and take interactive tests within the videos. The input is the distribution link and the smart wearable device, and the output is the user's test answers. Specifically, users answer the tests using eye tracking and voice recognition while watching the videos.

[0713] Step 6:

[0714] The server automatically scores the user's answers and provides feedback on the learning results in real time. The input is the user's test answers, and the output is the scoring results and feedback information. Specifically, the server analyzes the answer data, performs automatic scoring, and provides feedback based on the score and level of understanding.

[0715] Step 7:

[0716] The server manages multiple educational goal settings and enables the provision of curricula from other educational institutions. The input is the curriculum data from other educational institutions and the user's curriculum selection, and the output is the video and test for the selected curriculum. Specifically, the server retrieves the selected curriculum from the database and delivers it to the user.

[0717] Step 8:

[0718] The user selects and takes a curriculum from another educational institution. The input is the user's curriculum selection, and the output is learning content and test answers based on the curriculum from the other educational institution. Specifically, the user searches for the target grade, subject, and educational institution name, views the provided curriculum, and takes the test.

[0719] The above are the specific processing steps of the system program that realizes this application example.

[0720] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0721] This invention is a teacher replacement AI system that uses artificial intelligence (AI), interactive video content, and emotion recognition technology to improve the quality of education. The system collects a huge amount of teaching material data and uses generative AI to automatically generate a curriculum based on the educational goals set by each educational institution. It also has an emotion engine that recognizes users' emotions in real time and personalizes the learning experience. Below, we will explain each major component of the system and how it works.

[0722] 1. Curriculum setting and data collection

[0723] User (School Administrator):

[0724] Users (school administrators) input educational goals (learning objectives and curriculum requirements) into the system and upload teaching material data such as textbooks, past exam questions, and other teaching materials.

[0725] Device:

[0726] The terminal transmits the information input by the school administrator to the server and uploads the teaching material data to the server.

[0727] server:

[0728] The server receives the educational goal settings and teaching material data, analyzes them, and stores them in a database. Specifically, it performs text analysis, extracts keywords and important points, and converts them into a format that is easy to search.

[0729] 2. Curriculum generation and animation

[0730] server:

[0731] The server uses generative AI to automatically generate a curriculum based on educational goals, including setting the learning sequence and selecting learning topics.

[0732] server:

[0733] The server then creates video content based on the generated curriculum. Specifically, it generates slides based on text information and adds narration using a speech synthesis engine. At the same time, it sets up educational test questions at the end of each topic.

[0734] 3. Real-time feedback from an emotion engine

[0735] server:

[0736] The server uses an emotion engine to recognize the user's emotions in real time, adjust the difficulty of educational tests based on the emotion data, and provide feedback according to the user's learning progress. The emotion engine identifies the user's emotions using facial expression analysis, voice analysis, behavior analysis, etc.

[0737] 4. Video content and test distribution

[0738] server:

[0739] The server uploads the generated video content and educational tests to the streaming server and generates links for each. These links are organized by semester and subject.

[0740] server:

[0741] The server distributes the viewing link to the user terminal. Specifically, it sends the viewing link to the terminal of the registered student, allowing them to start learning.

[0742] 5. Student viewing and testing

[0743] User (student):

[0744] The user (student) clicks on the provided link to watch the video, answers the test questions inserted in the video while watching, and sends the answers to the system.

[0745] 6. Feedback on learning results

[0746] server:

[0747] The server automatically scores the received answers and analyzes the accuracy rate and level of understanding. The results are fed back to the user's (student's) dashboard as learning results. Specifically, the score, mistakes, topics requiring additional study, etc. are displayed. Emotional data is also reflected in the learning results, personalizing the learning experience.

[0748] 7. Customization and participation in other educational institutions' curricula

[0749] User (student):

[0750] Users (students) can select and take courses from other educational institutions by searching for the relevant grade, subject, and educational institution name, and then watching videos and taking tests based on the provided curriculum.

[0751] server:

[0752] The server provides selected users with videos and tests from other educational institutions' curricula and records their learning progress.

[0753] Specific examples

[0754] For example, suppose an educational administrator at School A sets up a "second-semester mathematics curriculum" and uploads related textbooks and past exam questions. The server receives this and uses generative AI to automatically generate lectures such as "Fundamentals of Equations" and "Probability Calculations." Test questions are inserted at the end of each chapter to check comprehension. Users (students) watch these videos on their devices and answer each test. The server automatically scores the answers and provides real-time feedback. At the same time, an emotion engine recognizes the user's (student's) current emotions and adjusts the difficulty level or sends encouraging messages to further personalize the learning experience. In some cases, students can also take an excellent mathematics curriculum from another school, School B, and the server provides videos and tests accordingly.

[0755] In this way, the educational system of the present invention supports efficient learning while improving the quality of education, reduces the burden on teachers, and contributes to eliminating educational disparities.The introduction of an emotion engine is designed to make the user's learning experience more comfortable and effective.

[0756] The processing flow will be explained below.

[0757] Step 1:

[0758] User (School Administrator):

[0759] The user (school administrator) inputs educational goals (learning objectives and curriculum requirements) into the system. Specifically, they input information such as the grade, subject, learning objectives for the semester, and key learning items, and then send this information to the system.

[0760] Step 2:

[0761] User (School Administrator):

[0762] Users (school administrators) select textbooks, past exam papers, and other educational material data and upload them to the system. The uploaded data becomes the basis for generating educational content.

[0763] Step 3:

[0764] Device:

[0765] The terminal transmits the educational goal setting sent from the school administrator and the uploaded teaching material data to the server.

[0766] Step 4:

[0767] server:

[0768] The server receives the educational goal settings and teaching material data and stores them in a database. Specifically, it extracts, organizes, and stores keywords and important points related to the educational goals.

[0769] Step 5:

[0770] server:

[0771] The server uses generative AI to automatically generate a curriculum based on the received educational goal settings, including selecting the necessary topics and setting the learning sequence.

[0772] Step 6:

[0773] server:

[0774] The server creates video content based on the generated curriculum. Specifically, it generates slides based on text information and adds narration using a speech synthesis engine. At this time, it is also possible to use an emotion engine to gauge the user's emotional reactions and insert messages to boost motivation at appropriate times.

[0775] Step 7:

[0776] server:

[0777] The server inserts interactive test questions into the video, providing questions and problems at key points in the video to check comprehension, and adjusts the difficulty of the test based on the user's emotional data.

[0778] Step 8:

[0779] server:

[0780] The server uploads the generated video content and tests to a streaming server and generates viewing links, organized by semester and subject.

[0781] Step 9:

[0782] server:

[0783] The server distributes the viewing link to the user's device. The link is sent to the device of the registered student to promote learning.

[0784] Step 10:

[0785] User (student):

[0786] The user (student) clicks on the provided link to watch the video. While watching, they answer test questions inserted in the video and send their answers to the system. The system recognizes emotions from the user's behavior and facial expressions while watching, and provides appropriate motivational and encouraging messages.

[0787] Step 11:

[0788] Device:

[0789] The device sends the user's (student's) answers to the server, along with emotional data in real time, for automatic grading.

[0790] Step 12:

[0791] server:

[0792] The server automatically scores the received answers and analyzes the accuracy rate and level of understanding. The results are fed back to the user's (student's) dashboard as learning results. Emotional data is also included in the feedback to personalize the learning experience.

[0793] Step 13:

[0794] User (student):

[0795] Students can check their learning results on the dashboard and re-learn topics they have not fully understood. They can also select and take courses from other educational institutions if they wish.

[0796] Step 14:

[0797] server:

[0798] The server provides selected users with videos and tests from other educational institutions' curricula and records their learning progress. By allowing users to take high-quality curricula from other educational institutions, the quality of education is improved.

[0799] Through this series of steps, the system provides an efficient and high-quality learning environment, reducing the burden on teachers while enabling education that meets the needs of each learner. The introduction of an emotion engine makes it possible to maintain learner motivation and provide a personalized learning experience.

[0800] Example 2

[0801] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0802] Conventional educational systems place a heavy burden on individual teachers, making it difficult to provide personalized education that takes into account individual learning styles and progress. They also struggle with real-time feedback using emotion recognition and the flexible use of curricula from other educational institutions. Furthermore, there is a lack of technology to efficiently manage large amounts of teaching material data and automatically generate optimal curricula.

[0803] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0804] In this invention, the server includes means for storing a huge amount of teaching material data in a database, means for automatically generating a curriculum based on educational goals using a generative AI model, means for generating slides from text information and generating video content by adding narration using a speech synthesis engine, means for recognizing a user's emotions in real time using an emotion engine and providing feedback based on the user's learning progress, means for automatically scoring the user's answers and providing feedback on the learning results, and means for managing multiple educational goal settings and enabling the provision of curricula from other educational institutions. This makes it possible to provide personalized education according to each user's learning style and progress, thereby improving the quality of education.

[0805] "Huge amounts of educational material data" refers to a wide variety of educational materials and digital content, and the amount is extremely large, detailed, and comprehensive.

[0806] A "generative AI model" refers to a technology that uses artificial intelligence to automatically create curricula and learning plans based on user input data and requirements.

[0807] "Educational goals" are learning objectives and goals set by the user (school administrator), and serve as the basis for curriculum and lesson plans.

[0808] "Text information" refers to character data such as sentences and keywords contained in the teaching material data.

[0809] "Slides" are presentation-style materials used as part of educational content, and are primarily used to provide visual information.

[0810] A "speech synthesis engine" refers to a system or software that provides the technology to convert text data into artificially generated voice data.

[0811] "Video content" refers to educational video information provided through a combination of slides and audio narration.

[0812] An "emotion engine" refers to a technology that analyzes a user's facial expressions, voice, actions, etc. to recognize emotions and provide that information to the system.

[0813] "User terminal" refers to a device (e.g., PC, tablet, smartphone, etc.) that a user uses to access the educational system and view educational content or take tests.

[0814] A "streaming server" refers to a network server that distributes digital data such as video content and test questions in real time.

[0815] "Real-time awareness" refers to the system's ability to respond immediately to user input and actions, providing appropriate feedback and adjustments on the spot.

[0816] "Automatic scoring" refers to a technology in which the system automatically evaluates the answers submitted by the user and calculates the score and percentage of correct answers.

[0817] "Feedback" refers to information such as evaluations, advice, and corrections provided to users based on their learning progress and results.

[0818] "Educational goal setting" refers to the process in which a user registers predetermined learning goals in the system and creates a learning plan based on those goals.

[0819] "Curriculum of other educational institutions" refers to the learning plans and lesson contents provided by educational institutions other than the educational institution using the system.

[0820] "Personalization" refers to optimizing the educational content and feedback provided according to the characteristics and needs of each individual user.

[0821] This invention is an educational system that uses artificial intelligence (AI), interactive video content, and emotion recognition technology to improve the quality of education. The system collects a huge amount of educational material data and uses a generative AI model to automatically generate a curriculum based on the educational goals set by each educational institution. It also has an emotion engine that recognizes users' emotions in real time and personalizes the learning experience.

[0822] The hardware required to implement the system includes a server, a user terminal, and a streaming server. The software required includes a generative AI model (e.g., software dedicated to generative AI), a text analysis library (e.g., an NLP library), and a speech synthesis engine (e.g., a speech synthesis API).

[0823] First, the user (school administrator) enters educational goals into the system and uploads the corresponding teaching material data. The device then sends this information to the server. The server then analyzes the received educational goals and teaching material data. Specifically, it uses a Python NLP library to perform text analysis, extracting keywords and important points and storing them in a database.

[0824] The server then automatically generates a curriculum using a generative AI model. For example, GPT-4 is used as the generative AI model. The generated curriculum includes setting the learning order and selecting learning topics. The server then creates video content based on the curriculum. PowerPoint slides are generated from the text information and narration is added using a speech synthesis engine. These are then integrated using video editing software such as FFmpeg to generate the video content. At the same time, educational test questions are set at the end of each topic.

[0825] The generated video content is uploaded to a streaming server, and a viewing link is generated. The server distributes this link to the user's device. The user (student) uses the provided link to watch the video, answer the embedded test questions, and send the answers to the server. The server uses an auto-grader library to automatically grade the received answers. Feedback is displayed on the user's (student's) dashboard based on the correct answers and level of understanding. Emotional data generated by an emotion engine is also taken into account in the feedback.

[0826] The emotion engine uses Microsoft Azure Emotion API and other tools to analyze facial expressions, voice, and behavior in real time to recognize the user's emotions. For example, it can suggest taking a break if the user is tired, or adjust the difficulty of learning if the user is highly motivated.

[0827] The system also manages multiple educational goal settings and can provide curricula from other educational institutions. Users (students) can search for, view, and take courses from other educational institutions. The server provides videos and tests corresponding to the selected curriculum and records the student's learning progress.

[0828] Specific examples

[0829] For example, suppose an educational administrator at School A sets up a "second-semester mathematics curriculum" and uploads related textbooks and past exam questions. The server receives this and uses a generative AI model (e.g., GPT-4) to automatically generate lectures such as "Fundamentals of Equations" and "Probability Calculations." Test questions are inserted into the generated videos at the end of each chapter to check comprehension. Users (students) watch these videos on their devices and answer each test. The server automatically scores the answers and provides feedback in real time. At the same time, an emotion engine recognizes the user's (student's) current emotions and personalizes the learning experience by adjusting the difficulty level and sending encouraging messages.

[0830] Prompt Sentence Examples

[0831] "Generate a second-semester mathematics curriculum based on the following criteria. Coverage includes basic equations and probability calculations. Also, include test questions at the end of each chapter to assess understanding."

[0832] The introduction of this system is expected to improve the quality of education, support efficient learning, reduce the burden on teachers, and contribute to eliminating educational disparities.

[0833] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0834] Step 1:

[0835] User (school administrator)

[0836] Operation: A user logs in to the system, inputs an educational goal (e.g., "Second semester mathematics curriculum"), and uploads the corresponding teaching material data (textbooks, past exam questions) to the system.

[0837] Input: Educational goals, textbook file, past exam question file.

[0838] Output: The educational goals and teaching material data are uploaded and sent to the server.

[0839] Step 2:

[0840] Terminal

[0841] Operation: The device sends the entered educational goals and teaching material data to the server. When the user presses the upload button, the data is sent via an HTTP POST request.

[0842] Input: Educational goals, textbook files, and past exam files entered by the user into the terminal.

[0843] Output: The educational goals and teaching material data are sent to the server.

[0844] Step 3:

[0845] server

[0846] Operation: The server analyzes the received educational goals and teaching material data. It uses a Python NLP library (e.g., spaCy) to perform text analysis and extract keywords and key points. The analysis results are stored in a database.

[0847] Input: Educational goals, teaching material data (textbook files, past exam files).

[0848] Output: Analysis results (keywords, important points) are stored in a database.

[0849] Step 4:

[0850] server

[0851] Operation: The server automatically generates a curriculum using a generative AI model (e.g., GPT-4) based on the analysis results. A prompt sentence is input to the generative AI model to generate the curriculum.

[0852] Input: Analysis result, prompt statement.

[0853] Output: Auto-generated curriculum.

[0854] Step 5:

[0855] server

[0856] How it works: The server creates video content based on the generated curriculum, using text information to generate slides with Python's PPTX library, creating narration with Google Text-to-Speech API, and integrating them with FFmpeg.

[0857] Input: Auto-generated curriculum,text information.

[0858] Output: The generated video content.

[0859] Step 6:

[0860] server

[0861] Operation: The server uploads the generated video content and educational test to the streaming server and generates a viewing link, which is then sent to the user's device.

[0862] Input: Generated video content, educational tests.

[0863] Output: Viewing link.

[0864] Step 7:

[0865] User (student)

[0866] How it works: Users watch the video using the provided viewing link and answer the test questions inserted within the video. Their answers are then sent to the system.

[0867] Input: Viewing link, answers to test questions.

[0868] Output: User response data.

[0869] Step 8:

[0870] Terminal

[0871] Operation: The terminal sends the user's answer data to the server. When the user presses the "Send Answer" button, the answer data is sent via an HTTP POST request.

[0872] Input: User response data.

[0873] Output: The answer data is sent to the server.

[0874] Step 9:

[0875] server

[0876] How it works: The server automatically scores the received answer data and analyzes the level of understanding and the percentage of correct answers. It uses the Python auto-grader library to perform the scoring and analysis. It then provides real-time feedback to the user's dashboard. The feedback includes emotional data obtained using an emotion engine.

[0877] Input: Response data, emotion data.

[0878] Output: Marking results and feedback.

[0879] Step 10:

[0880] User (student)

[0881] How it works: Users can select and take courses from other educational institutions. They select their grade and subject on the system, watch videos based on the curriculum provided, and take tests.

[0882] Input: Institutional curriculum choices.

[0883] Output: Viewing and testing data.

[0884] Step 11:

[0885] server

[0886] How it works: The server provides users with selected curriculum videos and tests from other educational institutions, records their learning progress, and provides feedback.

[0887] Input: Institution curriculum, user progress data.

[0888] Output: curriculum videos, tests, progress feedback.

[0889] (Application example 2)

[0890] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0891] Traditional education systems often have uniform curricula and content, and do not adequately personalize content based on individual students' learning progress or emotions. They also lack interactive feedback and mechanisms for students to actively participate, making it difficult to maximize learning outcomes. Furthermore, they lack the flexibility to easily use curricula from other educational institutions.

[0892] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0893] In this invention, the server includes means for storing a huge amount of educational material data in a database, means for automatically generating a curriculum based on educational goals using a generation AI, means for generating video content and inserting educational tests into the videos, means for distributing the generated video content to user terminals, means for automatically scoring user answers and providing feedback on learning results, means for managing multiple educational goal settings and enabling the provision of curricula from other educational institutions, means including an emotion engine for recognizing user emotions in real time and adjusting the difficulty of educational tests based on that data, and means for providing an interactive educational experience related to the educational material. This makes it possible to provide a learning experience optimized for each user, thereby improving motivation to learn and understanding.

[0894] A "server" is a computing device that provides and manages data over a network.

[0895] A "database" is an information system for efficiently storing, managing, and searching large amounts of data.

[0896] "Generative AI" is a general term for artificial intelligence technology that automatically generates new information based on given conditions and data.

[0897] "Educational goals" are the objectives or results to be achieved through educational activities.

[0898] "Curriculum" means a set of educational content or learning plan.

[0899] "Video content" refers to dynamic video data that provides information through visual and audio means.

[0900] "Educational testing" refers to exams and quizzes used to assess a learner's understanding or proficiency.

[0901] "User terminal" refers to a computer or mobile device that is directly used by a user.

[0902] An "emotion engine" is a software technology that analyzes a user's facial expressions, voice, etc. and recognizes their emotional state.

[0903] An "interactive educational experience" is a learning activity in which users actively participate and interact with information.

[0904] This invention is an educational system that uses artificial intelligence (AI), interactive video content, and emotion recognition technology. This system collects a huge amount of educational material data and uses generative AI to automatically generate curricula based on the educational goals set by each educational institution. It also has an emotion engine that recognizes users' emotions in real time to personalize the learning experience.

[0905] The server stores a huge amount of teaching material data in a database, analyzes it, and converts it into an easily searchable format. The user (school administrator) inputs educational goals (learning objectives and curriculum requirements) into the system and uploads teaching material data such as books, past exam questions, and other teaching materials. The terminal sends this input information to the server, which analyzes it and stores it in the database. As a concrete example, a school administrator can set up a "second semester mathematics curriculum" and upload related books and past exam questions.

[0906] The server then uses generative AI to automatically generate a curriculum based on educational goals, and creates video content based on the generated curriculum. This video includes the setting of the learning order and the selection of learning topics, and narration is added using a speech synthesis engine. Educational test questions are set at the end of each topic. The generated video content is uploaded to a streaming server, and links organized by semester and subject are generated. These viewing links are distributed to registered user devices.

[0907] Users (students) click these links to watch the videos and answer the test questions inserted in the videos. The server automatically scores the answers and provides feedback on the learning results. Specifically, the user's (student's) dashboard displays the learning results, such as the score, mistakes made, and topics requiring additional study.

[0908] Furthermore, the present invention utilizes an emotion engine to recognize user emotions in real time and personalize the learning experience based on the emotion data. Specifically, the system uses facial, voice, and behavioral analysis to identify user emotions, and then adjusts the difficulty of educational tests and provides real-time feedback and encouraging messages based on the identified emotions. The system utilizes hardware and software such as OpenAI API, TensorFlow, OpenCV, and gTTS.

[0909] As a concrete example, imagine a situation where you want to send an encouraging message to a user (student) while they are viewing learning materials, such as "You will succeed." Examples of prompt sentences that can be used include the following:

[0910] "The student seems frustrated. Give encouraging words."

[0911] "Don't give up! You are doing great! Keep going and you will succeed."

[0912] In this way, the educational system of the present invention improves the quality of education, supports efficient learning, reduces the burden on teachers, and contributes to eliminating educational disparities.The introduction of an emotion engine is designed to make the user's learning experience more comfortable and effective.

[0913] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0914] Step 1:

[0915] The server receives educational goals (learning objectives and curriculum requirements) as input from the user (school administrator), and also uploads related educational material data (textbooks, past exam questions, etc.) to the database. This allows the educational goal settings and educational material data to be stored in the database. Specific operations include performing text analysis and extracting important keywords and points.

[0916] Step 2:

[0917] The server automatically generates a curriculum based on the generative AI model using the educational goals and teaching material data stored in the database. The server uses the educational goals and teaching material data as input and obtains the generated curriculum as output. Specific operations include setting the learning order and selecting learning topics.

[0918] Step 3:

[0919] The server generates video content based on the generated curriculum and inserts educational tests into the video. Using the generated curriculum as input, the server creates video content as output. Specifically, the server generates slides based on text information and adds narration using a speech synthesis engine (such as gTTS).

[0920] Step 4:

[0921] The server uploads the generated video content to the streaming server and generates a viewing link for each video. The generated video content is used as input and a viewing link is obtained as output. Specific operations include file upload processing and link generation.

[0922] Step 5:

[0923] The server distributes the viewing link to the user's device and allows the user (student) to begin learning. The viewing link is used as input and confirmation of link distribution is output. Specifically, the server sends the link to the user via email or a notification system.

[0924] Step 6:

[0925] The user (student) clicks on the provided link to watch the video and answers the test questions inserted in the video while watching. The viewing link and the user's answers are used as input, and the answer results are obtained as output. Specific operations include playing the video and submitting the test answers.

[0926] Step 7:

[0927] The server automatically scores the user's answers and provides feedback on the learning results. It uses the user's answer data as input and obtains feedback results as output. Specifically, it analyzes and automatically scores the answers, and displays the scores and analysis results of the level of understanding on a dashboard.

[0928] Step 8:

[0929] The server uses an emotion engine to recognize the user's emotions in real time and adjusts the level of difficulty and feedback based on that data. It uses the user's facial images and voice data as input, and obtains emotion analysis results and feedback as output. Specifically, it performs facial expression analysis (OpenCV) and voice analysis, and uses the OpenAI API to generate encouraging messages and other prompts.

[0930] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0931] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0932] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0933] [Third embodiment]

[0934] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0935] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0936] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0937] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0938] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0939] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0940] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0941] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0942] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0943] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0944] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0945] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0946] This invention is a teacher replacement AI system that uses artificial intelligence (AI) and interactive video content to improve the quality of education. This system has the ability to collect a huge amount of teaching material data and use generative AI to automatically generate a curriculum based on the educational goals set by each educational institution. Below, we will explain each major component of this system and how it works.

[0947] 1. Curriculum setting and data collection

[0948] User (School Administrator):

[0949] School administrators input educational goals (learning objectives and curriculum requirements) and upload teaching material data such as textbooks, past exam questions, and other teaching materials.

[0950] Device:

[0951] The terminal transmits the information input by the school administrator to the server and uploads the teaching material data to the server.

[0952] server:

[0953] The server receives the educational goal settings and teaching material data, analyzes them, and stores them in a database. Specifically, it performs text analysis to extract keywords and important points.

[0954] 2. Curriculum generation and animation

[0955] server:

[0956] The server uses AI to automatically generate a curriculum based on educational goals. Video content is then created based on the generated curriculum. Slides are generated based on text information, and narration is added using a speech synthesis engine. Educational test questions are also inserted into the video to add interactivity.

[0957] 3. Video content and test distribution

[0958] server:

[0959] The server uploads the generated video content and educational tests to the streaming server and generates links for each. The links are organized by semester and subject and provided to students' devices.

[0960] 4. Students listen and take the test

[0961] User (student):

[0962] Students click on the provided link to watch the video content, answer the test questions inserted in the video, and send their answers from their device to the server.

[0963] 5. Feedback on learning results

[0964] server:

[0965] The server automatically scores the answers received and analyzes the accuracy rate and level of understanding. The learning results are then fed back to the student's dashboard, which displays the score, mistakes made, and topics requiring additional study.

[0966] 6. Customization and participation in other educational institutions' curricula

[0967] User (student):

[0968] Students can select and take courses from other educational institutions by searching for the relevant grade, subject, and educational institution, and then watching videos and taking tests based on the provided curriculum.

[0969] server:

[0970] The server provides videos and tests for the selected curriculum and records the student's learning progress.

[0971] Specific examples

[0972] For example, suppose an educational administrator at School A sets up a "second-semester mathematics curriculum" and uploads related textbooks and past exam questions. The server receives this and uses generative AI to automatically generate lectures such as "Fundamentals of Equations" and "Probability Calculations." Test questions are inserted at the end of each chapter in the generated videos to check comprehension. Students watch these videos on their devices and answer each test. The server automatically grades the answers and provides feedback in real time. In some cases, students can also take an excellent mathematics curriculum from another school, School B, and the server provides them with corresponding videos and tests.

[0973] In this way, the educational system of the present invention supports efficient learning while improving the quality of education, and also contributes to eliminating educational disparities.

[0974] The processing flow will be explained below.

[0975] Step 1:

[0976] User (School Administrator):

[0977] The user (school administrator) inputs educational goals (learning objectives and curriculum requirements) into the system. Specifically, they enter information such as the grade, subject, learning objectives for the semester, and key learning items, and then send it to the system.

[0978] Step 2:

[0979] User (School Administrator):

[0980] Users (school administrators) select textbooks, past exam papers, and other teaching material data and upload them to the system, which is then added to the system's teaching material database.

[0981] Step 3:

[0982] Device:

[0983] The terminal transmits the educational goal setting sent by the user and the uploaded teaching material data to the server.

[0984] Step 4:

[0985] server:

[0986] The server analyzes the received educational goal settings and teaching material data and stores them in a database. Specifically, it performs text analysis, extracts keywords and important points, and converts them into a format that is easy to search.

[0987] Step 5:

[0988] server:

[0989] The server uses generative AI to automatically generate a curriculum based on educational goals, including setting the learning sequence and selecting learning topics.

[0990] Step 6:

[0991] server:

[0992] The server then creates video content based on the generated curriculum. Specifically, it generates slides based on text information and adds narration using a speech synthesis engine. At the same time, it sets up educational test questions at the end of each topic.

[0993] Step 7:

[0994] server:

[0995] The server uploads the generated videos and tests to a streaming server and generates viewing links, organized by semester and subject.

[0996] Step 8:

[0997] server:

[0998] The server distributes the viewing link to the user terminal. Specifically, it sends the viewing link to the terminal of the registered student, allowing them to start learning.

[0999] Step 9:

[1000] User (student):

[1001] The user (student) clicks on the provided link to watch the video, answers the test questions inserted in the video while watching, and sends the answers to the system.

[1002] Step 10:

[1003] Device:

[1004] The terminal sends the user's (student's) answers to the server, which then sends the answers in real time and automatically grades them.

[1005] Step 11:

[1006] server:

[1007] The server automatically scores the received answers and analyzes the accuracy rate and level of understanding. The results are fed back to the user's (student's) dashboard as learning results.

[1008] Step 12:

[1009] User (student):

[1010] Students can check their learning results on the dashboard and re-learn topics they have not fully understood. They can also select and take courses from other educational institutions if they wish.

[1011] Step 13:

[1012] server:

[1013] The server provides selected users with videos and tests from other educational institutions' curricula and records their learning progress, allowing users to take high-quality curricula from other educational institutions and improve the quality of their education.

[1014] Through this series of steps, the system can provide an efficient and high-quality learning environment, reduce the burden on teachers, and contribute to eliminating educational disparities.

[1015] Example 1

[1016] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1017] In conventional educational systems, the provision of teaching materials and feedback on learning results was not done in real time, resulting in issues with student learning efficiency. It was also difficult to automatically generate curricula based on educational goals, and it was difficult to share resources across multiple educational institutions. Furthermore, content that lacked interactivity made it difficult to maintain students' interest, which tended to reduce learning effectiveness.

[1018] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1019] In this invention, the server includes a means for storing a large amount of teaching material data in a database, a means for automatically generating a curriculum based on educational goals using a generative AI, a means for inputting prompts into a generative AI model and creating video content based on the curriculum, a means for inserting educational tests into the videos, a means for distributing the generated video content and educational tests to a user terminal, a means for automatically scoring user answers and providing real-time feedback on learning results, and a means for managing multiple educational goal settings and enabling the provision of curricula from other educational institutions. This enables real-time feedback on learning results, automatic generation of a curriculum based on educational goals, and resource sharing among multiple educational institutions. Furthermore, highly interactive content can maintain student interest and improve learning effectiveness.

[1020] "Vast amounts of educational material data" refers to the large amount of electronic data used for education, such as textbooks, past exam questions, and supplementary materials.

[1021] A "database" refers to a system for efficiently storing, managing, searching, and using information.

[1022] "Generative AI" refers to artificial intelligence that automatically generates natural language, images, curriculum, and more based on input data.

[1023] An "educational goal" refers to a specific objective or purpose that a student should achieve through a particular learning process.

[1024] "Curriculum" refers to learning content and educational programs that are systematically constructed based on educational goals.

[1025] A "generative AI model" refers to an artificial intelligence algorithm that learns from diverse data and generates new data and content based on that knowledge.

[1026] A "prompt sentence" refers to an input sentence that elicits a specific response or output from a generative AI model.

[1027] "Video Content" refers to educational materials in video format created for educational purposes.

[1028] "Educational test" refers to an assessment tool that includes questions designed to assess a learner's understanding and knowledge retention.

[1029] "User terminal" refers to electronic devices such as PCs, smartphones, and tablets that learners and educational institution administrators use to access and operate the system.

[1030] "Automatic scoring" refers to the process by which a system automatically evaluates and scores submitted test answers.

[1031] "Real-time feedback" refers to responding immediately to a user's actions and answers, and providing learning results and evaluations immediately.

[1032] "Setting multiple educational goals" refers to the ability of different learners and grade levels to have different educational goals and to manage these multiple goals simultaneously.

[1033] "Curriculum of other educational institutions" refers to educational programs and learning content offered at other schools or educational facilities.

[1034] This invention is a teacher replacement AI system that uses artificial intelligence (AI) and interactive video content to improve the quality of education. Specific implementation methods of this system are described below.

[1035] Curriculum setting and data collection

[1036] User (School Administrator):

[1037] School administrators log in to the system and enter educational goals (learning objectives and curriculum requirements) into an input form on a terminal. They also upload related educational material data, such as textbooks, past exam questions, and supplementary materials, to the system. Specifically, they use a web browser to perform operations from the management dashboard.

[1038] Device:

[1039] The device receives the user's input information and uploaded files and sends them to the server. The device can be a PC, tablet, smartphone, etc. This information is temporarily stored on the device, encrypted, and then sent to the server.

[1040] server:

[1041] The server receives the educational goals and teaching material data sent from the device. The received data is then analyzed to extract educational keywords and key points, which are then stored in a database. The software used includes a natural language processing (NLP) engine, which analyzes a PDF file, such as "math textbook.pdf," to extract keywords like "equation" and "probability."

[1042] Curriculum generation and animation

[1043] server:

[1044] The server automatically generates a curriculum using a generative AI model (such as GPT-3 or BERT) based on the analyzed data and the input educational goals. A prompt is input into the generative AI model to generate an appropriate curriculum. An example of a prompt is, "Generate an environmental science curriculum for second-year high school students based on the following Sustainable Development Goals (SDGs). Provide the following materials as teaching material data: textbook (title: Earth Environmental Science, 2nd Edition), past exam questions (period: past five years), and other supplementary materials (title: Science for a Sustainable Future). The curriculum should also include interactive test questions."

[1045] Video content is created based on the generated curriculum. Specifically, slides are generated using presentation software, narration is added using a speech synthesis engine (e.g., Google Cloud Text-to-Speech), and educational test questions are added to the video to make it interactive.

[1046] Video content and test delivery

[1047] server:

[1048] The server uploads the created video content and educational tests to the streaming server, generates links for each piece of content, organizes them by semester and subject, and stores them in a database, allowing students to easily access the content.

[1049] Students listen and take the test

[1050] User (student):

[1051] Students click on the provided link on their device (PC, tablet, smartphone) to watch the video content. The video also includes educational tests, and they can answer interactive tests in real time according to their learning progress.

[1052] Feedback on learning results

[1053] server:

[1054] The server uses software to automatically score the test answers submitted by students. The automatic scoring is done using machine learning algorithms (e.g., Scikit-learn) to instantly analyze the percentage of correct answers and level of understanding. The results are immediately fed back to the student's dashboard, and further study advice is provided depending on the level of understanding.

[1055] Customization and access to other educational institutions' curricula

[1056] User (student):

[1057] Students can select and take courses offered by other educational institutions by searching for the relevant grade, subject, and educational institution name, and then taking the provided curriculum videos and tests.

[1058] server:

[1059] The server provides videos and tests for selected curriculum and records students' learning progress, allowing them to improve the quality of their education and contributing to eliminating educational disparities.

[1060] The educational system of the present invention supports efficient learning while improving the quality of education, and is of great help in eliminating educational disparities.

[1061] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1062] Step 1: Setting up the curriculum and inputting teaching material data

[1063] User (School Administrator):

[1064] School administrators log in to the system and input educational goals (learning objectives and curriculum requirements) into an input form on their terminal. They also upload related educational material data, such as textbooks, past exam papers, and supplementary materials, to the system. The input information and uploaded data become input. The system then receives the educational goals and educational material data.

[1065] Specific behavior:

[1066] Access the management dashboard and enter your educational goals (e.g., "Second semester math curriculum").

[1067] Upload files such as textbooks (e.g., "Mathematics textbook.pdf") and past exam questions (e.g., "Past exam questions.zip").

[1068] Step 2: Send data from the device to the server

[1069] Device:

[1070] The information entered by the user and the files uploaded are temporarily stored inside the device. This information is then encrypted and securely sent to the server. The input is the user's input information and uploaded data, and the output is the encrypted data to be sent.

[1071] Specific behavior:

[1072] The device encrypts educational goals and teaching material data.

[1073] The encrypted data is sent to the server.

[1074] Step 3: Receiving and analyzing the teaching material data

[1075] server:

[1076] The server receives the educational goals and teaching material data sent from the device. It performs text analysis on the received data and extracts educational keywords and important points. The results of this analysis are input, and the information stored in the database is output.

[1077] Specific behavior:

[1078] The server receives "MathematicsTextbook.pdf".

[1079] Using software (NLP engine), keywords such as "equation" and "probability" are extracted.

[1080] The extracted information is stored in a database.

[1081] Step 4: The curriculum generation process

[1082] server:

[1083] The server automatically generates a curriculum using a generative AI model based on the analyzed data and the input educational goals. At this time, a prompt sentence is input into the generative AI model, and an appropriate curriculum is output.

[1084] Specific behavior:

[1085] Enter a prompt into the generative AI model: "Generate an environmental science curriculum for second-year high school students based on the following Sustainable Development Goals (SDGs). Provide the following materials as teaching material data: textbook (title: Earth Environmental Science, 2nd Edition), past exam papers (period: past five years), and other supplementary materials (title: Science for a Sustainable Future). The curriculum should also include interactive test questions."

[1086] Receive and save the generated curriculum.

[1087] Step 5: Create video content

[1088] server:

[1089] The server creates video content based on the generated curriculum. Slides are generated using presentation software, and narration is added using a speech synthesis engine. Educational test questions are also interactively inserted into the video. The input is the generated curriculum, and the output is the completed video content.

[1090] Specific behavior:

[1091] Create slides: "Basics of Equations," "Calculating Probability," etc.

[1092] Add narration using a text-to-speech engine.

[1093] Educational tests are included for each chapter.

[1094] Step 6: Deliver content and tests

[1095] server:

[1096] The generated video content and educational tests are uploaded to a streaming server, and links are generated for each piece of content. These links are organized by semester and subject and stored in a database. The input is the completed video content, and the output is the provided link.

[1097] Specific behavior:

[1098] Upload the video file (e.g. "Basics of Equations.mp4" or "Probability Calculations.mp4") to the streaming server.

[1099] Each video link is generated and stored in an organized database.

[1100] Step 7: Students watch and take the test

[1101] User (student):

[1102] Students click the provided link on their device (PC, tablet, smartphone) to watch the video content and answer the interactive educational test inserted in the video. The input is the provided link and the student's viewing behavior, and the output is the submitted test answer.

[1103] Specific behavior:

[1104] The student clicks on the provided link: https: / / example.com / equations and watches the video.

[1105] Answer the test questions that appear while watching the video and submit your answers.

[1106] Step 8: Marking and feedback on answers

[1107] server:

[1108] The server uses an automatic scoring algorithm to evaluate test answers submitted by students. It analyzes the accuracy rate and level of understanding and provides real-time feedback to the student's dashboard. The input is the submitted test answers, and the output is the analysis results and feedback.

[1109] Specific behavior:

[1110] Test answers are graded using machine learning algorithms (e.g., Scikit-learn).

[1111] Correct answer rate and level of understanding are analyzed, and learning results are displayed on a dashboard.

[1112] Step 9: Selecting a curriculum from another institution

[1113] User (student):

[1114] Students can select and take courses offered by other educational institutions by searching for the target grade, subject, and educational institution name, watching videos based on the offered curriculum, and taking tests. The input is the search query, and the output is a link to the selected curriculum.

[1115] Specific behavior:

[1116] A student uses the search form to search for "School B's 3rd semester physics curriculum" and selects to take the course.

[1117] Step 10: Delivering curriculum and recording learning progress

[1118] server:

[1119] The server provides videos and tests for the selected curriculum and records the student's learning progress. The input is the link to the selected curriculum, and the output is the provided learning materials and recorded progress data.

[1120] Specific behavior:

[1121] We provided students with a video link and test for the "Physics curriculum for the third term at School B" that they selected.

[1122] Record student learning progress and display it on a dashboard.

[1123] (Application example 1)

[1124] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1125] Traditional educational systems require a lot of manual work, from setting up and generating curriculum to creating video content, and then distributing and providing feedback to students, making it difficult to provide efficient and effective education. Furthermore, low interactivity meant that students' motivation and comprehension were not sufficiently improved. Furthermore, it was difficult to provide real-time feedback or share curricula from other educational institutions, which could exacerbate educational disparities.

[1126] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1127] In this invention, the server includes means for storing a huge amount of teaching material data in a database, means for automatically generating a curriculum based on educational goals using a generation AI, means for generating video content and inserting educational tests into the videos, means for distributing the generated video content to user terminals, means for automatically scoring user answers and providing feedback on learning results, means for managing multiple educational goal settings and enabling the provision of curricula from other educational institutions, and means for real-time lecture viewing and interactive testing using smart wearable devices. This enables the provision of efficient and effective education and improves students' motivation to learn and their level of understanding.

[1128] "Teaching material data" refers to digital textbooks, past exam papers, and other learning materials used by teachers and educational institutions for educational purposes.

[1129] "Generative AI" refers to a system that uses artificial intelligence technology to automatically generate curriculum and educational content based on input data.

[1130] "Automatic curriculum generation" refers to the process in which generative AI automatically creates learning plans and course content based on the educational goals set by educational institutions.

[1131] "Video content" refers to educational multimedia files that combine audio, video, slides, etc.

[1132] "Educational tests" are questions created for educational purposes that are displayed within video content and used to gauge students' understanding.

[1133] "Delivery means" refers to the technology used to deliver video content and tests generated using the Internet or cloud services to each user's device.

[1134] "Automatic scoring" refers to the function in which the system analyzes the user's answers, determines whether they are correct, and assigns a score.

[1135] "Feedback" refers to the function of providing real-time information such as students' level of understanding and areas for improvement based on their learning results.

[1136] "Smart wearable devices" refer to interactive electronic devices that can be worn and used by a user, examples of which include smart glasses and smart watches.

[1137] "Real-time lecture viewing" refers to the function that allows students to attend lectures in real time using smart wearable devices.

[1138] An "interactive test" is a test format in which participants answer questions asked while watching a video on the spot using technologies such as voice recognition and eye tracking.

[1139] "Other educational institution curriculum" refers to the learning plans and course content offered by other schools or educational institutions that students can select and take.

[1140] This invention provides a teacher replacement system that uses generative AI models and interactive video content to improve the quality of education. This system stores a huge amount of teaching material data in a database, uses generative AI to automatically generate a curriculum based on educational goals, creates video content and educational tests, and distributes them to user devices. Furthermore, it is possible to watch lectures in real time and take interactive tests using smart wearable devices.

[1141] 1. Management of teaching material data

[1142] The server receives a huge amount of educational material data, such as textbooks and past exam questions, uploaded by school administrators and stores it in a database, which ensures that it is always accessible.

[1143] 2. Automatic curriculum generation

[1144] The server uses generative AI to automatically generate a curriculum based on the received teaching material data and educational goals. In this process, text analysis technology is used to extract important keywords and key points, and educational content is then constructed based on these.

[1145] 3. Creating video content and educational tests

[1146] The server creates video content based on the automatically generated curriculum. It generates slides based on text information, adds narration using a speech synthesis engine, and inserts educational test questions to add interactivity to the video.

[1147] 4. Content Delivery

[1148] The server uploads the generated video content and educational tests to the streaming server and distributes them to user devices.Using smart wearable devices, users can watch lectures in real time and take interactive tests.

[1149] 5. Automatic grading and feedback

[1150] The server automatically grades the user's answers and provides real-time feedback on the learning results to the user's device or smart wearable device. It also suggests additional learning based on the user's individual progress.

[1151] Specific examples

[1152] For example, suppose an educational administrator at School A sets up a "second-semester mathematics curriculum" and uploads related textbooks and past exam questions. The server receives this and uses generative AI to automatically generate lectures such as "Fundamentals of Equations" and "Probability Calculations." Test questions are inserted into the generated videos at the end of each chapter to check comprehension. Students watch these videos using smart glasses and answer each test using eye tracking and voice recognition. The server automatically grades the answers and provides feedback in real time.

[1153] Furthermore, an example of a prompt is, "Read the following passage and answer the question: Describe the automated generation and delivery of educational content. Question: What technologies are used to generate educational content?"

[1154] Specific hardware used includes smart wearable devices such as smart glasses and smart watches, and software used includes OpenCV, Transformers (Hugging Face), gTTS, and playsound.

[1155] Through the above structure and process, this educational system is able to provide efficient and effective education and improve students' motivation to learn and their level of understanding.

[1156] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1157] Step 1:

[1158] The server stores the educational material data (textbooks, past exam questions, etc.) uploaded by the school administrator in a database. The input is the data uploaded by the school administrator, and the output is the educational material data stored in the database. Specifically, the server receives the data and performs text analysis, extracts important keywords and points, and stores them in the database.

[1159] Step 2:

[1160] The server uses generative AI to automatically generate a curriculum based on educational goals. The input is stored teaching material data and educational goal settings, and the output is an automatically generated curriculum. Specifically, the generative AI model analyzes the data and generates lesson plans that suit the educational goals.

[1161] Step 3:

[1162] The server generates video content based on the automatically generated curriculum and inserts interactive educational tests into the videos. The input is the automatically generated curriculum, and the output is the video content and educational tests. Specifically, the server generates slides based on text information, adds narration using a speech synthesis engine, and inserts test questions at appropriate points.

[1163] Step 4:

[1164] The server uploads the generated video content to a streaming server and distributes it to user terminals. The input is the generated video content, and the output is a distribution link that is generated and provided to the user terminal. Specifically, the server uploads video files and provides a dedicated access point for each user.

[1165] Step 5:

[1166] Users use smart wearable devices to watch lectures in real time and take interactive tests within the videos. The input is the distribution link and the smart wearable device, and the output is the user's test answers. Specifically, users answer the tests using eye tracking and voice recognition while watching the videos.

[1167] Step 6:

[1168] The server automatically scores the user's answers and provides feedback on the learning results in real time. The input is the user's test answers, and the output is the scoring results and feedback information. Specifically, the server analyzes the answer data, performs automatic scoring, and provides feedback based on the score and level of understanding.

[1169] Step 7:

[1170] The server manages multiple educational goal settings and enables the provision of curricula from other educational institutions. The input is the curriculum data from other educational institutions and the user's curriculum selection, and the output is the video and test for the selected curriculum. Specifically, the server retrieves the selected curriculum from the database and delivers it to the user.

[1171] Step 8:

[1172] The user selects and takes a curriculum from another educational institution. The input is the user's curriculum selection, and the output is learning content and test answers based on the curriculum from the other educational institution. Specifically, the user searches for the target grade, subject, and educational institution name, views the provided curriculum, and takes the test.

[1173] The above are the specific processing steps of the system program that realizes this application example.

[1174] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1175] This invention is a teacher replacement AI system that uses artificial intelligence (AI), interactive video content, and emotion recognition technology to improve the quality of education. The system collects a huge amount of teaching material data and uses generative AI to automatically generate a curriculum based on the educational goals set by each educational institution. It also has an emotion engine that recognizes users' emotions in real time and personalizes the learning experience. Below, we will explain each major component of the system and how it works.

[1176] 1. Curriculum setting and data collection

[1177] User (School Administrator):

[1178] Users (school administrators) input educational goals (learning objectives and curriculum requirements) into the system and upload teaching material data such as textbooks, past exam questions, and other teaching materials.

[1179] Device:

[1180] The terminal transmits the information input by the school administrator to the server and uploads the teaching material data to the server.

[1181] server:

[1182] The server receives the educational goal settings and teaching material data, analyzes them, and stores them in a database. Specifically, it performs text analysis, extracts keywords and important points, and converts them into a format that is easy to search.

[1183] 2. Curriculum generation and animation

[1184] server:

[1185] The server uses generative AI to automatically generate a curriculum based on educational goals, including setting the learning sequence and selecting learning topics.

[1186] server:

[1187] The server then creates video content based on the generated curriculum. Specifically, it generates slides based on text information and adds narration using a speech synthesis engine. At the same time, it sets up educational test questions at the end of each topic.

[1188] 3. Real-time feedback from an emotion engine

[1189] server:

[1190] The server uses an emotion engine to recognize the user's emotions in real time, adjust the difficulty of educational tests based on the emotion data, and provide feedback according to the user's learning progress. The emotion engine identifies the user's emotions using facial expression analysis, voice analysis, behavior analysis, etc.

[1191] 4. Video content and test distribution

[1192] server:

[1193] The server uploads the generated video content and educational tests to the streaming server and generates links for each. These links are organized by semester and subject.

[1194] server:

[1195] The server distributes the viewing link to the user terminal. Specifically, it sends the viewing link to the terminal of the registered student, allowing them to start learning.

[1196] 5. Student viewing and testing

[1197] User (student):

[1198] The user (student) clicks on the provided link to watch the video, answers the test questions inserted in the video while watching, and sends the answers to the system.

[1199] 6. Feedback on learning results

[1200] server:

[1201] The server automatically scores the received answers and analyzes the accuracy rate and level of understanding. The results are fed back to the user's (student's) dashboard as learning results. Specifically, the score, mistakes, topics requiring additional study, etc. are displayed. Emotional data is also reflected in the learning results, personalizing the learning experience.

[1202] 7. Customization and participation in other educational institutions' curricula

[1203] User (student):

[1204] Users (students) can select and take courses from other educational institutions by searching for the relevant grade, subject, and educational institution name, and then watching videos and taking tests based on the provided curriculum.

[1205] server:

[1206] The server provides selected users with videos and tests from other educational institutions' curricula and records their learning progress.

[1207] Specific examples

[1208] For example, suppose an educational administrator at School A sets up a "second-semester mathematics curriculum" and uploads related textbooks and past exam questions. The server receives this and uses generative AI to automatically generate lectures such as "Fundamentals of Equations" and "Probability Calculations." Test questions are inserted at the end of each chapter to check comprehension. Users (students) watch these videos on their devices and answer each test. The server automatically scores the answers and provides real-time feedback. At the same time, an emotion engine recognizes the user's (student's) current emotions and adjusts the difficulty level or sends encouraging messages to further personalize the learning experience. In some cases, students can also take an excellent mathematics curriculum from another school, School B, and the server provides videos and tests accordingly.

[1209] In this way, the educational system of the present invention supports efficient learning while improving the quality of education, reduces the burden on teachers, and contributes to eliminating educational disparities.The introduction of an emotion engine is designed to make the user's learning experience more comfortable and effective.

[1210] The processing flow will be explained below.

[1211] Step 1:

[1212] User (School Administrator):

[1213] The user (school administrator) inputs educational goals (learning objectives and curriculum requirements) into the system. Specifically, they input information such as the grade, subject, learning objectives for the semester, and key learning items, and then send this information to the system.

[1214] Step 2:

[1215] User (School Administrator):

[1216] Users (school administrators) select textbooks, past exam papers, and other educational material data and upload them to the system. The uploaded data becomes the basis for generating educational content.

[1217] Step 3:

[1218] Device:

[1219] The terminal transmits the educational goal setting sent from the school administrator and the uploaded teaching material data to the server.

[1220] Step 4:

[1221] server:

[1222] The server receives the educational goal settings and teaching material data and stores them in a database. Specifically, it extracts, organizes, and stores keywords and important points related to the educational goals.

[1223] Step 5:

[1224] server:

[1225] The server uses generative AI to automatically generate a curriculum based on the received educational goal settings, including selecting the necessary topics and setting the learning sequence.

[1226] Step 6:

[1227] server:

[1228] The server creates video content based on the generated curriculum. Specifically, it generates slides based on text information and adds narration using a speech synthesis engine. At this time, it is also possible to use an emotion engine to gauge the user's emotional reactions and insert messages to boost motivation at appropriate times.

[1229] Step 7:

[1230] server:

[1231] The server inserts interactive test questions into the video, providing questions and problems at key points in the video to check comprehension, and adjusts the difficulty of the test based on the user's emotional data.

[1232] Step 8:

[1233] server:

[1234] The server uploads the generated video content and tests to a streaming server and generates viewing links, organized by semester and subject.

[1235] Step 9:

[1236] server:

[1237] The server distributes the viewing link to the user's device. The link is sent to the device of the registered student to promote learning.

[1238] Step 10:

[1239] User (student):

[1240] The user (student) clicks on the provided link to watch the video. While watching, they answer test questions inserted in the video and send their answers to the system. The system recognizes emotions from the user's behavior and facial expressions while watching, and provides appropriate motivational and encouraging messages.

[1241] Step 11:

[1242] Device:

[1243] The device sends the user's (student's) answers to the server, along with emotional data in real time, for automatic grading.

[1244] Step 12:

[1245] server:

[1246] The server automatically scores the received answers and analyzes the accuracy rate and level of understanding. The results are fed back to the user's (student's) dashboard as learning results. Emotional data is also included in the feedback to personalize the learning experience.

[1247] Step 13:

[1248] User (student):

[1249] Students can check their learning results on the dashboard and re-learn topics they have not fully understood. They can also select and take courses from other educational institutions if they wish.

[1250] Step 14:

[1251] server:

[1252] The server provides selected users with videos and tests from other educational institutions' curricula and records their learning progress. By allowing users to take high-quality curricula from other educational institutions, the quality of education is improved.

[1253] Through this series of steps, the system provides an efficient and high-quality learning environment, reducing the burden on teachers while enabling education that meets the needs of each learner. The introduction of an emotion engine makes it possible to maintain learner motivation and provide a personalized learning experience.

[1254] Example 2

[1255] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1256] Conventional educational systems place a heavy burden on individual teachers, making it difficult to provide personalized education that takes into account individual learning styles and progress. They also struggle with real-time feedback using emotion recognition and the flexible use of curricula from other educational institutions. Furthermore, there is a lack of technology to efficiently manage large amounts of teaching material data and automatically generate optimal curricula.

[1257] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1258] In this invention, the server includes means for storing a huge amount of teaching material data in a database, means for automatically generating a curriculum based on educational goals using a generative AI model, means for generating slides from text information and generating video content by adding narration using a speech synthesis engine, means for recognizing a user's emotions in real time using an emotion engine and providing feedback based on the user's learning progress, means for automatically scoring the user's answers and providing feedback on the learning results, and means for managing multiple educational goal settings and enabling the provision of curricula from other educational institutions. This makes it possible to provide personalized education according to each user's learning style and progress, thereby improving the quality of education.

[1259] "Huge amounts of educational material data" refers to a wide variety of educational materials and digital content, and the amount is extremely large, detailed, and comprehensive.

[1260] A "generative AI model" refers to a technology that uses artificial intelligence to automatically create curricula and learning plans based on user input data and requirements.

[1261] "Educational goals" are learning objectives and goals set by the user (school administrator), and serve as the basis for curriculum and lesson plans.

[1262] "Text information" refers to character data such as sentences and keywords contained in the teaching material data.

[1263] "Slides" are presentation-style materials used as part of educational content, and are primarily used to provide visual information.

[1264] A "speech synthesis engine" refers to a system or software that provides the technology to convert text data into artificially generated voice data.

[1265] "Video content" refers to educational video information provided through a combination of slides and audio narration.

[1266] An "emotion engine" refers to a technology that analyzes a user's facial expressions, voice, actions, etc. to recognize emotions and provide that information to the system.

[1267] "User terminal" refers to a device (e.g., PC, tablet, smartphone, etc.) that a user uses to access the educational system and view educational content or take tests.

[1268] A "streaming server" refers to a network server that distributes digital data such as video content and test questions in real time.

[1269] "Real-time awareness" refers to the system's ability to respond immediately to user input and actions, providing appropriate feedback and adjustments on the spot.

[1270] "Automatic scoring" refers to a technology in which the system automatically evaluates the answers submitted by the user and calculates the score and percentage of correct answers.

[1271] "Feedback" refers to information such as evaluations, advice, and corrections provided to users based on their learning progress and results.

[1272] "Educational goal setting" refers to the process in which a user registers predetermined learning goals in the system and creates a learning plan based on those goals.

[1273] "Curriculum of other educational institutions" refers to the learning plans and lesson contents provided by educational institutions other than the educational institution using the system.

[1274] "Personalization" refers to optimizing the educational content and feedback provided according to the characteristics and needs of each individual user.

[1275] This invention is an educational system that uses artificial intelligence (AI), interactive video content, and emotion recognition technology to improve the quality of education. The system collects a huge amount of educational material data and uses a generative AI model to automatically generate a curriculum based on the educational goals set by each educational institution. It also has an emotion engine that recognizes users' emotions in real time and personalizes the learning experience.

[1276] The hardware required to implement the system includes a server, a user terminal, and a streaming server. The software required includes a generative AI model (e.g., software dedicated to generative AI), a text analysis library (e.g., an NLP library), and a speech synthesis engine (e.g., a speech synthesis API).

[1277] First, the user (school administrator) enters educational goals into the system and uploads the corresponding teaching material data. The device then sends this information to the server. The server then analyzes the received educational goals and teaching material data. Specifically, it uses a Python NLP library to perform text analysis, extracting keywords and important points and storing them in a database.

[1278] The server then automatically generates a curriculum using a generative AI model. For example, GPT-4 is used as the generative AI model. The generated curriculum includes setting the learning order and selecting learning topics. The server then creates video content based on the curriculum. PowerPoint slides are generated from the text information and narration is added using a speech synthesis engine. These are then integrated using video editing software such as FFmpeg to generate the video content. At the same time, educational test questions are set at the end of each topic.

[1279] The generated video content is uploaded to a streaming server, and a viewing link is generated. The server distributes this link to the user's device. The user (student) uses the provided link to watch the video, answer the embedded test questions, and send the answers to the server. The server uses an auto-grader library to automatically grade the received answers. Feedback is displayed on the user's (student's) dashboard based on the correct answers and level of understanding. Emotional data generated by an emotion engine is also taken into account in the feedback.

[1280] The emotion engine uses Microsoft Azure Emotion API and other tools to analyze facial expressions, voice, and behavior in real time to recognize the user's emotions. For example, it can suggest taking a break if the user is tired, or adjust the difficulty of learning if the user is highly motivated.

[1281] The system also manages multiple educational goal settings and can provide curricula from other educational institutions. Users (students) can search for, view, and take courses from other educational institutions. The server provides videos and tests corresponding to the selected curriculum and records the student's learning progress.

[1282] Specific examples

[1283] For example, suppose an educational administrator at School A sets up a "second-semester mathematics curriculum" and uploads related textbooks and past exam questions. The server receives this and uses a generative AI model (e.g., GPT-4) to automatically generate lectures such as "Fundamentals of Equations" and "Probability Calculations." Test questions are inserted into the generated videos at the end of each chapter to check comprehension. Users (students) watch these videos on their devices and answer each test. The server automatically scores the answers and provides feedback in real time. At the same time, an emotion engine recognizes the user's (student's) current emotions and personalizes the learning experience by adjusting the difficulty level and sending encouraging messages.

[1284] Prompt Sentence Examples

[1285] "Generate a second-semester mathematics curriculum based on the following criteria. Coverage includes basic equations and probability calculations. Also, include test questions at the end of each chapter to assess understanding."

[1286] The introduction of this system is expected to improve the quality of education, support efficient learning, reduce the burden on teachers, and contribute to eliminating educational disparities.

[1287] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1288] Step 1:

[1289] User (school administrator)

[1290] Operation: A user logs in to the system, inputs an educational goal (e.g., "Second semester mathematics curriculum"), and uploads the corresponding teaching material data (textbooks, past exam questions) to the system.

[1291] Input: Educational goals, textbook file, past exam question file.

[1292] Output: The educational goals and teaching material data are uploaded and sent to the server.

[1293] Step 2:

[1294] Terminal

[1295] Operation: The device sends the entered educational goals and teaching material data to the server. When the user presses the upload button, the data is sent via an HTTP POST request.

[1296] Input: Educational goals, textbook files, and past exam files entered by the user into the terminal.

[1297] Output: The educational goals and teaching material data are sent to the server.

[1298] Step 3:

[1299] server

[1300] Operation: The server analyzes the received educational goals and teaching material data. It uses a Python NLP library (e.g., spaCy) to perform text analysis and extract keywords and key points. The analysis results are stored in a database.

[1301] Input: Educational goals, teaching material data (textbook files, past exam files).

[1302] Output: Analysis results (keywords, important points) are stored in a database.

[1303] Step 4:

[1304] server

[1305] Operation: The server automatically generates a curriculum using a generative AI model (e.g., GPT-4) based on the analysis results. A prompt sentence is input to the generative AI model to generate the curriculum.

[1306] Input: Analysis result, prompt statement.

[1307] Output: Auto-generated curriculum.

[1308] Step 5:

[1309] server

[1310] How it works: The server creates video content based on the generated curriculum, using text information to generate slides with Python's PPTX library, creating narration with Google Text-to-Speech API, and integrating them with FFmpeg.

[1311] Input: Auto-generated curriculum,text information.

[1312] Output: The generated video content.

[1313] Step 6:

[1314] server

[1315] Operation: The server uploads the generated video content and educational test to the streaming server and generates a viewing link, which is then sent to the user's device.

[1316] Input: Generated video content, educational tests.

[1317] Output: Viewing link.

[1318] Step 7:

[1319] User (student)

[1320] How it works: Users watch the video using the provided viewing link and answer the test questions inserted within the video. Their answers are then sent to the system.

[1321] Input: Viewing link, answers to test questions.

[1322] Output: User response data.

[1323] Step 8:

[1324] Terminal

[1325] Operation: The terminal sends the user's answer data to the server. When the user presses the "Send Answer" button, the answer data is sent via an HTTP POST request.

[1326] Input: User response data.

[1327] Output: The answer data is sent to the server.

[1328] Step 9:

[1329] server

[1330] How it works: The server automatically scores the received answer data and analyzes the level of understanding and the percentage of correct answers. It uses the Python auto-grader library to perform the scoring and analysis. It then provides real-time feedback to the user's dashboard. The feedback includes emotional data obtained using an emotion engine.

[1331] Input: Response data, emotion data.

[1332] Output: Marking results and feedback.

[1333] Step 10:

[1334] User (student)

[1335] How it works: Users can select and take courses from other educational institutions. They select their grade and subject on the system, watch videos based on the curriculum provided, and take tests.

[1336] Input: Institutional curriculum choices.

[1337] Output: Viewing and testing data.

[1338] Step 11:

[1339] server

[1340] How it works: The server provides users with selected curriculum videos and tests from other educational institutions, records their learning progress, and provides feedback.

[1341] Input: Institution curriculum, user progress data.

[1342] Output: curriculum videos, tests, progress feedback.

[1343] (Application example 2)

[1344] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1345] Traditional education systems often have uniform curricula and content, and do not adequately personalize content based on individual students' learning progress or emotions. They also lack interactive feedback and mechanisms for students to actively participate, making it difficult to maximize learning outcomes. Furthermore, they lack the flexibility to easily use curricula from other educational institutions.

[1346] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1347] In this invention, the server includes means for storing a huge amount of educational material data in a database, means for automatically generating a curriculum based on educational goals using a generation AI, means for generating video content and inserting educational tests into the videos, means for distributing the generated video content to user terminals, means for automatically scoring user answers and providing feedback on learning results, means for managing multiple educational goal settings and enabling the provision of curricula from other educational institutions, means including an emotion engine for recognizing user emotions in real time and adjusting the difficulty of educational tests based on that data, and means for providing an interactive educational experience related to the educational material. This makes it possible to provide a learning experience optimized for each user, thereby improving motivation to learn and understanding.

[1348] A "server" is a computing device that provides and manages data over a network.

[1349] A "database" is an information system for efficiently storing, managing, and searching large amounts of data.

[1350] "Generative AI" is a general term for artificial intelligence technology that automatically generates new information based on given conditions and data.

[1351] "Educational goals" are the objectives or results to be achieved through educational activities.

[1352] "Curriculum" means a set of educational content or learning plan.

[1353] "Video content" refers to dynamic video data that provides information through visual and audio means.

[1354] "Educational testing" refers to exams and quizzes used to assess a learner's understanding or proficiency.

[1355] "User terminal" refers to a computer or mobile device that is directly used by a user.

[1356] An "emotion engine" is a software technology that analyzes a user's facial expressions, voice, etc. and recognizes their emotional state.

[1357] An "interactive educational experience" is a learning activity in which users actively participate and interact with information.

[1358] This invention is an educational system that uses artificial intelligence (AI), interactive video content, and emotion recognition technology. This system collects a huge amount of educational material data and uses generative AI to automatically generate curricula based on the educational goals set by each educational institution. It also has an emotion engine that recognizes users' emotions in real time to personalize the learning experience.

[1359] The server stores a huge amount of teaching material data in a database, analyzes it, and converts it into an easily searchable format. The user (school administrator) inputs educational goals (learning objectives and curriculum requirements) into the system and uploads teaching material data such as books, past exam questions, and other teaching materials. The terminal sends this input information to the server, which analyzes it and stores it in the database. As a concrete example, a school administrator can set up a "second semester mathematics curriculum" and upload related books and past exam questions.

[1360] The server then uses generative AI to automatically generate a curriculum based on educational goals, and creates video content based on the generated curriculum. This video includes the setting of the learning order and the selection of learning topics, and narration is added using a speech synthesis engine. Educational test questions are set at the end of each topic. The generated video content is uploaded to a streaming server, and links organized by semester and subject are generated. These viewing links are distributed to registered user devices.

[1361] Users (students) click these links to watch the videos and answer the test questions inserted in the videos. The server automatically scores the answers and provides feedback on the learning results. Specifically, the user's (student's) dashboard displays the learning results, such as the score, mistakes made, and topics requiring additional study.

[1362] Furthermore, the present invention utilizes an emotion engine to recognize user emotions in real time and personalize the learning experience based on the emotion data. Specifically, the system uses facial, voice, and behavioral analysis to identify user emotions, and then adjusts the difficulty of educational tests and provides real-time feedback and encouraging messages based on the identified emotions. The system utilizes hardware and software such as OpenAI API, TensorFlow, OpenCV, and gTTS.

[1363] As a concrete example, imagine a situation where you want to send an encouraging message to a user (student) while they are viewing learning materials, such as "You will succeed." Examples of prompt sentences that can be used include the following:

[1364] "The student seems frustrated. Give encouraging words."

[1365] "Don't give up! You are doing great! Keep going and you will succeed."

[1366] In this way, the educational system of the present invention improves the quality of education, supports efficient learning, reduces the burden on teachers, and contributes to eliminating educational disparities.The introduction of an emotion engine is designed to make the user's learning experience more comfortable and effective.

[1367] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1368] Step 1:

[1369] The server receives educational goals (learning objectives and curriculum requirements) as input from the user (school administrator), and also uploads related educational material data (textbooks, past exam questions, etc.) to the database. This allows the educational goal settings and educational material data to be stored in the database. Specific operations include performing text analysis and extracting important keywords and points.

[1370] Step 2:

[1371] The server automatically generates a curriculum based on the generative AI model using the educational goals and teaching material data stored in the database. The server uses the educational goals and teaching material data as input and obtains the generated curriculum as output. Specific operations include setting the learning order and selecting learning topics.

[1372] Step 3:

[1373] The server generates video content based on the generated curriculum and inserts educational tests into the video. Using the generated curriculum as input, the server creates video content as output. Specifically, the server generates slides based on text information and adds narration using a speech synthesis engine (such as gTTS).

[1374] Step 4:

[1375] The server uploads the generated video content to the streaming server and generates a viewing link for each video. The generated video content is used as input and a viewing link is obtained as output. Specific operations include file upload processing and link generation.

[1376] Step 5:

[1377] The server distributes the viewing link to the user's device and allows the user (student) to begin learning. The viewing link is used as input and confirmation of link distribution is output. Specifically, the server sends the link to the user via email or a notification system.

[1378] Step 6:

[1379] The user (student) clicks on the provided link to watch the video and answers the test questions inserted in the video while watching. The viewing link and the user's answers are used as input, and the answer results are obtained as output. Specific operations include playing the video and submitting the test answers.

[1380] Step 7:

[1381] The server automatically scores the user's answers and provides feedback on the learning results. It uses the user's answer data as input and obtains feedback results as output. Specifically, it analyzes and automatically scores the answers, and displays the scores and analysis results of the level of understanding on a dashboard.

[1382] Step 8:

[1383] The server uses an emotion engine to recognize the user's emotions in real time and adjusts the level of difficulty and feedback based on that data. It uses the user's facial images and voice data as input, and obtains emotion analysis results and feedback as output. Specifically, it performs facial expression analysis (OpenCV) and voice analysis, and uses the OpenAI API to generate encouraging messages and other prompts.

[1384] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1385] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1386] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1387] [Fourth embodiment]

[1388] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1389] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1390] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1391] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1392] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1393] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1394] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1395] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1396] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1397] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1398] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1399] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1400] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1401] This invention is a teacher replacement AI system that uses artificial intelligence (AI) and interactive video content to improve the quality of education. This system has the ability to collect a huge amount of teaching material data and use generative AI to automatically generate a curriculum based on the educational goals set by each educational institution. Below, we will explain each major component of this system and how it works.

[1402] 1. Curriculum setting and data collection

[1403] User (School Administrator):

[1404] School administrators input educational goals (learning objectives and curriculum requirements) and upload teaching material data such as textbooks, past exam questions, and other teaching materials.

[1405] Device:

[1406] The terminal transmits the information input by the school administrator to the server and uploads the teaching material data to the server.

[1407] server:

[1408] The server receives the educational goal settings and teaching material data, analyzes them, and stores them in a database. Specifically, it performs text analysis to extract keywords and important points.

[1409] 2. Curriculum generation and animation

[1410] server:

[1411] The server uses AI to automatically generate a curriculum based on educational goals. Video content is then created based on the generated curriculum. Slides are generated based on text information, and narration is added using a speech synthesis engine. Educational test questions are also inserted into the video to add interactivity.

[1412] 3. Video content and test distribution

[1413] server:

[1414] The server uploads the generated video content and educational tests to the streaming server and generates links for each. The links are organized by semester and subject and provided to students' devices.

[1415] 4. Students listen and take the test

[1416] User (student):

[1417] Students click on the provided link to watch the video content, answer the test questions inserted in the video, and send their answers from their device to the server.

[1418] 5. Feedback on learning results

[1419] server:

[1420] The server automatically scores the answers received and analyzes the accuracy rate and level of understanding. The learning results are then fed back to the student's dashboard, which displays the score, mistakes made, and topics requiring additional study.

[1421] 6. Customization and participation in other educational institutions' curricula

[1422] User (student):

[1423] Students can select and take courses from other educational institutions by searching for the relevant grade, subject, and educational institution, and then watching videos and taking tests based on the provided curriculum.

[1424] server:

[1425] The server provides videos and tests for the selected curriculum and records the student's learning progress.

[1426] Specific examples

[1427] For example, suppose an educational administrator at School A sets up a "second-semester mathematics curriculum" and uploads related textbooks and past exam questions. The server receives this and uses generative AI to automatically generate lectures such as "Fundamentals of Equations" and "Probability Calculations." Test questions are inserted at the end of each chapter in the generated videos to check comprehension. Students watch these videos on their devices and answer each test. The server automatically grades the answers and provides feedback in real time. In some cases, students can also take an excellent mathematics curriculum from another school, School B, and the server provides them with corresponding videos and tests.

[1428] In this way, the educational system of the present invention supports efficient learning while improving the quality of education, and also contributes to eliminating educational disparities.

[1429] The processing flow will be explained below.

[1430] Step 1:

[1431] User (School Administrator):

[1432] The user (school administrator) inputs educational goals (learning objectives and curriculum requirements) into the system. Specifically, they enter information such as the grade, subject, learning objectives for the semester, and key learning items, and then send it to the system.

[1433] Step 2:

[1434] User (School Administrator):

[1435] Users (school administrators) select textbooks, past exam papers, and other teaching material data and upload them to the system, which is then added to the system's teaching material database.

[1436] Step 3:

[1437] Device:

[1438] The terminal transmits the educational goal setting sent by the user and the uploaded teaching material data to the server.

[1439] Step 4:

[1440] server:

[1441] The server analyzes the received educational goal settings and teaching material data and stores them in a database. Specifically, it performs text analysis, extracts keywords and important points, and converts them into a format that is easy to search.

[1442] Step 5:

[1443] server:

[1444] The server uses generative AI to automatically generate a curriculum based on educational goals, including setting the learning sequence and selecting learning topics.

[1445] Step 6:

[1446] server:

[1447] The server then creates video content based on the generated curriculum. Specifically, it generates slides based on text information and adds narration using a speech synthesis engine. At the same time, it sets up educational test questions at the end of each topic.

[1448] Step 7:

[1449] server:

[1450] The server uploads the generated videos and tests to a streaming server and generates viewing links, organized by semester and subject.

[1451] Step 8:

[1452] server:

[1453] The server distributes the viewing link to the user terminal. Specifically, it sends the viewing link to the terminal of the registered student, allowing them to start learning.

[1454] Step 9:

[1455] User (student):

[1456] The user (student) clicks on the provided link to watch the video, answers the test questions inserted in the video while watching, and sends the answers to the system.

[1457] Step 10:

[1458] Device:

[1459] The terminal sends the user's (student's) answers to the server, which then sends the answers in real time and automatically grades them.

[1460] Step 11:

[1461] server:

[1462] The server automatically scores the received answers and analyzes the accuracy rate and level of understanding. The results are fed back to the user's (student's) dashboard as learning results.

[1463] Step 12:

[1464] User (student):

[1465] Students can check their learning results on the dashboard and re-learn topics they have not fully understood. They can also select and take courses from other educational institutions if they wish.

[1466] Step 13:

[1467] server:

[1468] The server provides selected users with videos and tests from other educational institutions' curricula and records their learning progress, allowing users to take high-quality curricula from other educational institutions and improve the quality of their education.

[1469] Through this series of steps, the system can provide an efficient and high-quality learning environment, reduce the burden on teachers, and contribute to eliminating educational disparities.

[1470] Example 1

[1471] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1472] In conventional educational systems, the provision of teaching materials and feedback on learning results was not done in real time, resulting in issues with student learning efficiency. It was also difficult to automatically generate curricula based on educational goals, and it was difficult to share resources across multiple educational institutions. Furthermore, content that lacked interactivity made it difficult to maintain students' interest, which tended to reduce learning effectiveness.

[1473] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1474] In this invention, the server includes a means for storing a large amount of teaching material data in a database, a means for automatically generating a curriculum based on educational goals using a generative AI, a means for inputting prompts into a generative AI model and creating video content based on the curriculum, a means for inserting educational tests into the videos, a means for distributing the generated video content and educational tests to a user terminal, a means for automatically scoring user answers and providing real-time feedback on learning results, and a means for managing multiple educational goal settings and enabling the provision of curricula from other educational institutions. This enables real-time feedback on learning results, automatic generation of a curriculum based on educational goals, and resource sharing among multiple educational institutions. Furthermore, highly interactive content can maintain student interest and improve learning effectiveness.

[1475] "Vast amounts of educational material data" refers to the large amount of electronic data used for education, such as textbooks, past exam questions, and supplementary materials.

[1476] A "database" refers to a system for efficiently storing, managing, searching, and using information.

[1477] "Generative AI" refers to artificial intelligence that automatically generates natural language, images, curriculum, and more based on input data.

[1478] An "educational goal" refers to a specific objective or purpose that a student should achieve through a particular learning process.

[1479] "Curriculum" refers to learning content and educational programs that are systematically constructed based on educational goals.

[1480] A "generative AI model" refers to an artificial intelligence algorithm that learns from diverse data and generates new data and content based on that knowledge.

[1481] A "prompt sentence" refers to an input sentence that elicits a specific response or output from a generative AI model.

[1482] "Video Content" refers to educational materials in video format created for educational purposes.

[1483] "Educational test" refers to an assessment tool that includes questions designed to assess a learner's understanding and knowledge retention.

[1484] "User terminal" refers to electronic devices such as PCs, smartphones, and tablets that learners and educational institution administrators use to access and operate the system.

[1485] "Automatic scoring" refers to the process by which a system automatically evaluates and scores submitted test answers.

[1486] "Real-time feedback" refers to responding immediately to a user's actions and answers, and providing learning results and evaluations immediately.

[1487] "Setting multiple educational goals" refers to the ability of different learners and grade levels to have different educational goals and to manage these multiple goals simultaneously.

[1488] "Curriculum of other educational institutions" refers to educational programs and learning content offered at other schools or educational facilities.

[1489] This invention is a teacher replacement AI system that uses artificial intelligence (AI) and interactive video content to improve the quality of education. Specific implementation methods of this system are described below.

[1490] Curriculum setting and data collection

[1491] User (School Administrator):

[1492] School administrators log in to the system and enter educational goals (learning objectives and curriculum requirements) into an input form on a terminal. They also upload related educational material data, such as textbooks, past exam questions, and supplementary materials, to the system. Specifically, they use a web browser to perform operations from the management dashboard.

[1493] Device:

[1494] The device receives the user's input information and uploaded files and sends them to the server. The device can be a PC, tablet, smartphone, etc. This information is temporarily stored on the device, encrypted, and then sent to the server.

[1495] server:

[1496] The server receives the educational goals and teaching material data sent from the device. The received data is then analyzed to extract educational keywords and key points, which are then stored in a database. The software used includes a natural language processing (NLP) engine, which analyzes a PDF file, such as "math textbook.pdf," to extract keywords like "equation" and "probability."

[1497] Curriculum generation and animation

[1498] server:

[1499] The server automatically generates a curriculum using a generative AI model (such as GPT-3 or BERT) based on the analyzed data and the input educational goals. A prompt is input into the generative AI model to generate an appropriate curriculum. An example of a prompt is, "Generate an environmental science curriculum for second-year high school students based on the following Sustainable Development Goals (SDGs). Provide the following materials as teaching material data: textbook (title: Earth Environmental Science, 2nd Edition), past exam questions (period: past five years), and other supplementary materials (title: Science for a Sustainable Future). The curriculum should also include interactive test questions."

[1500] Video content is created based on the generated curriculum. Specifically, slides are generated using presentation software, narration is added using a speech synthesis engine (e.g., Google Cloud Text-to-Speech), and educational test questions are added to the video to make it interactive.

[1501] Video content and test delivery

[1502] server:

[1503] The server uploads the created video content and educational tests to the streaming server, generates links for each piece of content, organizes them by semester and subject, and stores them in a database, allowing students to easily access the content.

[1504] Students listen and take the test

[1505] User (student):

[1506] Students click on the provided link on their device (PC, tablet, smartphone) to watch the video content. The video also includes educational tests, and they can answer interactive tests in real time according to their learning progress.

[1507] Feedback on learning results

[1508] server:

[1509] The server uses software to automatically score the test answers submitted by students. The automatic scoring is done using machine learning algorithms (e.g., Scikit-learn) to instantly analyze the percentage of correct answers and level of understanding. The results are immediately fed back to the student's dashboard, and further study advice is provided depending on the level of understanding.

[1510] Customization and access to other educational institutions' curricula

[1511] User (student):

[1512] Students can select and take courses offered by other educational institutions by searching for the relevant grade, subject, and educational institution name, and then taking the provided curriculum videos and tests.

[1513] server:

[1514] The server provides videos and tests for selected curriculum and records students' learning progress, allowing them to improve the quality of their education and contributing to eliminating educational disparities.

[1515] The educational system of the present invention supports efficient learning while improving the quality of education, and is of great help in eliminating educational disparities.

[1516] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1517] Step 1: Setting up the curriculum and inputting teaching material data

[1518] User (School Administrator):

[1519] School administrators log in to the system and input educational goals (learning objectives and curriculum requirements) into an input form on their terminal. They also upload related educational material data, such as textbooks, past exam papers, and supplementary materials, to the system. The input information and uploaded data become input. The system then receives the educational goals and educational material data.

[1520] Specific behavior:

[1521] Access the management dashboard and enter your educational goals (e.g., "Second semester math curriculum").

[1522] Upload files such as textbooks (e.g., "Mathematics textbook.pdf") and past exam questions (e.g., "Past exam questions.zip").

[1523] Step 2: Send data from the device to the server

[1524] Device:

[1525] The information entered by the user and the files uploaded are temporarily stored inside the device. This information is then encrypted and securely sent to the server. The input is the user's input information and uploaded data, and the output is the encrypted data to be sent.

[1526] Specific behavior:

[1527] The device encrypts educational goals and teaching material data.

[1528] The encrypted data is sent to the server.

[1529] Step 3: Receiving and analyzing the teaching material data

[1530] server:

[1531] The server receives the educational goals and teaching material data sent from the device. It performs text analysis on the received data and extracts educational keywords and important points. The results of this analysis are input, and the information stored in the database is output.

[1532] Specific behavior:

[1533] The server receives "MathematicsTextbook.pdf".

[1534] Using software (NLP engine), keywords such as "equation" and "probability" are extracted.

[1535] The extracted information is stored in a database.

[1536] Step 4: The curriculum generation process

[1537] server:

[1538] The server automatically generates a curriculum using a generative AI model based on the analyzed data and the input educational goals. At this time, a prompt sentence is input into the generative AI model, and an appropriate curriculum is output.

[1539] Specific behavior:

[1540] Enter a prompt into the generative AI model: "Generate an environmental science curriculum for second-year high school students based on the following Sustainable Development Goals (SDGs). Provide the following materials as teaching material data: textbook (title: Earth Environmental Science, 2nd Edition), past exam papers (period: past five years), and other supplementary materials (title: Science for a Sustainable Future). The curriculum should also include interactive test questions."

[1541] Receive and save the generated curriculum.

[1542] Step 5: Create video content

[1543] server:

[1544] The server creates video content based on the generated curriculum. Slides are generated using presentation software, and narration is added using a speech synthesis engine. Educational test questions are also interactively inserted into the video. The input is the generated curriculum, and the output is the completed video content.

[1545] Specific behavior:

[1546] Create slides: "Basics of Equations," "Calculating Probability," etc.

[1547] Add narration using a text-to-speech engine.

[1548] Educational tests are included for each chapter.

[1549] Step 6: Deliver content and tests

[1550] server:

[1551] The generated video content and educational tests are uploaded to a streaming server, and links are generated for each piece of content. These links are organized by semester and subject and stored in a database. The input is the completed video content, and the output is the provided link.

[1552] Specific behavior:

[1553] Upload the video file (e.g. "Basics of Equations.mp4" or "Probability Calculations.mp4") to the streaming server.

[1554] Each video link is generated and stored in an organized database.

[1555] Step 7: Students watch and take the test

[1556] User (student):

[1557] Students click the provided link on their device (PC, tablet, smartphone) to watch the video content and answer the interactive educational test inserted in the video. The input is the provided link and the student's viewing behavior, and the output is the submitted test answer.

[1558] Specific behavior:

[1559] The student clicks on the provided link: https: / / example.com / equations and watches the video.

[1560] Answer the test questions that appear while watching the video and submit your answers.

[1561] Step 8: Marking and feedback on answers

[1562] server:

[1563] The server uses an automatic scoring algorithm to evaluate test answers submitted by students. It analyzes the accuracy rate and level of understanding and provides real-time feedback to the student's dashboard. The input is the submitted test answers, and the output is the analysis results and feedback.

[1564] Specific behavior:

[1565] Test answers are graded using machine learning algorithms (e.g., Scikit-learn).

[1566] Correct answer rate and level of understanding are analyzed, and learning results are displayed on a dashboard.

[1567] Step 9: Selecting a curriculum from another institution

[1568] User (student):

[1569] Students can select and take courses offered by other educational institutions by searching for the target grade, subject, and educational institution name, watching videos based on the offered curriculum, and taking tests. The input is the search query, and the output is a link to the selected curriculum.

[1570] Specific behavior:

[1571] A student uses the search form to search for "School B's 3rd semester physics curriculum" and selects to take the course.

[1572] Step 10: Delivering curriculum and recording learning progress

[1573] server:

[1574] The server provides videos and tests for the selected curriculum and records the student's learning progress. The input is the link to the selected curriculum, and the output is the provided learning materials and recorded progress data.

[1575] Specific behavior:

[1576] We provided students with a video link and test for the "Physics curriculum for the third term at School B" that they selected.

[1577] Record student learning progress and display it on a dashboard.

[1578] (Application example 1)

[1579] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1580] Traditional educational systems require a lot of manual work, from setting up and generating curriculum to creating video content, and then distributing and providing feedback to students, making it difficult to provide efficient and effective education. Furthermore, low interactivity meant that students' motivation and comprehension were not sufficiently improved. Furthermore, it was difficult to provide real-time feedback or share curricula from other educational institutions, which could exacerbate educational disparities.

[1581] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1582] In this invention, the server includes means for storing a huge amount of teaching material data in a database, means for automatically generating a curriculum based on educational goals using a generation AI, means for generating video content and inserting educational tests into the videos, means for distributing the generated video content to user terminals, means for automatically scoring user answers and providing feedback on learning results, means for managing multiple educational goal settings and enabling the provision of curricula from other educational institutions, and means for real-time lecture viewing and interactive testing using smart wearable devices. This enables the provision of efficient and effective education and improves students' motivation to learn and their level of understanding.

[1583] "Teaching material data" refers to digital textbooks, past exam papers, and other learning materials used by teachers and educational institutions for educational purposes.

[1584] "Generative AI" refers to a system that uses artificial intelligence technology to automatically generate curriculum and educational content based on input data.

[1585] "Automatic curriculum generation" refers to the process in which generative AI automatically creates learning plans and course content based on the educational goals set by educational institutions.

[1586] "Video content" refers to educational multimedia files that combine audio, video, slides, etc.

[1587] "Educational tests" are questions created for educational purposes that are displayed within video content and used to gauge students' understanding.

[1588] "Delivery means" refers to the technology used to deliver video content and tests generated using the Internet or cloud services to each user's device.

[1589] "Automatic scoring" refers to the function in which the system analyzes the user's answers, determines whether they are correct, and assigns a score.

[1590] "Feedback" refers to the function of providing real-time information such as students' level of understanding and areas for improvement based on their learning results.

[1591] "Smart wearable devices" refer to interactive electronic devices that can be worn and used by a user, examples of which include smart glasses and smart watches.

[1592] "Real-time lecture viewing" refers to the function that allows students to attend lectures in real time using smart wearable devices.

[1593] An "interactive test" is a test format in which participants answer questions asked while watching a video on the spot using technologies such as voice recognition and eye tracking.

[1594] "Other educational institution curriculum" refers to the learning plans and course content offered by other schools or educational institutions that students can select and take.

[1595] This invention provides a teacher replacement system that uses generative AI models and interactive video content to improve the quality of education. This system stores a huge amount of teaching material data in a database, uses generative AI to automatically generate a curriculum based on educational goals, creates video content and educational tests, and distributes them to user devices. Furthermore, it is possible to watch lectures in real time and take interactive tests using smart wearable devices.

[1596] 1. Management of teaching material data

[1597] The server receives a huge amount of educational material data, such as textbooks and past exam questions, uploaded by school administrators and stores it in a database, which ensures that it is always accessible.

[1598] 2. Automatic curriculum generation

[1599] The server uses generative AI to automatically generate a curriculum based on the received teaching material data and educational goals. In this process, text analysis technology is used to extract important keywords and key points, and educational content is then constructed based on these.

[1600] 3. Creating video content and educational tests

[1601] The server creates video content based on the automatically generated curriculum. It generates slides based on text information, adds narration using a speech synthesis engine, and inserts educational test questions to add interactivity to the video.

[1602] 4. Content Delivery

[1603] The server uploads the generated video content and educational tests to the streaming server and distributes them to user devices.Using smart wearable devices, users can watch lectures in real time and take interactive tests.

[1604] 5. Automatic grading and feedback

[1605] The server automatically grades the user's answers and provides real-time feedback on the learning results to the user's device or smart wearable device. It also suggests additional learning based on the user's individual progress.

[1606] Specific examples

[1607] For example, suppose an educational administrator at School A sets up a "second-semester mathematics curriculum" and uploads related textbooks and past exam questions. The server receives this and uses generative AI to automatically generate lectures such as "Fundamentals of Equations" and "Probability Calculations." Test questions are inserted into the generated videos at the end of each chapter to check comprehension. Students watch these videos using smart glasses and answer each test using eye tracking and voice recognition. The server automatically grades the answers and provides feedback in real time.

[1608] Furthermore, an example of a prompt is, "Read the following passage and answer the question: Describe the automated generation and delivery of educational content. Question: What technologies are used to generate educational content?"

[1609] Specific hardware used includes smart wearable devices such as smart glasses and smart watches, and software used includes OpenCV, Transformers (Hugging Face), gTTS, and playsound.

[1610] Through the above structure and process, this educational system is able to provide efficient and effective education and improve students' motivation to learn and their level of understanding.

[1611] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1612] Step 1:

[1613] The server stores the educational material data (textbooks, past exam questions, etc.) uploaded by the school administrator in a database. The input is the data uploaded by the school administrator, and the output is the educational material data stored in the database. Specifically, the server receives the data and performs text analysis, extracts important keywords and points, and stores them in the database.

[1614] Step 2:

[1615] The server uses generative AI to automatically generate a curriculum based on educational goals. The input is stored teaching material data and educational goal settings, and the output is an automatically generated curriculum. Specifically, the generative AI model analyzes the data and generates lesson plans that suit the educational goals.

[1616] Step 3:

[1617] The server generates video content based on the automatically generated curriculum and inserts interactive educational tests into the videos. The input is the automatically generated curriculum, and the output is the video content and educational tests. Specifically, the server generates slides based on text information, adds narration using a speech synthesis engine, and inserts test questions at appropriate points.

[1618] Step 4:

[1619] The server uploads the generated video content to a streaming server and distributes it to user terminals. The input is the generated video content, and the output is a distribution link that is generated and provided to the user terminal. Specifically, the server uploads video files and provides a dedicated access point for each user.

[1620] Step 5:

[1621] Users use smart wearable devices to watch lectures in real time and take interactive tests within the videos. The input is the distribution link and the smart wearable device, and the output is the user's test answers. Specifically, users answer the tests using eye tracking and voice recognition while watching the videos.

[1622] Step 6:

[1623] The server automatically scores the user's answers and provides feedback on the learning results in real time. The input is the user's test answers, and the output is the scoring results and feedback information. Specifically, the server analyzes the answer data, performs automatic scoring, and provides feedback based on the score and level of understanding.

[1624] Step 7:

[1625] The server manages multiple educational goal settings and enables the provision of curricula from other educational institutions. The input is the curriculum data from other educational institutions and the user's curriculum selection, and the output is the video and test for the selected curriculum. Specifically, the server retrieves the selected curriculum from the database and delivers it to the user.

[1626] Step 8:

[1627] The user selects and takes a curriculum from another educational institution. The input is the user's curriculum selection, and the output is learning content and test answers based on the curriculum from the other educational institution. Specifically, the user searches for the target grade, subject, and educational institution name, views the provided curriculum, and takes the test.

[1628] The above are the specific processing steps of the system program that realizes this application example.

[1629] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1630] This invention is a teacher replacement AI system that uses artificial intelligence (AI), interactive video content, and emotion recognition technology to improve the quality of education. The system collects a huge amount of teaching material data and uses generative AI to automatically generate a curriculum based on the educational goals set by each educational institution. It also has an emotion engine that recognizes users' emotions in real time and personalizes the learning experience. Below, we will explain each major component of the system and how it works.

[1631] 1. Curriculum setting and data collection

[1632] User (School Administrator):

[1633] Users (school administrators) input educational goals (learning objectives and curriculum requirements) into the system and upload teaching material data such as textbooks, past exam questions, and other teaching materials.

[1634] Device:

[1635] The terminal transmits the information input by the school administrator to the server and uploads the teaching material data to the server.

[1636] server:

[1637] The server receives the educational goal settings and teaching material data, analyzes them, and stores them in a database. Specifically, it performs text analysis, extracts keywords and important points, and converts them into a format that is easy to search.

[1638] 2. Curriculum generation and animation

[1639] server:

[1640] The server uses generative AI to automatically generate a curriculum based on educational goals, including setting the learning sequence and selecting learning topics.

[1641] server:

[1642] The server then creates video content based on the generated curriculum. Specifically, it generates slides based on text information and adds narration using a speech synthesis engine. At the same time, it sets up educational test questions at the end of each topic.

[1643] 3. Real-time feedback from an emotion engine

[1644] server:

[1645] The server uses an emotion engine to recognize the user's emotions in real time, adjust the difficulty of educational tests based on the emotion data, and provide feedback according to the user's learning progress. The emotion engine identifies the user's emotions using facial expression analysis, voice analysis, behavior analysis, etc.

[1646] 4. Video content and test distribution

[1647] server:

[1648] The server uploads the generated video content and educational tests to the streaming server and generates links for each. These links are organized by semester and subject.

[1649] server:

[1650] The server distributes the viewing link to the user terminal. Specifically, it sends the viewing link to the terminal of the registered student, allowing them to start learning.

[1651] 5. Student viewing and testing

[1652] User (student):

[1653] The user (student) clicks on the provided link to watch the video, answers the test questions inserted in the video while watching, and sends the answers to the system.

[1654] 6. Feedback on learning results

[1655] server:

[1656] The server automatically scores the received answers and analyzes the accuracy rate and level of understanding. The results are fed back to the user's (student's) dashboard as learning results. Specifically, the score, mistakes, topics requiring additional study, etc. are displayed. Emotional data is also reflected in the learning results, personalizing the learning experience.

[1657] 7. Customization and participation in other educational institutions' curricula

[1658] User (student):

[1659] Users (students) can select and take courses from other educational institutions by searching for the relevant grade, subject, and educational institution name, and then watching videos and taking tests based on the provided curriculum.

[1660] server:

[1661] The server provides selected users with videos and tests from other educational institutions' curricula and records their learning progress.

[1662] Specific examples

[1663] For example, suppose an educational administrator at School A sets up a "second-semester mathematics curriculum" and uploads related textbooks and past exam questions. The server receives this and uses generative AI to automatically generate lectures such as "Fundamentals of Equations" and "Probability Calculations." Test questions are inserted at the end of each chapter to check comprehension. Users (students) watch these videos on their devices and answer each test. The server automatically scores the answers and provides real-time feedback. At the same time, an emotion engine recognizes the user's (student's) current emotions and adjusts the difficulty level or sends encouraging messages to further personalize the learning experience. In some cases, students can also take an excellent mathematics curriculum from another school, School B, and the server provides videos and tests accordingly.

[1664] In this way, the educational system of the present invention supports efficient learning while improving the quality of education, reduces the burden on teachers, and contributes to eliminating educational disparities.The introduction of an emotion engine is designed to make the user's learning experience more comfortable and effective.

[1665] The processing flow will be explained below.

[1666] Step 1:

[1667] User (School Administrator):

[1668] The user (school administrator) inputs educational goals (learning objectives and curriculum requirements) into the system. Specifically, they input information such as the grade, subject, learning objectives for the semester, and key learning items, and then send this information to the system.

[1669] Step 2:

[1670] User (School Administrator):

[1671] Users (school administrators) select textbooks, past exam papers, and other educational material data and upload them to the system. The uploaded data becomes the basis for generating educational content.

[1672] Step 3:

[1673] Device:

[1674] The terminal transmits the educational goal setting sent from the school administrator and the uploaded teaching material data to the server.

[1675] Step 4:

[1676] server:

[1677] The server receives the educational goal settings and teaching material data and stores them in a database. Specifically, it extracts, organizes, and stores keywords and important points related to the educational goals.

[1678] Step 5:

[1679] server:

[1680] The server uses generative AI to automatically generate a curriculum based on the received educational goal settings, including selecting the necessary topics and setting the learning sequence.

[1681] Step 6:

[1682] server:

[1683] The server creates video content based on the generated curriculum. Specifically, it generates slides based on text information and adds narration using a speech synthesis engine. At this time, it is also possible to use an emotion engine to gauge the user's emotional reactions and insert messages to boost motivation at appropriate times.

[1684] Step 7:

[1685] server:

[1686] The server inserts interactive test questions into the video, providing questions and problems at key points in the video to check comprehension, and adjusts the difficulty of the test based on the user's emotional data.

[1687] Step 8:

[1688] server:

[1689] The server uploads the generated video content and tests to a streaming server and generates viewing links, organized by semester and subject.

[1690] Step 9:

[1691] server:

[1692] The server distributes the viewing link to the user's device. The link is sent to the device of the registered student to promote learning.

[1693] Step 10:

[1694] User (student):

[1695] The user (student) clicks on the provided link to watch the video. While watching, they answer test questions inserted in the video and send their answers to the system. The system recognizes emotions from the user's behavior and facial expressions while watching, and provides appropriate motivational and encouraging messages.

[1696] Step 11:

[1697] Device:

[1698] The device sends the user's (student's) answers to the server, along with emotional data in real time, for automatic grading.

[1699] Step 12:

[1700] server:

[1701] The server automatically scores the received answers and analyzes the accuracy rate and level of understanding. The results are fed back to the user's (student's) dashboard as learning results. Emotional data is also included in the feedback to personalize the learning experience.

[1702] Step 13:

[1703] User (student):

[1704] Students can check their learning results on the dashboard and re-learn topics they have not fully understood. They can also select and take courses from other educational institutions if they wish.

[1705] Step 14:

[1706] server:

[1707] The server provides selected users with videos and tests from other educational institutions' curricula and records their learning progress. By allowing users to take high-quality curricula from other educational institutions, the quality of education is improved.

[1708] Through this series of steps, the system provides an efficient and high-quality learning environment, reducing the burden on teachers while enabling education that meets the needs of each learner. The introduction of an emotion engine makes it possible to maintain learner motivation and provide a personalized learning experience.

[1709] Example 2

[1710] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1711] Conventional educational systems place a heavy burden on individual teachers, making it difficult to provide personalized education that takes into account individual learning styles and progress. They also struggle with real-time feedback using emotion recognition and the flexible use of curricula from other educational institutions. Furthermore, there is a lack of technology to efficiently manage large amounts of teaching material data and automatically generate optimal curricula.

[1712] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1713] In this invention, the server includes means for storing a huge amount of teaching material data in a database, means for automatically generating a curriculum based on educational goals using a generative AI model, means for generating slides from text information and generating video content by adding narration using a speech synthesis engine, means for recognizing a user's emotions in real time using an emotion engine and providing feedback based on the user's learning progress, means for automatically scoring the user's answers and providing feedback on the learning results, and means for managing multiple educational goal settings and enabling the provision of curricula from other educational institutions. This makes it possible to provide personalized education according to each user's learning style and progress, thereby improving the quality of education.

[1714] "Huge amounts of educational material data" refers to a wide variety of educational materials and digital content, and the amount is extremely large, detailed, and comprehensive.

[1715] A "generative AI model" refers to a technology that uses artificial intelligence to automatically create curricula and learning plans based on user input data and requirements.

[1716] "Educational goals" are learning objectives and goals set by the user (school administrator), and serve as the basis for curriculum and lesson plans.

[1717] "Text information" refers to character data such as sentences and keywords contained in the teaching material data.

[1718] "Slides" are presentation-style materials used as part of educational content, and are primarily used to provide visual information.

[1719] A "speech synthesis engine" refers to a system or software that provides the technology to convert text data into artificially generated voice data.

[1720] "Video content" refers to educational video information provided through a combination of slides and audio narration.

[1721] An "emotion engine" refers to a technology that analyzes a user's facial expressions, voice, actions, etc. to recognize emotions and provide that information to the system.

[1722] "User terminal" refers to a device (e.g., PC, tablet, smartphone, etc.) that a user uses to access the educational system and view educational content or take tests.

[1723] A "streaming server" refers to a network server that distributes digital data such as video content and test questions in real time.

[1724] "Real-time awareness" refers to the system's ability to respond immediately to user input and actions, providing appropriate feedback and adjustments on the spot.

[1725] "Automatic scoring" refers to a technology in which the system automatically evaluates the answers submitted by the user and calculates the score and percentage of correct answers.

[1726] "Feedback" refers to information such as evaluations, advice, and corrections provided to users based on their learning progress and results.

[1727] "Educational goal setting" refers to the process in which a user registers predetermined learning goals in the system and creates a learning plan based on those goals.

[1728] "Curriculum of other educational institutions" refers to the learning plans and lesson contents provided by educational institutions other than the educational institution using the system.

[1729] "Personalization" refers to optimizing the educational content and feedback provided according to the characteristics and needs of each individual user.

[1730] This invention is an educational system that uses artificial intelligence (AI), interactive video content, and emotion recognition technology to improve the quality of education. The system collects a huge amount of educational material data and uses a generative AI model to automatically generate a curriculum based on the educational goals set by each educational institution. It also has an emotion engine that recognizes users' emotions in real time and personalizes the learning experience.

[1731] The hardware required to implement the system includes a server, a user terminal, and a streaming server. The software required includes a generative AI model (e.g., software dedicated to generative AI), a text analysis library (e.g., an NLP library), and a speech synthesis engine (e.g., a speech synthesis API).

[1732] First, the user (school administrator) enters educational goals into the system and uploads the corresponding teaching material data. The device then sends this information to the server. The server then analyzes the received educational goals and teaching material data. Specifically, it uses a Python NLP library to perform text analysis, extracting keywords and important points and storing them in a database.

[1733] The server then automatically generates a curriculum using a generative AI model. For example, GPT-4 is used as the generative AI model. The generated curriculum includes setting the learning order and selecting learning topics. The server then creates video content based on the curriculum. PowerPoint slides are generated from the text information and narration is added using a speech synthesis engine. These are then integrated using video editing software such as FFmpeg to generate the video content. At the same time, educational test questions are set at the end of each topic.

[1734] The generated video content is uploaded to a streaming server, and a viewing link is generated. The server distributes this link to the user's device. The user (student) uses the provided link to watch the video, answer the embedded test questions, and send the answers to the server. The server uses an auto-grader library to automatically grade the received answers. Feedback is displayed on the user's (student's) dashboard based on the correct answers and level of understanding. Emotional data generated by an emotion engine is also taken into account in the feedback.

[1735] The emotion engine uses Microsoft Azure Emotion API and other tools to analyze facial expressions, voice, and behavior in real time to recognize the user's emotions. For example, it can suggest taking a break if the user is tired, or adjust the difficulty of learning if the user is highly motivated.

[1736] The system also manages multiple educational goal settings and can provide curricula from other educational institutions. Users (students) can search for, view, and take courses from other educational institutions. The server provides videos and tests corresponding to the selected curriculum and records the student's learning progress.

[1737] Specific examples

[1738] For example, suppose an educational administrator at School A sets up a "second-semester mathematics curriculum" and uploads related textbooks and past exam questions. The server receives this and uses a generative AI model (e.g., GPT-4) to automatically generate lectures such as "Fundamentals of Equations" and "Probability Calculations." Test questions are inserted into the generated videos at the end of each chapter to check comprehension. Users (students) watch these videos on their devices and answer each test. The server automatically scores the answers and provides feedback in real time. At the same time, an emotion engine recognizes the user's (student's) current emotions and personalizes the learning experience by adjusting the difficulty level and sending encouraging messages.

[1739] Prompt Sentence Examples

[1740] "Generate a second-semester mathematics curriculum based on the following criteria. Coverage includes basic equations and probability calculations. Also, include test questions at the end of each chapter to assess understanding."

[1741] The introduction of this system is expected to improve the quality of education, support efficient learning, reduce the burden on teachers, and contribute to eliminating educational disparities.

[1742] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1743] Step 1:

[1744] User (school administrator)

[1745] Operation: A user logs in to the system, inputs an educational goal (e.g., "Second semester mathematics curriculum"), and uploads the corresponding teaching material data (textbooks, past exam questions) to the system.

[1746] Input: Educational goals, textbook file, past exam question file.

[1747] Output: The educational goals and teaching material data are uploaded and sent to the server.

[1748] Step 2:

[1749] Terminal

[1750] Operation: The device sends the entered educational goals and teaching material data to the server. When the user presses the upload button, the data is sent via an HTTP POST request.

[1751] Input: Educational goals, textbook files, and past exam files entered by the user into the terminal.

[1752] Output: The educational goals and teaching material data are sent to the server.

[1753] Step 3:

[1754] server

[1755] Operation: The server analyzes the received educational goals and teaching material data. It uses a Python NLP library (e.g., spaCy) to perform text analysis and extract keywords and key points. The analysis results are stored in a database.

[1756] Input: Educational goals, teaching material data (textbook files, past exam files).

[1757] Output: Analysis results (keywords, important points) are stored in a database.

[1758] Step 4:

[1759] server

[1760] Operation: The server automatically generates a curriculum using a generative AI model (e.g., GPT-4) based on the analysis results. A prompt sentence is input to the generative AI model to generate the curriculum.

[1761] Input: Analysis result, prompt statement.

[1762] Output: Auto-generated curriculum.

[1763] Step 5:

[1764] server

[1765] How it works: The server creates video content based on the generated curriculum, using text information to generate slides with Python's PPTX library, creating narration with Google Text-to-Speech API, and integrating them with FFmpeg.

[1766] Input: Auto-generated curriculum,text information.

[1767] Output: The generated video content.

[1768] Step 6:

[1769] server

[1770] Operation: The server uploads the generated video content and educational test to the streaming server and generates a viewing link, which is then sent to the user's device.

[1771] Input: Generated video content, educational tests.

[1772] Output: Viewing link.

[1773] Step 7:

[1774] User (student)

[1775] How it works: Users watch the video using the provided viewing link and answer the test questions inserted within the video. Their answers are then sent to the system.

[1776] Input: Viewing link, answers to test questions.

[1777] Output: User response data.

[1778] Step 8:

[1779] Terminal

[1780] Operation: The terminal sends the user's answer data to the server. When the user presses the "Send Answer" button, the answer data is sent via an HTTP POST request.

[1781] Input: User response data.

[1782] Output: The answer data is sent to the server.

[1783] Step 9:

[1784] server

[1785] How it works: The server automatically scores the received answer data and analyzes the level of understanding and the percentage of correct answers. It uses the Python auto-grader library to perform the scoring and analysis. It then provides real-time feedback to the user's dashboard. The feedback includes emotional data obtained using an emotion engine.

[1786] Input: Response data, emotion data.

[1787] Output: Marking results and feedback.

[1788] Step 10:

[1789] User (student)

[1790] How it works: Users can select and take courses from other educational institutions. They select their grade and subject on the system, watch videos based on the curriculum provided, and take tests.

[1791] Input: Institutional curriculum choices.

[1792] Output: Viewing and testing data.

[1793] Step 11:

[1794] server

[1795] How it works: The server provides users with selected curriculum videos and tests from other educational institutions, records their learning progress, and provides feedback.

[1796] Input: Institution curriculum, user progress data.

[1797] Output: curriculum videos, tests, progress feedback.

[1798] (Application example 2)

[1799] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1800] Traditional education systems often have uniform curricula and content, and do not adequately personalize content based on individual students' learning progress or emotions. They also lack interactive feedback and mechanisms for students to actively participate, making it difficult to maximize learning outcomes. Furthermore, they lack the flexibility to easily use curricula from other educational institutions.

[1801] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1802] In this invention, the server includes means for storing a huge amount of educational material data in a database, means for automatically generating a curriculum based on educational goals using a generation AI, means for generating video content and inserting educational tests into the videos, means for distributing the generated video content to user terminals, means for automatically scoring user answers and providing feedback on learning results, means for managing multiple educational goal settings and enabling the provision of curricula from other educational institutions, means including an emotion engine for recognizing user emotions in real time and adjusting the difficulty of educational tests based on that data, and means for providing an interactive educational experience related to the educational material. This makes it possible to provide a learning experience optimized for each user, thereby improving motivation to learn and understanding.

[1803] A "server" is a computing device that provides and manages data over a network.

[1804] A "database" is an information system for efficiently storing, managing, and searching large amounts of data.

[1805] "Generative AI" is a general term for artificial intelligence technology that automatically generates new information based on given conditions and data.

[1806] "Educational goals" are the objectives or results to be achieved through educational activities.

[1807] "Curriculum" means a set of educational content or learning plan.

[1808] "Video content" refers to dynamic video data that provides information through visual and audio means.

[1809] "Educational testing" refers to exams and quizzes used to assess a learner's understanding or proficiency.

[1810] "User terminal" refers to a computer or mobile device that is directly used by a user.

[1811] An "emotion engine" is a software technology that analyzes a user's facial expressions, voice, etc. and recognizes their emotional state.

[1812] An "interactive educational experience" is a learning activity in which users actively participate and interact with information.

[1813] This invention is an educational system that uses artificial intelligence (AI), interactive video content, and emotion recognition technology. This system collects a huge amount of educational material data and uses generative AI to automatically generate curricula based on the educational goals set by each educational institution. It also has an emotion engine that recognizes users' emotions in real time to personalize the learning experience.

[1814] The server stores a huge amount of teaching material data in a database, analyzes it, and converts it into an easily searchable format. The user (school administrator) inputs educational goals (learning objectives and curriculum requirements) into the system and uploads teaching material data such as books, past exam questions, and other teaching materials. The terminal sends this input information to the server, which analyzes it and stores it in the database. As a concrete example, a school administrator can set up a "second semester mathematics curriculum" and upload related books and past exam questions.

[1815] The server then uses generative AI to automatically generate a curriculum based on educational goals, and creates video content based on the generated curriculum. This video includes the setting of the learning order and the selection of learning topics, and narration is added using a speech synthesis engine. Educational test questions are set at the end of each topic. The generated video content is uploaded to a streaming server, and links organized by semester and subject are generated. These viewing links are distributed to registered user devices.

[1816] Users (students) click these links to watch the videos and answer the test questions inserted in the videos. The server automatically scores the answers and provides feedback on the learning results. Specifically, the user's (student's) dashboard displays the learning results, such as the score, mistakes made, and topics requiring additional study.

[1817] Furthermore, the present invention utilizes an emotion engine to recognize user emotions in real time and personalize the learning experience based on the emotion data. Specifically, the system uses facial, voice, and behavioral analysis to identify user emotions, and then adjusts the difficulty of educational tests and provides real-time feedback and encouraging messages based on the identified emotions. The system utilizes hardware and software such as OpenAI API, TensorFlow, OpenCV, and gTTS.

[1818] As a concrete example, imagine a situation where you want to send an encouraging message to a user (student) while they are viewing learning materials, such as "You will succeed." Examples of prompt sentences that can be used include the following:

[1819] "The student seems frustrated. Give encouraging words."

[1820] "Don't give up! You are doing great! Keep going and you will succeed."

[1821] In this way, the educational system of the present invention improves the quality of education, supports efficient learning, reduces the burden on teachers, and contributes to eliminating educational disparities.The introduction of an emotion engine is designed to make the user's learning experience more comfortable and effective.

[1822] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1823] Step 1:

[1824] The server receives educational goals (learning objectives and curriculum requirements) as input from the user (school administrator), and also uploads related educational material data (textbooks, past exam questions, etc.) to the database. This allows the educational goal settings and educational material data to be stored in the database. Specific operations include performing text analysis and extracting important keywords and points.

[1825] Step 2:

[1826] The server automatically generates a curriculum based on the generative AI model using the educational goals and teaching material data stored in the database. The server uses the educational goals and teaching material data as input and obtains the generated curriculum as output. Specific operations include setting the learning order and selecting learning topics.

[1827] Step 3:

[1828] The server generates video content based on the generated curriculum and inserts educational tests into the video. Using the generated curriculum as input, the server creates video content as output. Specifically, the server generates slides based on text information and adds narration using a speech synthesis engine (such as gTTS).

[1829] Step 4:

[1830] The server uploads the generated video content to the streaming server and generates a viewing link for each video. The generated video content is used as input and a viewing link is obtained as output. Specific operations include file upload processing and link generation.

[1831] Step 5:

[1832] The server distributes the viewing link to the user's device and allows the user (student) to begin learning. The viewing link is used as input and confirmation of link distribution is output. Specifically, the server sends the link to the user via email or a notification system.

[1833] Step 6:

[1834] The user (student) clicks on the provided link to watch the video and answers the test questions inserted in the video while watching. The viewing link and the user's answers are used as input, and the answer results are obtained as output. Specific operations include playing the video and submitting the test answers.

[1835] Step 7:

[1836] The server automatically scores the user's answers and provides feedback on the learning results. It uses the user's answer data as input and obtains feedback results as ...

Claims

1. A means of storing a huge amount of teaching material data in a database, A means for automatically generating a curriculum based on educational goals using generative AI; means for generating video content and inserting educational tests into the video; means for distributing the generated video content to a user terminal; A means for automatically scoring the user's answers and providing feedback on the learning results; A means to manage multiple educational goal settings and provide curricula from other educational institutions, education system, including

2. 10. The educational system of claim 1, further comprising means for providing real-time feedback within the video content to enhance interactivity.

3. 2. The education system according to claim 1, further comprising a function for allowing users to post comments, and means for analyzing collected comments and reflecting the results in the curriculum.

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