system

Abstract

We provide the system. [Solution] A means of generating an educational plan tailored to a child's learning goals, A means of presenting learning content delivered based on individualized educational plans, A means for recording and analyzing the user's learning progress, Means for adjusting the educational plan based on the analysis results, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] With the increase in international marriages, children are forced to choose between the educational systems of two countries. In particular, there is a shortage of tools to efficiently support Japanese compulsory education, and there is a problem that it is difficult for children to appropriately understand and acquire the Japanese language and culture. Furthermore, it is difficult to adjust learning based on individual progress, and there is a problem that the means for users to obtain feedback for improving the quality of learning is limited.

Means for Solving the Problems

[0005] This invention provides a means to solve the aforementioned problems by generating an educational plan optimized for a child's learning goals and delivering learning content based on that individual educational plan. Furthermore, it realizes a personalized learning experience by recording and analyzing the user's learning progress and flexibly adjusting the educational plan based on the analysis results. It also helps children deepen their cultural understanding by quickly resolving questions using a real-time question-answering function and providing interactive content about Japanese culture.

[0006] An "educational plan" refers to the framework and content of learning designed based on the individual goals and progress of the learners.

[0007] "Learning content" refers to materials, assignments, activities, and other media provided to support learning based on an educational plan.

[0008] "Progress records" refer to the act of saving and managing the achievements, unfulfilled items, and level of accomplishment of learners as they progress through the educational plan.

[0009] "Analysis" refers to the process of thoroughly evaluating learners' understanding and data based on progress records, and identifying challenges and areas for improvement.

[0010] "Real-time question answering function" refers to the system's ability to provide immediate answers to learners' questions and inquiries.

[0011] "Interactive content" refers to learning materials designed to encourage active user participation and facilitate the acquisition of experience and knowledge through two-way communication. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0013] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0014] First, the language used in the following description will be explained.

[0015] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0016] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0018] In the following embodiments, the numbered communication I / F (Interface) is an interface that includes a communication processor, an antenna, and the like. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0019] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0023] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0025] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0026] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0027] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0031] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0032] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0033] The system of the present invention provides users with a personalized learning experience, enabling the generation of educational plans, presentation of learning content, recording and analysis of progress, adjustment of plans, real-time question answering, and delivery of interactive cultural content. This allows users to efficiently acquire Japanese compulsory education and culture.

[0034] The server's first step is to generate an educational plan based on the individual information provided by the user. The server considers the child's age, grade level, and educational goals, and creates a curriculum that conforms to the Japanese compulsory education curriculum guidelines. This ensures that the content is best suited to the learner.

[0035] When a user begins their daily learning activities through their device, the device displays learning content provided by the server. This includes video materials, text materials, and workbooks, each organized according to the educational plan.

[0036] Progress tracking is extremely important. The terminal continuously records completed tasks and test results and sends them to the server. The server collects this data and analyzes the user's understanding and progress. Based on the analysis, the server adjusts the educational plan and provides additional materials tailored to the user's progress and areas of weakness.

[0037] When a user has a question, they can input it in real time through their device. The server's AI receives the question and provides an immediate answer. This allows learners to resolve their questions quickly.

[0038] Furthermore, as part of cultural learning, the server delivers interactive content to the terminals. This includes lectures on traditional Japanese events and the formation of history, as well as quizzes about cultural customs. Through this, users can deepen their understanding of Japanese culture.

[0039] Through the process described above, this system provides users with a comprehensive and personalized educational experience, efficiently meeting Japanese educational requirements while accommodating learning in a multicultural environment. For example, when learning new kanji characters, the device visually displays how to write them and provides examples of their usage, including pronunciation, to aid user understanding. This allows learners to improve their Japanese language skills in an enjoyable and effective way.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] Users register with the system using their device and enter information such as their child's age, grade level, and learning goals. Users also select the goals they wish to achieve in their current area of ​​education.

[0043] Step 2:

[0044] Based on the information received from the user, the server generates an initial educational plan. Following the Japanese compulsory education curriculum guidelines, the server designs a curriculum for subjects such as Japanese language, mathematics, social studies, and science that is tailored to the participants' needs.

[0045] Step 3:

[0046] Based on the educational plan generated by the server, daily learning content is designed and delivered to the devices. This content includes video materials, texts, quizzes, and practical exercises.

[0047] Step 4:

[0048] Users access content through their devices and progress through their learning. Users reinforce their knowledge by watching learning materials and solving assignments. If questions arise, users can use the question function on their devices to make inquiries.

[0049] Step 5:

[0050] The generating AI receives questions from users and provides immediate answers. The server presents relevant additional materials to support the user's understanding.

[0051] Step 6:

[0052] The device records the user's learning progress. This progress includes the number of completed assignments, test results, and teacher evaluations. This data is sent to the server as a learning history.

[0053] Step 7:

[0054] The server analyzes progress data to identify areas where the user is struggling. Based on the analysis results, the educational plan is adjusted, and content is redesigned to strengthen remedial instruction in specific areas.

[0055] Step 8:

[0056] The server generates and delivers periodic evaluation tests to the terminal. Users take these tests and set their next learning goals based on the results. Based on the test results, the server provides the user with feedback and suggestions for improvement.

[0057] Step 9:

[0058] Users receive feedback and prepare for the next learning cycle. The server creates updated educational plans and continuously optimizes the learning process.

[0059] (Example 1)

[0060] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0061] Traditional education systems struggle to provide personalized education for individual learners, and uniform curricula lead to decreased learning efficiency. Furthermore, they fail to adequately address the needs of diverse learners with varying educational goals due to insufficient adjustment of dynamic educational plans and the cultivation of cultural knowledge. Additionally, they lack means to quickly resolve user questions that arise during learning.

[0062] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0063] In this invention, the server includes means for generating an educational plan that conforms to learning objectives based on individual information, means for presenting learning data according to the generated educational plan, means for recording the user's learning progress and transmitting it to a database for analysis, means for dynamically adjusting the educational plan based on the analysis results, and means for generating variable educational content based on instructional statements using a generation AI. This makes it possible to provide users with efficient and personalized educational plans.

[0064] "Individual information" refers to personalized information about each learner, such as the user's age, grade level, and educational goals.

[0065] An "educational plan" refers to learning content and curriculum optimized based on individual information.

[0066] "Learning data" refers to educational materials such as videos, texts, and workbooks provided based on the educational plan.

[0067] "Learning progress" refers to information that shows the progress of educational activities, such as assignments completed by the user and test results.

[0068] A "database" is a system for collecting and managing recorded information on learning progress and educational plans.

[0069] "Analysis results" refer to the evaluation results of the user's level of understanding and the educational plan obtained by analyzing learning progress data.

[0070] "Dynamic adjustment" refers to the process of modifying and updating the educational plan as needed based on the analysis results.

[0071] "Generative AI" is a technology that uses artificial intelligence to create new educational content from instructions and prompts.

[0072] An "instruction statement" is a text-based command given to a generation AI to generate specific educational content.

[0073] This invention implements an educational system in which three elements—a server, a terminal, and a user—operate together as a single unit.

[0074] The server receives individual information registered by users, compares it with the Japanese compulsory education curriculum database, and automatically generates an educational plan that conforms to the learning objectives. Based on this plan, the server provides learning data such as videos, texts, and workbooks optimized for each user. Specifically, a generation AI model is used as the software, and customized learning materials are created by inputting prompts.

[0075] The terminal displays learning data retrieved from the server to the user. As the user learns, their progress is automatically recorded and sent to the server. This allows the learning progress to be updated in real time, and the server uses this data to analyze the progress.

[0076] To address user questions during their learning process, the system includes a real-time question-answering function. When a user enters a question via their device, the server uses AI generation to quickly generate an answer, supporting the user's learning.

[0077] Furthermore, the server promotes a deeper understanding of Japanese culture among users through interactive cultural content. This includes quizzes and explanations on traditional events, historical background, and cultural knowledge, providing a multicultural educational experience.

[0078] For example, when learning new kanji characters, the device visually displays how to write them and provides examples of pronunciation and usage to aid user understanding. Examples of prompts to input into the generation AI model include, "Generate a quiz about Japanese history for 5th graders," and "Provide content that shows how to learn new kanji characters for 2nd year middle school students." In this way, it is possible to provide users with a flexible and effective educational experience.

[0079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0080] Step 1: Generating an Educational Plan

[0081] The server receives individual information entered by the user (age, grade level, educational goals, etc.). Based on this input, it accesses the Japanese compulsory education curriculum database and generates an educational plan optimized for the user. In this process, the curriculum is dynamically selected according to age and learning level, and an educational plan is generated as output with individual educational goals set.

[0082] Step 2: Presentation of training data

[0083] Based on the educational plan, the server selects appropriate learning data (video materials, text materials, workbooks, etc.) and sends it to the terminal. The terminal receives this data and displays it on the screen when the user begins learning. At this stage, the learning content is provided as output data from the server and is visually displayed to the user by the terminal.

[0084] Step 3: Record and submit your learning progress

[0085] The device automatically records the user's learning activities (such as completed assignments and test results). This data is sent to the server as a progress log. The server receives and aggregates the progress logs and creates output data that centrally manages the user's learning progress.

[0086] Step 4: Analysis of progress data

[0087] The server analyzes the received progress data to evaluate the user's understanding and learning speed. This involves using data analysis techniques to calculate the user's accuracy rate and problem-solving time, and outputting analysis results that evaluate learning efficiency.

[0088] Step 5: Adjusting the Education Plan

[0089] Based on the analysis results, the server dynamically adjusts the educational plan. Here, it uses a generation AI model to create additional teaching materials for areas where understanding is lacking, and updates the educational plan as output, providing new educational resources.

[0090] Step 6: Real-time question answering

[0091] If a user encounters a question during their learning process, they input the question through their device. The server analyzes the question using a generative AI model and generates an appropriate answer. This answer is then immediately provided to the user, supporting their learning.

[0092] Step 7: Providing Cultural Content

[0093] The server generates and delivers interactive content about Japanese culture to the user's device. The user then uses this content to deepen their knowledge of the culture. In this process, the server selects and generates cultural content, and as output, provides an interactive learning experience through the device.

[0094] (Application Example 1)

[0095] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0096] In today's educational environment, there is a demand for personalized learning experiences tailored to individual learners. However, traditional educational systems struggle to provide appropriate educational plans and content in real time while considering individual learning progress and comprehension levels. Furthermore, interactive educational methods for deepening understanding of Japanese culture are limited. In addition, there is a lack of effective means to resolve learners' questions on the spot.

[0097] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0098] In this invention, the server includes a device for generating educational plans based on a child's learning objectives, a mechanism for presenting educational materials delivered according to the individual educational plan, means for recording and analyzing the user's learning progress, and a robotic device for presenting educational content using sound and visuals. This enables the provision of personalized learning plans, real-time question answering, and effective learning of Japanese culture.

[0099] A "device for generating educational plans based on children's learning objectives" is a system for formulating individualized educational strategies tailored to the learner's age, interests, and level of understanding.

[0100] A "mechanism for providing educational materials delivered according to individual educational plans" is a system for providing learners with teaching materials and learning content that are compatible with their educational plans.

[0101] "Means for recording and analyzing users' learning progress" refers to methods for recording how far learners have progressed in their studies and analyzing their progress based on that data.

[0102] A "robot device that presents educational content using sound and visuals" is a robot-type device that provides educational content to learners by utilizing sound and video technology.

[0103] A "real-time prompt for generating answers to questions" refers to an input instruction in an algorithm or system that immediately generates a response to a learner's question.

[0104] "Learning materials related to Japanese culture" refers to educational content about Japanese traditions, customs, and history.

[0105] To implement this invention, it is necessary to build a system in which a server, a terminal, and a user work together in cooperation. First, the server receives individual information of the learner as input and generates an educational plan optimized for the learner's learning objectives based on that information. This plan reflects the learner's age, grade level, and specific learning objectives.

[0106] The device displays relevant educational content to learners according to this educational plan. This content includes videos, text, and interactive cultural learning materials, designed to effectively support learning. The device continuously records progress and test results, sending them to the server. Based on this information, the server analyzes it, adjusts the educational plan as needed, and suggests appropriate educational content tailored to the learner's progress.

[0107] In addition, the device is equipped with robotic functions that can be operated by gestures and voice, presenting educational content through an interactive and visual experience. Specifically, it provides audio and visual presentation functions, for example, by offering explanations accompanied by actual movements when teaching how to write or pronounce kanji characters.

[0108] If a user has a question, they can input it through their device. The server uses a generative AI model to answer the question in real time, helping learners deepen their understanding on the spot. For example, it can instantly answer questions like, "How do you pronounce the kanji for 'mikan' (orange)?"

[0109] This invention is built using embedded AI platforms such as NVIDIA's Jetson series and utilizes prompts from a generative AI model to generate effective answers to questions. An example of a prompt is, "Generate a kanji learning plan for a second-grade elementary school student. Next, suggest adjusting the learning content based on the following levels of understanding." In this way, the entire system works together to realize a personalized educational experience.

[0110] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0111] Step 1:

[0112] The server receives individualized information from the user, such as age, grade level, and learning objectives. Using this information as input, it generates a personalized learning plan for the learner. The generated plan includes an individualized learning strategy, such as which subjects should be studied in focus. This plan is then sent to the terminal.

[0113] Step 2:

[0114] The device prepares appropriate educational content based on the educational plan sent from the server. Video materials, text materials, and interactive cultural materials are selected and displayed. Specifically, the device projects visual content onto a screen using a projector and provides audio commentary through a speaker. This process is adjusted according to the user's progress.

[0115] Step 3:

[0116] When a user completes each learning session, the device records test results and progress data. This data is collected and sent to a server. The server analyzes the received data to identify areas of learning comprehension and areas where there are challenges. Based on this analysis, the educational plan is automatically adjusted. For example, areas where understanding is weak will have additional content added to reinforce them.

[0117] Step 4:

[0118] When a user has a question, they input it via their device. The server uses a generative AI model to generate a prompt related to this question and prepare an appropriate answer. An immediate answer to the question is generated and presented to the user via their device. This process is designed to resolve any questions the user may have during the learning process and deepen their understanding. By utilizing the "generative AI model," specific questions such as "How do you pronounce the kanji for 'mikan'?" can be answered in both voice and text.

[0119] Step 5:

[0120] The server delivers interactive Japanese cultural content to the terminal. The terminal uses robotic functions to display this content and provides explanations through voice and movement. For example, the terminal can interactively manipulate visual learning materials with audio guides in response to user reactions. This makes learning more effective and engaging.

[0121] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0122] This invention is a system for providing users with a personalized learning experience, aiming to further enhance the quality of learning by incorporating an emotion engine. In addition to generating educational plans, presenting learning content, recording and analyzing progress, and adjusting plans, this system recognizes the user's emotions and utilizes that information to optimize learning.

[0123] The server's initial role is to generate an educational plan based on the user's learning goals and current progress. This plan is rooted in the requirements of Japanese compulsory education and tailored to individual learning needs. The server then schedules learning content according to this plan and delivers it to the user via the terminal.

[0124] The device presents content received from the server to the user. This includes not only video learning materials, exercises, and quizzes, but also the hardware necessary for the emotion engine to recognize emotions from the user's speech and facial expressions.

[0125] This emotion engine analyzes subtle emotional changes in the user in real time during daily learning sessions and sends feedback to the server. The server analyzes this emotional data to evaluate the user's learning quality and motivation, and flexibly adjusts the learning content and how it is presented accordingly. For example, if the user is showing signs of stress or confusion, the server can present easier problems or add content that promotes relaxation.

[0126] Furthermore, the server facilitates effective learning by further tailoring the educational plan based on the progress and sentiment data it analyzes. When a user experiences a moderate sense of accomplishment or positive emotions, the server suggests challenging and amplified learning content to maintain motivation.

[0127] For example, if a user is frustrated because they cannot write kanji correctly, the emotion engine will sense this, and the server will immediately provide feedback. The device will then help the user maintain a positive learning experience by suggesting increasing practice time or switching to easier steps. In this way, the present invention achieves more intuitive and personalized learning by using an emotion engine.

[0128] The following describes the processing flow.

[0129] Step 1:

[0130] Users register with the system using their device and input information such as their child's age, learning goals, and areas of interest. Based on this information, users set learning priorities.

[0131] Step 2:

[0132] Based on the user information received by the server, an individualized educational plan is generated. The plan is customized to maximize the learner's progress and includes content that conforms to Japanese educational requirements.

[0133] Step 3:

[0134] Based on the educational plan generated by the server, learning content is compiled and delivered to the devices. This content includes text materials, videos, and interactive assignments.

[0135] Step 4:

[0136] The device uses sensors to capture the user's voice and facial expressions during training, enabling real-time emotion recognition by an emotion engine.

[0137] Step 5:

[0138] The emotion engine analyzes the user's emotions, identifying stress, confusion, and changes in motivation. This data is immediately sent to the server.

[0139] Step 6:

[0140] The server integrates emotional data and learning progress to adjust content according to the user's emotional state. For example, if the user is feeling stressed, it will present content with a lower difficulty level.

[0141] Step 7:

[0142] The server delivers emotional data-based feedback and support content aimed at improving motivation to the device.

[0143] Step 8:

[0144] The device presents new content to the user, allowing the user to continue learning. The user can progress through the learning process with support from the system.

[0145] Step 9:

[0146] The server periodically evaluates collected learning and sentiment data to generate updated educational plans that further refine long-term educational strategies. This cycle is repeated, providing users with an optimized learning experience.

[0147] (Example 2)

[0148] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0149] Existing learning systems tend to focus solely on knowledge transfer without considering the emotional state of individual learners. This leads to challenges such as difficulty maintaining motivation and decreased learning efficiency. Furthermore, there is insufficient provision of content optimized for cultural backgrounds and learning objectives.

[0150] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0151] In this invention, the server includes means for generating an educational plan based on the learner's goals, means for presenting learning content that conforms to the unit's educational plan, means for recording and analyzing the user's learning progress, and means for analyzing emotional information and adaptively adjusting the learning content based on the analysis results. This makes it possible to provide flexible learning plans that are tailored to the individual learner's emotions and progress.

[0152] "Learner's goals" refer to the specific skills and knowledge acquisition targets that users aim to achieve.

[0153] An "educational plan" refers to educational guidelines and schedules that are constructed based on learners' goals and progress.

[0154] "Learning content" refers to the teaching materials and assignments provided to learners based on the educational plan.

[0155] "User learning progress" refers to an evaluation criterion that shows how much content a learner has learned according to the educational plan.

[0156] "Emotional information" refers to data that indicates the emotions and psychological states expressed by learners during the learning process.

[0157] "Analysis" refers to the process of analyzing collected data and information to derive meaning and trends.

[0158] "Adaptive adjustment" refers to the act of flexibly changing learning plans and content in response to the results of analysis.

[0159] This invention is a system for providing learners with a personalized learning experience. This system is realized by coordinating a server, a terminal, and an emotion engine.

[0160] The server uses AI algorithms to generate individualized learning plans, taking into account the learner's goals and progress. These plans are optimized to meet the learner's specific learning needs and comply with Japanese compulsory education standards. Based on these plans, the server schedules and delivers the necessary learning content to the user's device. This process utilizes a database system capable of handling large amounts of data and optimized network protocols.

[0161] The terminal provides an interface for presenting learning content received from the server to the learner. It can present content in various formats, such as video materials and quizzes. Furthermore, the terminal incorporates an emotion engine and is equipped with hardware for real-time monitoring of the learner's emotional state using speech and facial recognition technologies. This includes a webcam and a high-sensitivity microphone.

[0162] The emotion engine analyzes the learner's voice tone and facial expressions, and feeds the resulting emotional information back to the server. The server analyzes this feedback and assesses whether the learner is stressed or relaxed. Based on this, the server adaptively adjusts the content to enable the learner to continue learning in a more effective way.

[0163] For example, if a learner becomes frustrated while practicing difficult kanji characters, the emotion engine detects this. The server immediately receives this information and sends new instructions to the learner. The device then presents the learner with options to increase practice time or switch to easier practice problems.

[0164] An example of a prompt for a generative AI model is, "If the emotion engine detects that the user is experiencing stress, what kind of learning content should be provided?" Based on this prompt, the AI ​​model generates the most suitable content.

[0165] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0166] Step 1:

[0167] The server retrieves the user's learning goals and past learning records from a database. Based on this data, it uses an AI algorithm to generate an individualized learning plan. Specifically, it analyzes the learning content necessary to achieve the goals and constructs step-by-step learning steps. It receives the user's learning history and set goals as input and generates an individually optimized learning plan as output.

[0168] Step 2:

[0169] The server schedules the necessary learning content based on the generated educational plan. It creates a list of content for each learning point and determines the appropriate timing to present them to the user. It receives educational plan data as input and generates a list of scheduled content as output. Specifically, it determines which content to present and in what order, and prepares it for delivery to the terminal.

[0170] Step 3:

[0171] The terminal presents learning content received from the server to the user. This content includes videos, learning materials, quizzes, and more. The terminal's interface allows users to easily access this content. It receives content data from the server as input and presents visual and auditory information to the user as output.

[0172] Step 4:

[0173] The device uses a built-in emotion engine to monitor the user's emotional state in real time. It uses microphones and cameras to sense and analyze the user's voice and facial expressions. It takes user audio and video data as input and obtains the results of the emotion analysis as output. Specifically, it determines whether the user is feeling frustrated or anxious.

[0174] Step 5:

[0175] The server analyzes the sentiment analysis results sent from the terminal and makes adjustments to enhance learning effectiveness. It changes the difficulty level of content or adds new content as needed. It receives sentiment analysis data as input and generates adjusted educational plans and content as output. For example, if a user is experiencing stress, it might add relaxation-promoting materials.

[0176] Step 6:

[0177] The server monitors overall learning progress and periodically updates the educational plan. This process uses comprehensive data analysis that combines user progress records and sentiment data. Learning progress data and sentiment status are taken as input, and an updated educational plan is generated as output. This ensures that the learning experience is always optimized for the user.

[0178] (Application Example 2)

[0179] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0180] Traditional educational support systems have struggled to fully understand the emotions and motivations of each learner and provide appropriate content and feedback in real time, resulting in a decline in the quality of learning. Furthermore, it has been difficult to reduce the stress and frustration children experience during learning and to provide a positive learning experience.

[0181] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0182] In this invention, the server includes means for generating a learning plan tailored to a child's educational goals, means for presenting educational materials provided based on the individual learning plan, means for recording and evaluating the user's learning progress, means for adjusting the learning plan based on the evaluation results, and means for recognizing emotional information and adjusting the learning content based on said information. This enables the provision of appropriate educational content tailored to the learner's emotions, resulting in a personalized learning experience.

[0183] "Children" refers to young people who are eligible to receive learning support.

[0184] "Educational objectives" refer to the specific standards of knowledge and skills that learners are expected to achieve.

[0185] A "learning plan" refers to a schedule or curriculum that is systematically designed to achieve educational goals.

[0186] "Means" refers to the methods or devices employed to achieve a specific objective.

[0187] "Educational materials" refer to teaching materials and reference materials provided to learners.

[0188] "To present" refers to delivering information or content to learners visually or aurally.

[0189] "Progress" refers to the process or stage of results toward achieving a specific goal.

[0190] "Evaluation" refers to judging progress and results based on specific criteria.

[0191] "To adjust" refers to changing settings or plans to an optimal state depending on the situation and needs.

[0192] "Emotional information" refers to data and signals that indicate a learner's emotions and psychological state.

[0193] "Adjusting" refers to changing the services or functions provided according to the user's condition and needs.

[0194] The system for realizing this application implements each function with the server, terminal, and user as the main subjects. The server generates a learning plan based on the child's educational goals. This includes creating an appropriate curriculum that reflects the user's current learning progress and emotional state. The server also sends learning materials and content to the terminal in accordance with the generated learning plan.

[0195] The terminal displays content received from the server to the user and monitors the user's facial expressions and voice in real time using hardware such as cameras and microphones. This data is processed by an emotion recognition engine to determine the user's emotional state. The software used includes an emotion recognition algorithm and an AI for generating educational plans.

[0196] Specifically, if a user's facial expression indicates dissatisfaction while working through the learning materials, the server can use that information to switch to easier problems or suggest taking a break during the learning process. Furthermore, if the server detects that the user is calm, it can encourage them to tackle slightly more difficult problems.

[0197] For example, if a user is having difficulty writing kanji characters, the system's emotion engine will detect this, and the server will generate a flexible response based on the user's learning progress. An example of a prompt might be, "Analyze the emotions the child is feeling based on facial expression and voice data, and adjust the learning program accordingly."

[0198] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0199] Step 1:

[0200] The server receives the user's educational goals and current learning progress as input and generates a learning plan. The program analyzes this data and selects the necessary educational content. The output is a curriculum tailored to the user. Specifically, this involves referencing a database of past learning history and applying an educational AI model.

[0201] Step 2:

[0202] The server selects the necessary learning content based on the generated learning plan and sends it to the terminal. The output is the learning materials and information displayed to the user. In this step, videos, quizzes, practice questions, etc., are selected according to the user's progress level.

[0203] Step 3:

[0204] The terminal presents learning content received from the server to the user. The input is educational materials sent from the server. The output is the learning material content displayed on the user's screen. In addition to display, interactive materials accept user responses.

[0205] Step 4:

[0206] The device uses its built-in camera and microphone to collect emotional information as input, capturing the user's facial expressions and voice data in real time. The output is processed emotional data. The collected data is analyzed by an emotion recognition algorithm to determine the user's emotional state.

[0207] Step 5:

[0208] The server adjusts existing learning plans and content based on sentiment information received from the terminal. The input is analyzed sentiment data, and the output is the adjusted learning plan and content. Specifically, if dissatisfaction is detected, actions such as lowering the difficulty level are taken.

[0209] Step 6:

[0210] The user continues learning based on the new learning content and suggestions presented on the device. The output is the user's progress data. This data is fed back as input to step 1, continuously optimizing the system's operation.

[0211] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0212] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0213] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0214] [Second Embodiment]

[0215] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0216] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0217] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0218] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0219] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0220] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0221] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0222] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0223] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0224] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0225] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0226] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0227] The system of the present invention provides users with a personalized learning experience, enabling the generation of educational plans, presentation of learning content, recording and analysis of progress, adjustment of plans, real-time question answering, and delivery of interactive cultural content. This allows users to efficiently acquire Japanese compulsory education and culture.

[0228] The server's first step is to generate an educational plan based on the individual information provided by the user. The server considers the child's age, grade level, and educational goals, and creates a curriculum that conforms to the Japanese compulsory education curriculum guidelines. This ensures that the content is best suited to the learner.

[0229] When a user begins their daily learning activities through their device, the device displays learning content provided by the server. This includes video materials, text materials, and workbooks, each organized according to the educational plan.

[0230] Progress tracking is extremely important. The terminal continuously records completed tasks and test results and sends them to the server. The server collects this data and analyzes the user's understanding and progress. Based on the analysis, the server adjusts the educational plan and provides additional materials tailored to the user's progress and areas of weakness.

[0231] When a user has a question, they can input it in real time through their device. The server's AI receives the question and provides an immediate answer. This allows learners to resolve their questions quickly.

[0232] Furthermore, as part of cultural learning, the server delivers interactive content to the terminals. This includes lectures on traditional Japanese events and the formation of history, as well as quizzes about cultural customs. Through this, users can deepen their understanding of Japanese culture.

[0233] Through the process described above, this system provides users with a comprehensive and personalized educational experience, efficiently meeting Japanese educational requirements while accommodating learning in a multicultural environment. For example, when learning new kanji characters, the device visually displays how to write them and provides examples of their usage, including pronunciation, to aid user understanding. This allows learners to improve their Japanese language skills in an enjoyable and effective way.

[0234] The following describes the processing flow.

[0235] Step 1:

[0236] Users register with the system using their device and enter information such as their child's age, grade level, and learning goals. Users also select the goals they wish to achieve in their current area of ​​education.

[0237] Step 2:

[0238] Based on the information received from the user, the server generates an initial educational plan. Following the Japanese compulsory education curriculum guidelines, the server designs a curriculum for subjects such as Japanese language, mathematics, social studies, and science that is tailored to the participants' needs.

[0239] Step 3:

[0240] Based on the educational plan generated by the server, daily learning content is designed and delivered to the devices. This content includes video materials, texts, quizzes, and practical exercises.

[0241] Step 4:

[0242] Users access content through their devices and progress through their learning. Users reinforce their knowledge by watching learning materials and solving assignments. If questions arise, users can use the question function on their devices to make inquiries.

[0243] Step 5:

[0244] The generating AI receives questions from users and provides immediate answers. The server presents relevant additional materials to support the user's understanding.

[0245] Step 6:

[0246] The device records the user's learning progress. This progress includes the number of completed assignments, test results, and teacher evaluations. This data is sent to the server as a learning history.

[0247] Step 7:

[0248] The server analyzes progress data to identify areas where the user is struggling. Based on the analysis results, the educational plan is adjusted, and content is redesigned to strengthen remedial instruction in specific areas.

[0249] Step 8:

[0250] The server generates and delivers periodic evaluation tests to the terminal. Users take these tests and set their next learning goals based on the results. Based on the test results, the server provides the user with feedback and suggestions for improvement.

[0251] Step 9:

[0252] Users receive feedback and prepare for the next learning cycle. The server creates updated educational plans and continuously optimizes the learning process.

[0253] (Example 1)

[0254] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0255] Traditional education systems struggle to provide personalized education for individual learners, and uniform curricula lead to decreased learning efficiency. Furthermore, they fail to adequately address the needs of diverse learners with varying educational goals due to insufficient adjustment of dynamic educational plans and the cultivation of cultural knowledge. Additionally, they lack means to quickly resolve user questions that arise during learning.

[0256] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0257] In this invention, the server includes means for generating an educational plan that conforms to learning objectives based on individual information, means for presenting learning data according to the generated educational plan, means for recording the user's learning progress and transmitting it to a database for analysis, means for dynamically adjusting the educational plan based on the analysis results, and means for generating variable educational content based on instructional statements using a generation AI. This makes it possible to provide users with efficient and personalized educational plans.

[0258] "Individual information" refers to personalized information about each learner, such as the user's age, grade level, and educational goals.

[0259] An "educational plan" refers to learning content and curriculum optimized based on individual information.

[0260] "Learning data" refers to educational materials such as videos, texts, and workbooks provided based on the educational plan.

[0261] "Learning progress" refers to information that shows the progress of educational activities, such as assignments completed by the user and test results.

[0262] A "database" is a system for collecting and managing recorded information on learning progress and educational plans.

[0263] "Analysis results" refer to the evaluation results of the user's level of understanding and the educational plan obtained by analyzing learning progress data.

[0264] "Dynamic adjustment" refers to the process of modifying and updating the educational plan as needed based on the analysis results.

[0265] "Generative AI" is a technology that uses artificial intelligence to create new educational content from instructions and prompts.

[0266] An "instruction statement" is a text-based command given to a generation AI to generate specific educational content.

[0267] This invention implements an educational system in which three elements—a server, a terminal, and a user—operate together as a single unit.

[0268] The server receives individual information registered by users, compares it with the Japanese compulsory education curriculum database, and automatically generates an educational plan that conforms to the learning objectives. Based on this plan, the server provides learning data such as videos, texts, and workbooks optimized for each user. Specifically, a generation AI model is used as the software, and customized learning materials are created by inputting prompts.

[0269] The terminal displays learning data retrieved from the server to the user. As the user learns, their progress is automatically recorded and sent to the server. This allows the learning progress to be updated in real time, and the server uses this data to analyze the progress.

[0270] To address user questions during their learning process, the system includes a real-time question-answering function. When a user enters a question via their device, the server uses AI generation to quickly generate an answer, supporting the user's learning.

[0271] Furthermore, the server promotes a deeper understanding of Japanese culture among users through interactive cultural content. This includes quizzes and explanations on traditional events, historical background, and cultural knowledge, providing a multicultural educational experience.

[0272] For example, when learning new kanji characters, the device visually displays how to write them and provides examples of pronunciation and usage to aid user understanding. Examples of prompts to input into the generation AI model include, "Generate a quiz about Japanese history for 5th graders," and "Provide content that shows how to learn new kanji characters for 2nd year middle school students." In this way, it is possible to provide users with a flexible and effective educational experience.

[0273] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0274] Step 1: Generating an Educational Plan

[0275] The server receives individual information entered by the user (age, grade level, educational goals, etc.). Based on this input, it accesses the Japanese compulsory education curriculum database and generates an educational plan optimized for the user. In this process, the curriculum is dynamically selected according to age and learning level, and an educational plan is generated as output with individual educational goals set.

[0276] Step 2: Presentation of training data

[0277] Based on the educational plan, the server selects appropriate learning data (video materials, text materials, workbooks, etc.) and sends it to the terminal. The terminal receives this data and displays it on the screen when the user begins learning. At this stage, the learning content is provided as output data from the server and is visually displayed to the user by the terminal.

[0278] Step 3: Record and submit your learning progress

[0279] The device automatically records the user's learning activities (such as completed assignments and test results). This data is sent to the server as a progress log. The server receives and aggregates the progress logs and creates output data that centrally manages the user's learning progress.

[0280] Step 4: Analysis of progress data

[0281] The server analyzes the received progress data to evaluate the user's understanding and learning speed. This involves using data analysis techniques to calculate the user's accuracy rate and problem-solving time, and outputting analysis results that evaluate learning efficiency.

[0282] Step 5: Adjusting the Education Plan

[0283] Based on the analysis results, the server dynamically adjusts the education plan. Here, additional teaching materials are created for areas where there is a lack of understanding using a generative AI model, and the education plan is updated as an output to provide new educational resources.

[0284] Step 6: Real-time question and answer

[0285] When the user has doubts during learning, the user inputs a question through the terminal. The server analyzes the question using a generative AI model and generates an appropriate answer. This answer is immediately provided to the user as an output to support the user's learning.

[0286] Step 7: Provision of cultural content

[0287] The server generates interactive content related to Japanese culture and distributes it to the terminal. The user uses this to deepen their knowledge of culture. In this process, the server selects and generates cultural content, and provides an interactive learning experience as an output through the terminal.

[0288] (Application Example 1)

[0289] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0290] In the modern educational environment, there is a demand to provide a personalized learning experience tailored to individual learners. However, in conventional educational systems, it is difficult to provide an appropriate educational plan and content in real time while considering the individual learning progress and understanding level. Also, there are limited interactive educational methods for deepening understanding of Japanese culture. Furthermore, there is a problem of a lack of effective means for solving learners' doubts immediately.

[0291] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0292] In this invention, the server includes a device for generating educational plans based on a child's learning objectives, a mechanism for presenting educational materials delivered according to the individual educational plan, means for recording and analyzing the user's learning progress, and a robotic device for presenting educational content using sound and visuals. This enables the provision of personalized learning plans, real-time question answering, and effective learning of Japanese culture.

[0293] A "device for generating educational plans based on children's learning objectives" is a system for formulating individualized educational strategies tailored to the learner's age, interests, and level of understanding.

[0294] A "mechanism for providing educational materials delivered according to individual educational plans" is a system for providing learners with teaching materials and learning content that are compatible with their educational plans.

[0295] "Means for recording and analyzing users' learning progress" refers to methods for recording how far learners have progressed in their studies and analyzing their progress based on that data.

[0296] A "robot device that presents educational content using sound and visuals" is a robot-type device that provides educational content to learners by utilizing sound and video technology.

[0297] A "real-time prompt for generating answers to questions" refers to an input instruction in an algorithm or system that immediately generates a response to a learner's question.

[0298] "Learning materials related to Japanese culture" refers to educational content about Japanese traditions, customs, and history.

[0299] To implement this invention, it is necessary to build a system in which a server, a terminal, and a user work together in cooperation. First, the server receives individual information of the learner as input and generates an educational plan optimized for the learner's learning objectives based on that information. This plan reflects the learner's age, grade level, and specific learning objectives.

[0300] The device displays relevant educational content to learners according to this educational plan. This content includes videos, text, and interactive cultural learning materials, designed to effectively support learning. The device continuously records progress and test results, sending them to the server. Based on this information, the server analyzes it, adjusts the educational plan as needed, and suggests appropriate educational content tailored to the learner's progress.

[0301] In addition, the device is equipped with robotic functions that can be operated by gestures and voice, presenting educational content through an interactive and visual experience. Specifically, it provides audio and visual presentation functions, for example, by offering explanations accompanied by actual movements when teaching how to write or pronounce kanji characters.

[0302] If a user has a question, they can input it through their device. The server uses a generative AI model to answer the question in real time, helping learners deepen their understanding on the spot. For example, it can instantly answer questions like, "How do you pronounce the kanji for 'mikan' (orange)?"

[0303] This invention is built using embedded AI platforms such as NVIDIA's Jetson series and utilizes prompts from a generative AI model to generate effective answers to questions. An example of a prompt is, "Generate a kanji learning plan for a second-grade elementary school student. Next, suggest adjusting the learning content based on the following levels of understanding." In this way, the entire system works together to realize a personalized educational experience.

[0304] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0305] Step 1:

[0306] The server receives individual information such as the age, school year, and learning goals provided by the user. Using this information as input data, it generates an educational plan dedicated to the learner. The generated educational plan includes individualized learning strategies such as which subjects should be focused on. This plan is sent to the terminal.

[0307] Step 2:

[0308] Based on the educational plan sent from the server, the terminal prepares appropriate educational content. Video teaching materials, text materials, and interactive cultural materials are selected and displayed. As a specific operation, the terminal projects visual content onto the screen using a projector and provides audio explanations through a speaker. This process is adjusted according to the user's progress.

[0309] Step 3:

[0310] When the user completes each learning session, the terminal records the test results and progress data. This data is collected and sent to the server. The server analyzes the received data and identifies the areas of learning comprehension and problems. Based on this analysis result, the educational plan is automatically adjusted. For example, content for intensively reinforcing the areas with low comprehension is added.

[0311] Step 4:

[0312] When a user has a question, they input it via their device. The server uses a generative AI model to generate a prompt related to this question and prepare an appropriate answer. An immediate answer to the question is generated and presented to the user via their device. This process is designed to resolve any questions the user may have during the learning process and deepen their understanding. By utilizing the "generative AI model," specific questions such as "How do you pronounce the kanji for 'mikan'?" can be answered in both voice and text.

[0313] Step 5:

[0314] The server delivers interactive Japanese cultural content to the terminal. The terminal uses robotic functions to display this content and provides explanations through voice and movement. For example, the terminal can interactively manipulate visual learning materials with audio guides in response to user reactions. This makes learning more effective and engaging.

[0315] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0316] This invention is a system for providing users with a personalized learning experience, aiming to further enhance the quality of learning by incorporating an emotion engine. In addition to generating educational plans, presenting learning content, recording and analyzing progress, and adjusting plans, this system recognizes the user's emotions and utilizes that information to optimize learning.

[0317] The server's initial role is to generate an educational plan based on the user's learning goals and current progress. This plan is rooted in the requirements of Japanese compulsory education and tailored to individual learning needs. The server then schedules learning content according to this plan and delivers it to the user via the terminal.

[0318] The device presents content received from the server to the user. This includes not only video learning materials, exercises, and quizzes, but also the hardware necessary for the emotion engine to recognize emotions from the user's speech and facial expressions.

[0319] This emotion engine analyzes subtle emotional changes in the user in real time during daily learning sessions and sends feedback to the server. The server analyzes this emotional data to evaluate the user's learning quality and motivation, and flexibly adjusts the learning content and how it is presented accordingly. For example, if the user is showing signs of stress or confusion, the server can present easier problems or add content that promotes relaxation.

[0320] Furthermore, the server facilitates effective learning by further tailoring the educational plan based on the progress and sentiment data it analyzes. When a user experiences a moderate sense of accomplishment or positive emotions, the server suggests challenging and amplified learning content to maintain motivation.

[0321] For example, if a user is frustrated because they cannot write kanji correctly, the emotion engine will sense this, and the server will immediately provide feedback. The device will then help the user maintain a positive learning experience by suggesting increasing practice time or switching to easier steps. In this way, the present invention achieves more intuitive and personalized learning by using an emotion engine.

[0322] The following describes the processing flow.

[0323] Step 1:

[0324] Users register with the system using their device and input information such as their child's age, learning goals, and areas of interest. Based on this information, users set learning priorities.

[0325] Step 2:

[0326] Based on the user information received by the server, an individualized educational plan is generated. The plan is customized to maximize the learner's progress and includes content that conforms to Japanese educational requirements.

[0327] Step 3:

[0328] Based on the educational plan generated by the server, learning content is compiled and delivered to the devices. This content includes text materials, videos, and interactive assignments.

[0329] Step 4:

[0330] The device uses sensors to capture the user's voice and facial expressions during training, enabling real-time emotion recognition by an emotion engine.

[0331] Step 5:

[0332] The emotion engine analyzes the user's emotions, identifying stress, confusion, and changes in motivation. This data is immediately sent to the server.

[0333] Step 6:

[0334] The server integrates emotional data and learning progress to adjust content according to the user's emotional state. For example, if the user is feeling stressed, it will present content with a lower difficulty level.

[0335] Step 7:

[0336] The server delivers emotional data-based feedback and support content aimed at improving motivation to the device.

[0337] Step 8:

[0338] The device presents new content to the user, allowing the user to continue learning. The user can progress through the learning process with support from the system.

[0339] Step 9:

[0340] The server periodically evaluates collected learning and sentiment data to generate updated educational plans that further refine long-term educational strategies. This cycle is repeated, providing users with an optimized learning experience.

[0341] (Example 2)

[0342] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0343] Existing learning systems tend to focus solely on knowledge transfer without considering the emotional state of individual learners. This leads to challenges such as difficulty maintaining motivation and decreased learning efficiency. Furthermore, there is insufficient provision of content optimized for cultural backgrounds and learning objectives.

[0344] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0345] In this invention, the server includes means for generating an educational plan based on the learner's goals, means for presenting learning content that conforms to the unit's educational plan, means for recording and analyzing the user's learning progress, and means for analyzing emotional information and adaptively adjusting the learning content based on the analysis results. This makes it possible to provide flexible learning plans that are tailored to the individual learner's emotions and progress.

[0346] "Learner's goals" refer to the specific skills and knowledge acquisition targets that users aim to achieve.

[0347] An "educational plan" refers to educational guidelines and schedules that are constructed based on learners' goals and progress.

[0348] "Learning content" refers to the teaching materials and assignments provided to learners based on the educational plan.

[0349] "User learning progress" refers to an evaluation criterion that shows how much content a learner has learned according to the educational plan.

[0350] "Emotional information" refers to data that indicates the emotions and psychological states expressed by learners during the learning process.

[0351] "Analysis" refers to the process of analyzing collected data and information to derive meaning and trends.

[0352] "Adaptive adjustment" refers to the act of flexibly changing learning plans and content in response to the results of analysis.

[0353] This invention is a system for providing learners with a personalized learning experience. This system is realized by coordinating a server, a terminal, and an emotion engine.

[0354] The server uses AI algorithms to generate individualized learning plans, taking into account the learner's goals and progress. These plans are optimized to meet the learner's specific learning needs and comply with Japanese compulsory education standards. Based on these plans, the server schedules and delivers the necessary learning content to the user's device. This process utilizes a database system capable of handling large amounts of data and optimized network protocols.

[0355] The terminal provides an interface for presenting learning content received from the server to the learner. It can present content in various formats, such as video materials and quizzes. Furthermore, the terminal incorporates an emotion engine and is equipped with hardware for real-time monitoring of the learner's emotional state using speech and facial recognition technologies. This includes a webcam and a high-sensitivity microphone.

[0356] The emotion engine analyzes the learner's voice tone and facial expressions, and feeds the resulting emotional information back to the server. The server analyzes this feedback and assesses whether the learner is stressed or relaxed. Based on this, the server adaptively adjusts the content to enable the learner to continue learning in a more effective way.

[0357] For example, if a learner becomes frustrated while practicing difficult kanji characters, the emotion engine detects this. The server immediately receives this information and sends new instructions to the learner. The device then presents the learner with options to increase practice time or switch to easier practice problems.

[0358] An example of a prompt for a generative AI model is, "If the emotion engine detects that the user is experiencing stress, what kind of learning content should be provided?" Based on this prompt, the AI ​​model generates the most suitable content.

[0359] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0360] Step 1:

[0361] The server retrieves the user's learning goals and past learning records from a database. Based on this data, it uses an AI algorithm to generate an individualized learning plan. Specifically, it analyzes the learning content necessary to achieve the goals and constructs step-by-step learning steps. It receives the user's learning history and set goals as input and generates an individually optimized learning plan as output.

[0362] Step 2:

[0363] The server schedules the necessary learning content based on the generated educational plan. It creates a list of content for each learning point and determines the appropriate timing to present them to the user. It receives educational plan data as input and generates a list of scheduled content as output. Specifically, it determines which content to present and in what order, and prepares it for delivery to the terminal.

[0364] Step 3:

[0365] The terminal presents learning content received from the server to the user. This content includes videos, learning materials, quizzes, and more. The terminal's interface allows users to easily access this content. It receives content data from the server as input and presents visual and auditory information to the user as output.

[0366] Step 4:

[0367] The device uses a built-in emotion engine to monitor the user's emotional state in real time. It uses microphones and cameras to sense and analyze the user's voice and facial expressions. It takes user audio and video data as input and obtains the results of the emotion analysis as output. Specifically, it determines whether the user is feeling frustrated or anxious.

[0368] Step 5:

[0369] The server analyzes the sentiment analysis results sent from the terminal and makes adjustments to enhance learning effectiveness. It changes the difficulty level of content or adds new content as needed. It receives sentiment analysis data as input and generates adjusted educational plans and content as output. For example, if a user is experiencing stress, it might add relaxation-promoting materials.

[0370] Step 6:

[0371] The server monitors overall learning progress and periodically updates the educational plan. This process uses comprehensive data analysis that combines user progress records and sentiment data. Learning progress data and sentiment status are taken as input, and an updated educational plan is generated as output. This ensures that the learning experience is always optimized for the user.

[0372] (Application Example 2)

[0373] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0374] Traditional educational support systems have struggled to fully understand the emotions and motivations of each learner and provide appropriate content and feedback in real time, resulting in a decline in the quality of learning. Furthermore, it has been difficult to reduce the stress and frustration children experience during learning and to provide a positive learning experience.

[0375] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0376] In this invention, the server includes means for generating a learning plan tailored to a child's educational goals, means for presenting educational materials provided based on the individual learning plan, means for recording and evaluating the user's learning progress, means for adjusting the learning plan based on the evaluation results, and means for recognizing emotional information and adjusting the learning content based on said information. This enables the provision of appropriate educational content tailored to the learner's emotions, resulting in a personalized learning experience.

[0377] "Children" refers to young people who are eligible to receive learning support.

[0378] "Educational objectives" refer to the specific standards of knowledge and skills that learners are expected to achieve.

[0379] A "learning plan" refers to a schedule or curriculum that is systematically designed to achieve educational goals.

[0380] "Means" refers to the methods or devices employed to achieve a specific objective.

[0381] "Educational materials" refer to teaching materials and reference materials provided to learners.

[0382] "To present" refers to delivering information or content to learners visually or aurally.

[0383] "Progress" refers to the process or stage of results toward achieving a specific goal.

[0384] "Evaluation" refers to judging progress and results based on specific criteria.

[0385] "To adjust" refers to changing settings or plans to an optimal state depending on the situation and needs.

[0386] "Emotional information" refers to data and signals that indicate a learner's emotions and psychological state.

[0387] "Adjusting" refers to changing the services or functions provided according to the user's condition and needs.

[0388] The system for realizing this application implements each function with the server, terminal, and user as the main subjects. The server generates a learning plan based on the child's educational goals. This includes creating an appropriate curriculum that reflects the user's current learning progress and emotional state. The server also sends learning materials and content to the terminal in accordance with the generated learning plan.

[0389] The terminal displays content received from the server to the user and monitors the user's facial expressions and voice in real time using hardware such as cameras and microphones. This data is processed by an emotion recognition engine to determine the user's emotional state. The software used includes an emotion recognition algorithm and an AI for generating educational plans.

[0390] Specifically, if a user's facial expression indicates dissatisfaction while working through the learning materials, the server can use that information to switch to easier problems or suggest taking a break during the learning process. Furthermore, if the server detects that the user is calm, it can encourage them to tackle slightly more difficult problems.

[0391] For example, if a user is having difficulty writing kanji characters, the system's emotion engine will detect this, and the server will generate a flexible response based on the user's learning progress. An example of a prompt might be, "Analyze the emotions the child is feeling based on facial expression and voice data, and adjust the learning program accordingly."

[0392] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0393] Step 1:

[0394] The server receives the user's educational goals and current learning progress as input and generates a learning plan. The program analyzes this data and selects the necessary educational content. The output is a curriculum tailored to the user. Specifically, this involves referencing a database of past learning history and applying an educational AI model.

[0395] Step 2:

[0396] The server selects the necessary learning content based on the generated learning plan and sends it to the terminal. The output is the learning materials and information displayed to the user. In this step, videos, quizzes, practice questions, etc., are selected according to the user's progress level.

[0397] Step 3:

[0398] The terminal presents learning content received from the server to the user. The input is educational materials sent from the server. The output is the learning material content displayed on the user's screen. In addition to display, interactive materials accept user responses.

[0399] Step 4:

[0400] The device uses its built-in camera and microphone to collect emotional information as input, capturing the user's facial expressions and voice data in real time. The output is processed emotional data. The collected data is analyzed by an emotion recognition algorithm to determine the user's emotional state.

[0401] Step 5:

[0402] The server adjusts existing learning plans and content based on sentiment information received from the terminal. The input is analyzed sentiment data, and the output is the adjusted learning plan and content. Specifically, if dissatisfaction is detected, actions such as lowering the difficulty level are taken.

[0403] Step 6:

[0404] The user continues learning based on the new learning content and suggestions presented on the device. The output is the user's progress data. This data is fed back as input to step 1, continuously optimizing the system's operation.

[0405] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0406] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0407] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0408] [Third Embodiment]

[0409] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0410] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0411] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0412] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0413] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0414] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0415] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0416] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0417] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0418] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0419] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0420] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0421] The system of the present invention provides users with a personalized learning experience, enabling the generation of educational plans, presentation of learning content, recording and analysis of progress, adjustment of plans, real-time question answering, and delivery of interactive cultural content. This allows users to efficiently acquire Japanese compulsory education and culture.

[0422] The server's first step is to generate an educational plan based on the individual information provided by the user. The server considers the child's age, grade level, and educational goals, and creates a curriculum that conforms to the Japanese compulsory education curriculum guidelines. This ensures that the content is best suited to the learner.

[0423] When a user begins their daily learning activities through their device, the device displays learning content provided by the server. This includes video materials, text materials, and workbooks, each organized according to the educational plan.

[0424] Progress tracking is extremely important. The terminal continuously records completed tasks and test results and sends them to the server. The server collects this data and analyzes the user's understanding and progress. Based on the analysis, the server adjusts the educational plan and provides additional materials tailored to the user's progress and areas of weakness.

[0425] When a user has a question, they can input it in real time through their device. The server's AI receives the question and provides an immediate answer. This allows learners to resolve their questions quickly.

[0426] Furthermore, as part of cultural learning, the server delivers interactive content to the terminals. This includes lectures on traditional Japanese events and the formation of history, as well as quizzes about cultural customs. Through this, users can deepen their understanding of Japanese culture.

[0427] Through the process described above, this system provides users with a comprehensive and personalized educational experience, efficiently meeting Japanese educational requirements while accommodating learning in a multicultural environment. For example, when learning new kanji characters, the device visually displays how to write them and provides examples of their usage, including pronunciation, to aid user understanding. This allows learners to improve their Japanese language skills in an enjoyable and effective way.

[0428] The following describes the processing flow.

[0429] Step 1:

[0430] Users register with the system using their device and enter information such as their child's age, grade level, and learning goals. Users also select the goals they wish to achieve in their current area of ​​education.

[0431] Step 2:

[0432] Based on the information received from the user, the server generates an initial educational plan. Following the Japanese compulsory education curriculum guidelines, the server designs a curriculum for subjects such as Japanese language, mathematics, social studies, and science that is tailored to the participants' needs.

[0433] Step 3:

[0434] Based on the educational plan generated by the server, daily learning content is designed and delivered to the devices. This content includes video materials, texts, quizzes, and practical exercises.

[0435] Step 4:

[0436] Users access content through their devices and progress through their learning. Users reinforce their knowledge by watching learning materials and solving assignments. If questions arise, users can use the question function on their devices to make inquiries.

[0437] Step 5:

[0438] The generating AI receives questions from users and provides immediate answers. The server presents relevant additional materials to support the user's understanding.

[0439] Step 6:

[0440] The device records the user's learning progress. This progress includes the number of completed assignments, test results, and teacher evaluations. This data is sent to the server as a learning history.

[0441] Step 7:

[0442] The server analyzes progress data to identify areas where the user is struggling. Based on the analysis results, the educational plan is adjusted, and content is redesigned to strengthen remedial instruction in specific areas.

[0443] Step 8:

[0444] The server generates and delivers periodic evaluation tests to the terminal. Users take these tests and set their next learning goals based on the results. Based on the test results, the server provides the user with feedback and suggestions for improvement.

[0445] Step 9:

[0446] Users receive feedback and prepare for the next learning cycle. The server creates updated educational plans and continuously optimizes the learning process.

[0447] (Example 1)

[0448] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0449] Traditional education systems struggle to provide personalized education for individual learners, and uniform curricula lead to decreased learning efficiency. Furthermore, they fail to adequately address the needs of diverse learners with varying educational goals due to insufficient adjustment of dynamic educational plans and the cultivation of cultural knowledge. Additionally, they lack means to quickly resolve user questions that arise during learning.

[0450] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0451] In this invention, the server includes means for generating an educational plan that conforms to learning objectives based on individual information, means for presenting learning data according to the generated educational plan, means for recording the user's learning progress and transmitting it to a database for analysis, means for dynamically adjusting the educational plan based on the analysis results, and means for generating variable educational content based on instructional statements using a generation AI. This makes it possible to provide users with efficient and personalized educational plans.

[0452] "Individual information" refers to personalized information about each learner, such as the user's age, grade level, and educational goals.

[0453] An "educational plan" refers to learning content and curriculum optimized based on individual information.

[0454] "Learning data" refers to educational materials such as videos, texts, and workbooks provided based on the educational plan.

[0455] "Learning progress" refers to information that shows the progress of educational activities, such as assignments completed by the user and test results.

[0456] A "database" is a system for collecting and managing recorded information on learning progress and educational plans.

[0457] "Analysis results" refer to the evaluation results of the user's level of understanding and the educational plan obtained by analyzing learning progress data.

[0458] "Dynamic adjustment" refers to the process of modifying and updating the educational plan as needed based on the analysis results.

[0459] "Generative AI" is a technology that uses artificial intelligence to create new educational content from instructions and prompts.

[0460] An "instruction statement" is a text-based command given to a generation AI to generate specific educational content.

[0461] This invention implements an educational system in which three elements—a server, a terminal, and a user—operate together as a single unit.

[0462] The server receives individual information registered by users, compares it with the Japanese compulsory education curriculum database, and automatically generates an educational plan that conforms to the learning objectives. Based on this plan, the server provides learning data such as videos, texts, and workbooks optimized for each user. Specifically, a generation AI model is used as the software, and customized learning materials are created by inputting prompts.

[0463] The terminal displays learning data retrieved from the server to the user. As the user learns, their progress is automatically recorded and sent to the server. This allows the learning progress to be updated in real time, and the server uses this data to analyze the progress.

[0464] To address user questions during their learning process, the system includes a real-time question-answering function. When a user enters a question via their device, the server uses AI generation to quickly generate an answer, supporting the user's learning.

[0465] Furthermore, the server promotes a deeper understanding of Japanese culture among users through interactive cultural content. This includes quizzes and explanations on traditional events, historical background, and cultural knowledge, providing a multicultural educational experience.

[0466] For example, when learning new kanji characters, the device visually displays how to write them and provides examples of pronunciation and usage to aid user understanding. Examples of prompts to input into the generation AI model include, "Generate a quiz about Japanese history for 5th graders," and "Provide content that shows how to learn new kanji characters for 2nd year middle school students." In this way, it is possible to provide users with a flexible and effective educational experience.

[0467] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0468] Step 1: Generating an Educational Plan

[0469] The server receives individual information entered by the user (age, grade level, educational goals, etc.). Based on this input, it accesses the Japanese compulsory education curriculum database and generates an educational plan optimized for the user. In this process, the curriculum is dynamically selected according to age and learning level, and an educational plan is generated as output with individual educational goals set.

[0470] Step 2: Presentation of training data

[0471] Based on the educational plan, the server selects appropriate learning data (video materials, text materials, workbooks, etc.) and sends it to the terminal. The terminal receives this data and displays it on the screen when the user begins learning. At this stage, the learning content is provided as output data from the server and is visually displayed to the user by the terminal.

[0472] Step 3: Record and submit your learning progress

[0473] The device automatically records the user's learning activities (such as completed assignments and test results). This data is sent to the server as a progress log. The server receives and aggregates the progress logs and creates output data that centrally manages the user's learning progress.

[0474] Step 4: Analysis of progress data

[0475] The server analyzes the received progress data to evaluate the user's understanding and learning speed. This involves using data analysis techniques to calculate the user's accuracy rate and problem-solving time, and outputting analysis results that evaluate learning efficiency.

[0476] Step 5: Adjusting the Education Plan

[0477] Based on the analysis results, the server dynamically adjusts the educational plan. Here, it uses a generation AI model to create additional teaching materials for areas where understanding is lacking, and updates the educational plan as output, providing new educational resources.

[0478] Step 6: Real-time question answering

[0479] If a user encounters a question during their learning process, they input the question through their device. The server analyzes the question using a generative AI model and generates an appropriate answer. This answer is then immediately provided to the user, supporting their learning.

[0480] Step 7: Providing Cultural Content

[0481] The server generates and delivers interactive content about Japanese culture to the user's device. The user then uses this content to deepen their knowledge of the culture. In this process, the server selects and generates cultural content, and as output, provides an interactive learning experience through the device.

[0482] (Application Example 1)

[0483] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0484] In today's educational environment, there is a demand for personalized learning experiences tailored to individual learners. However, traditional educational systems struggle to provide appropriate educational plans and content in real time while considering individual learning progress and comprehension levels. Furthermore, interactive educational methods for deepening understanding of Japanese culture are limited. In addition, there is a lack of effective means to resolve learners' questions on the spot.

[0485] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0486] In this invention, the server includes a device for generating educational plans based on a child's learning objectives, a mechanism for presenting educational materials delivered according to the individual educational plan, means for recording and analyzing the user's learning progress, and a robotic device for presenting educational content using sound and visuals. This enables the provision of personalized learning plans, real-time question answering, and effective learning of Japanese culture.

[0487] A "device for generating educational plans based on children's learning objectives" is a system for formulating individualized educational strategies tailored to the learner's age, interests, and level of understanding.

[0488] A "mechanism for providing educational materials delivered according to individual educational plans" is a system for providing learners with teaching materials and learning content that are compatible with their educational plans.

[0489] "Means for recording and analyzing users' learning progress" refers to methods for recording how far learners have progressed in their studies and analyzing their progress based on that data.

[0490] A "robot device that presents educational content using sound and visuals" is a robot-type device that provides educational content to learners by utilizing sound and video technology.

[0491] A "real-time prompt for generating answers to questions" refers to an input instruction in an algorithm or system that immediately generates a response to a learner's question.

[0492] "Learning materials related to Japanese culture" refers to educational content about Japanese traditions, customs, and history.

[0493] To implement this invention, it is necessary to build a system in which a server, a terminal, and a user work together in cooperation. First, the server receives individual information of the learner as input and generates an educational plan optimized for the learner's learning objectives based on that information. This plan reflects the learner's age, grade level, and specific learning objectives.

[0494] The device displays relevant educational content to learners according to this educational plan. This content includes videos, text, and interactive cultural learning materials, designed to effectively support learning. The device continuously records progress and test results, sending them to the server. Based on this information, the server analyzes it, adjusts the educational plan as needed, and suggests appropriate educational content tailored to the learner's progress.

[0495] In addition, the device is equipped with robotic functions that can be operated by gestures and voice, presenting educational content through an interactive and visual experience. Specifically, it provides audio and visual presentation functions, for example, by offering explanations accompanied by actual movements when teaching how to write or pronounce kanji characters.

[0496] If a user has a question, they can input it through their device. The server uses a generative AI model to answer the question in real time, helping learners deepen their understanding on the spot. For example, it can instantly answer questions like, "How do you pronounce the kanji for 'mikan' (orange)?"

[0497] This invention is built using embedded AI platforms such as NVIDIA's Jetson series and utilizes prompts from a generative AI model to generate effective answers to questions. An example of a prompt is, "Generate a kanji learning plan for a second-grade elementary school student. Next, suggest adjusting the learning content based on the following levels of understanding." In this way, the entire system works together to realize a personalized educational experience.

[0498] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0499] Step 1:

[0500] The server receives individualized information from the user, such as age, grade level, and learning objectives. Using this information as input, it generates a personalized learning plan for the learner. The generated plan includes an individualized learning strategy, such as which subjects should be studied in focus. This plan is then sent to the terminal.

[0501] Step 2:

[0502] The device prepares appropriate educational content based on the educational plan sent from the server. Video materials, text materials, and interactive cultural materials are selected and displayed. Specifically, the device projects visual content onto a screen using a projector and provides audio commentary through a speaker. This process is adjusted according to the user's progress.

[0503] Step 3:

[0504] When a user completes each learning session, the device records test results and progress data. This data is collected and sent to a server. The server analyzes the received data to identify areas of learning comprehension and areas where there are challenges. Based on this analysis, the educational plan is automatically adjusted. For example, areas where understanding is weak will have additional content added to reinforce them.

[0505] Step 4:

[0506] When a user has a question, they input it via their device. The server uses a generative AI model to generate a prompt related to this question and prepare an appropriate answer. An immediate answer to the question is generated and presented to the user via their device. This process is designed to resolve any questions the user may have during the learning process and deepen their understanding. By utilizing the "generative AI model," specific questions such as "How do you pronounce the kanji for 'mikan'?" can be answered in both voice and text.

[0507] Step 5:

[0508] The server delivers interactive Japanese cultural content to the terminal. The terminal uses robotic functions to display this content and provides explanations through voice and movement. For example, the terminal can interactively manipulate visual learning materials with audio guides in response to user reactions. This makes learning more effective and engaging.

[0509] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0510] This invention is a system for providing users with a personalized learning experience, aiming to further enhance the quality of learning by incorporating an emotion engine. In addition to generating educational plans, presenting learning content, recording and analyzing progress, and adjusting plans, this system recognizes the user's emotions and utilizes that information to optimize learning.

[0511] The server's initial role is to generate an educational plan based on the user's learning goals and current progress. This plan is rooted in the requirements of Japanese compulsory education and tailored to individual learning needs. The server then schedules learning content according to this plan and delivers it to the user via the terminal.

[0512] The device presents content received from the server to the user. This includes not only video learning materials, exercises, and quizzes, but also the hardware necessary for the emotion engine to recognize emotions from the user's speech and facial expressions.

[0513] This emotion engine analyzes subtle emotional changes in the user in real time during daily learning sessions and sends feedback to the server. The server analyzes this emotional data to evaluate the user's learning quality and motivation, and flexibly adjusts the learning content and how it is presented accordingly. For example, if the user is showing signs of stress or confusion, the server can present easier problems or add content that promotes relaxation.

[0514] Furthermore, the server facilitates effective learning by further tailoring the educational plan based on the progress and sentiment data it analyzes. When a user experiences a moderate sense of accomplishment or positive emotions, the server suggests challenging and amplified learning content to maintain motivation.

[0515] For example, if a user is frustrated because they cannot write kanji correctly, the emotion engine will sense this, and the server will immediately provide feedback. The device will then help the user maintain a positive learning experience by suggesting increasing practice time or switching to easier steps. In this way, the present invention achieves more intuitive and personalized learning by using an emotion engine.

[0516] The following describes the processing flow.

[0517] Step 1:

[0518] Users register with the system using their device and input information such as their child's age, learning goals, and areas of interest. Based on this information, users set learning priorities.

[0519] Step 2:

[0520] Based on the user information received by the server, an individualized educational plan is generated. The plan is customized to maximize the learner's progress and includes content that conforms to Japanese educational requirements.

[0521] Step 3:

[0522] Based on the educational plan generated by the server, learning content is compiled and delivered to the devices. This content includes text materials, videos, and interactive assignments.

[0523] Step 4:

[0524] The device uses sensors to capture the user's voice and facial expressions during training, enabling real-time emotion recognition by an emotion engine.

[0525] Step 5:

[0526] The emotion engine analyzes the user's emotions, identifying stress, confusion, and changes in motivation. This data is immediately sent to the server.

[0527] Step 6:

[0528] The server integrates emotional data and learning progress to adjust content according to the user's emotional state. For example, if the user is feeling stressed, it will present content with a lower difficulty level.

[0529] Step 7:

[0530] The server delivers emotional data-based feedback and support content aimed at improving motivation to the device.

[0531] Step 8:

[0532] The device presents new content to the user, allowing the user to continue learning. The user can progress through the learning process with support from the system.

[0533] Step 9:

[0534] The server periodically evaluates collected learning and sentiment data to generate updated educational plans that further refine long-term educational strategies. This cycle is repeated, providing users with an optimized learning experience.

[0535] (Example 2)

[0536] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0537] Existing learning systems tend to focus solely on knowledge transfer without considering the emotional state of individual learners. This leads to challenges such as difficulty maintaining motivation and decreased learning efficiency. Furthermore, there is insufficient provision of content optimized for cultural backgrounds and learning objectives.

[0538] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0539] In this invention, the server includes means for generating an educational plan based on the learner's goals, means for presenting learning content that conforms to the unit's educational plan, means for recording and analyzing the user's learning progress, and means for analyzing emotional information and adaptively adjusting the learning content based on the analysis results. This makes it possible to provide flexible learning plans that are tailored to the individual learner's emotions and progress.

[0540] "Learner's goals" refer to the specific skills and knowledge acquisition targets that users aim to achieve.

[0541] An "educational plan" refers to educational guidelines and schedules that are constructed based on learners' goals and progress.

[0542] "Learning content" refers to the teaching materials and assignments provided to learners based on the educational plan.

[0543] "User learning progress" refers to an evaluation criterion that shows how much content a learner has learned according to the educational plan.

[0544] "Emotional information" refers to data that indicates the emotions and psychological states expressed by learners during the learning process.

[0545] "Analysis" refers to the process of analyzing collected data and information to derive meaning and trends.

[0546] "Adaptive adjustment" refers to the act of flexibly changing learning plans and content in response to the results of analysis.

[0547] This invention is a system for providing learners with a personalized learning experience. This system is realized by coordinating a server, a terminal, and an emotion engine.

[0548] The server uses AI algorithms to generate individualized learning plans, taking into account the learner's goals and progress. These plans are optimized to meet the learner's specific learning needs and comply with Japanese compulsory education standards. Based on these plans, the server schedules and delivers the necessary learning content to the user's device. This process utilizes a database system capable of handling large amounts of data and optimized network protocols.

[0549] The terminal provides an interface for presenting learning content received from the server to the learner. It can present content in various formats, such as video materials and quizzes. Furthermore, the terminal incorporates an emotion engine and is equipped with hardware for real-time monitoring of the learner's emotional state using speech and facial recognition technologies. This includes a webcam and a high-sensitivity microphone.

[0550] The emotion engine analyzes the learner's voice tone and facial expressions, and feeds the resulting emotional information back to the server. The server analyzes this feedback and assesses whether the learner is stressed or relaxed. Based on this, the server adaptively adjusts the content to enable the learner to continue learning in a more effective way.

[0551] For example, if a learner becomes frustrated while practicing difficult kanji characters, the emotion engine detects this. The server immediately receives this information and sends new instructions to the learner. The device then presents the learner with options to increase practice time or switch to easier practice problems.

[0552] An example of a prompt for a generative AI model is, "If the emotion engine detects that the user is experiencing stress, what kind of learning content should be provided?" Based on this prompt, the AI ​​model generates the most suitable content.

[0553] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0554] Step 1:

[0555] The server retrieves the user's learning goals and past learning records from a database. Based on this data, it uses an AI algorithm to generate an individualized learning plan. Specifically, it analyzes the learning content necessary to achieve the goals and constructs step-by-step learning steps. It receives the user's learning history and set goals as input and generates an individually optimized learning plan as output.

[0556] Step 2:

[0557] The server schedules the necessary learning content based on the generated educational plan. It creates a list of content for each learning point and determines the appropriate timing to present them to the user. It receives educational plan data as input and generates a list of scheduled content as output. Specifically, it determines which content to present and in what order, and prepares it for delivery to the terminal.

[0558] Step 3:

[0559] The terminal presents learning content received from the server to the user. This content includes videos, learning materials, quizzes, and more. The terminal's interface allows users to easily access this content. It receives content data from the server as input and presents visual and auditory information to the user as output.

[0560] Step 4:

[0561] The device uses a built-in emotion engine to monitor the user's emotional state in real time. It uses microphones and cameras to sense and analyze the user's voice and facial expressions. It takes user audio and video data as input and obtains the results of the emotion analysis as output. Specifically, it determines whether the user is feeling frustrated or anxious.

[0562] Step 5:

[0563] The server analyzes the sentiment analysis results sent from the terminal and makes adjustments to enhance learning effectiveness. It changes the difficulty level of content or adds new content as needed. It receives sentiment analysis data as input and generates adjusted educational plans and content as output. For example, if a user is experiencing stress, it might add relaxation-promoting materials.

[0564] Step 6:

[0565] The server monitors overall learning progress and periodically updates the educational plan. This process uses comprehensive data analysis that combines user progress records and sentiment data. Learning progress data and sentiment status are taken as input, and an updated educational plan is generated as output. This ensures that the learning experience is always optimized for the user.

[0566] (Application Example 2)

[0567] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0568] Traditional educational support systems have struggled to fully understand the emotions and motivations of each learner and provide appropriate content and feedback in real time, resulting in a decline in the quality of learning. Furthermore, it has been difficult to reduce the stress and frustration children experience during learning and to provide a positive learning experience.

[0569] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0570] In this invention, the server includes means for generating a learning plan tailored to a child's educational goals, means for presenting educational materials provided based on the individual learning plan, means for recording and evaluating the user's learning progress, means for adjusting the learning plan based on the evaluation results, and means for recognizing emotional information and adjusting the learning content based on said information. This enables the provision of appropriate educational content tailored to the learner's emotions, resulting in a personalized learning experience.

[0571] "Children" refers to young people who are eligible to receive learning support.

[0572] "Educational objectives" refer to the specific standards of knowledge and skills that learners are expected to achieve.

[0573] A "learning plan" refers to a schedule or curriculum that is systematically designed to achieve educational goals.

[0574] "Means" refers to the methods or devices employed to achieve a specific objective.

[0575] "Educational materials" refer to teaching materials and reference materials provided to learners.

[0576] "To present" refers to delivering information or content to learners visually or aurally.

[0577] "Progress" refers to the process or stage of results toward achieving a specific goal.

[0578] "Evaluation" refers to judging progress and results based on specific criteria.

[0579] "To adjust" refers to changing settings or plans to an optimal state depending on the situation and needs.

[0580] "Emotional information" refers to data and signals that indicate a learner's emotions and psychological state.

[0581] "Adjusting" refers to changing the services or functions provided according to the user's condition and needs.

[0582] The system for realizing this application implements each function with the server, terminal, and user as the main subjects. The server generates a learning plan based on the child's educational goals. This includes creating an appropriate curriculum that reflects the user's current learning progress and emotional state. The server also sends learning materials and content to the terminal in accordance with the generated learning plan.

[0583] The terminal displays content received from the server to the user and monitors the user's facial expressions and voice in real time using hardware such as cameras and microphones. This data is processed by an emotion recognition engine to determine the user's emotional state. The software used includes an emotion recognition algorithm and an AI for generating educational plans.

[0584] Specifically, if a user's facial expression indicates dissatisfaction while working through the learning materials, the server can use that information to switch to easier problems or suggest taking a break during the learning process. Furthermore, if the server detects that the user is calm, it can encourage them to tackle slightly more difficult problems.

[0585] For example, if a user is having difficulty writing kanji characters, the system's emotion engine will detect this, and the server will generate a flexible response based on the user's learning progress. An example of a prompt might be, "Analyze the emotions the child is feeling based on facial expression and voice data, and adjust the learning program accordingly."

[0586] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0587] Step 1:

[0588] The server receives the user's educational goals and current learning progress as input and generates a learning plan. The program analyzes this data and selects the necessary educational content. The output is a curriculum tailored to the user. Specifically, this involves referencing a database of past learning history and applying an educational AI model.

[0589] Step 2:

[0590] The server selects the necessary learning content based on the generated learning plan and sends it to the terminal. The output is the learning materials and information displayed to the user. In this step, videos, quizzes, practice questions, etc., are selected according to the user's progress level.

[0591] Step 3:

[0592] The terminal presents learning content received from the server to the user. The input is educational materials sent from the server. The output is the learning material content displayed on the user's screen. In addition to display, interactive materials accept user responses.

[0593] Step 4:

[0594] The device uses its built-in camera and microphone to collect emotional information as input, capturing the user's facial expressions and voice data in real time. The output is processed emotional data. The collected data is analyzed by an emotion recognition algorithm to determine the user's emotional state.

[0595] Step 5:

[0596] The server adjusts existing learning plans and content based on sentiment information received from the terminal. The input is analyzed sentiment data, and the output is the adjusted learning plan and content. Specifically, if dissatisfaction is detected, actions such as lowering the difficulty level are taken.

[0597] Step 6:

[0598] The user continues learning based on the new learning content and suggestions presented on the device. The output is the user's progress data. This data is fed back as input to step 1, continuously optimizing the system's operation.

[0599] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0600] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0601] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0602] [Fourth Embodiment]

[0603] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0604] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0605] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0606] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0607] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0608] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0609] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0610] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0611] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0612] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0613] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0614] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0615] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0616] The system of the present invention provides users with a personalized learning experience, enabling the generation of educational plans, presentation of learning content, recording and analysis of progress, adjustment of plans, real-time question answering, and delivery of interactive cultural content. This allows users to efficiently acquire Japanese compulsory education and culture.

[0617] The server's first step is to generate an educational plan based on the individual information provided by the user. The server considers the child's age, grade level, and educational goals, and creates a curriculum that conforms to the Japanese compulsory education curriculum guidelines. This ensures that the content is best suited to the learner.

[0618] When a user begins their daily learning activities through their device, the device displays learning content provided by the server. This includes video materials, text materials, and workbooks, each organized according to the educational plan.

[0619] Progress tracking is extremely important. The terminal continuously records completed tasks and test results and sends them to the server. The server collects this data and analyzes the user's understanding and progress. Based on the analysis, the server adjusts the educational plan and provides additional materials tailored to the user's progress and areas of weakness.

[0620] When a user has a question, they can input it in real time through their device. The server's AI receives the question and provides an immediate answer. This allows learners to resolve their questions quickly.

[0621] Furthermore, as part of cultural learning, the server delivers interactive content to the terminals. This includes lectures on traditional Japanese events and the formation of history, as well as quizzes about cultural customs. Through this, users can deepen their understanding of Japanese culture.

[0622] Through the process described above, this system provides users with a comprehensive and personalized educational experience, efficiently meeting Japanese educational requirements while accommodating learning in a multicultural environment. For example, when learning new kanji characters, the device visually displays how to write them and provides examples of their usage, including pronunciation, to aid user understanding. This allows learners to improve their Japanese language skills in an enjoyable and effective way.

[0623] The following describes the processing flow.

[0624] Step 1:

[0625] Users register with the system using their device and enter information such as their child's age, grade level, and learning goals. Users also select the goals they wish to achieve in their current area of ​​education.

[0626] Step 2:

[0627] Based on the information received from the user, the server generates an initial educational plan. Following the Japanese compulsory education curriculum guidelines, the server designs a curriculum for subjects such as Japanese language, mathematics, social studies, and science that is tailored to the participants' needs.

[0628] Step 3:

[0629] Based on the educational plan generated by the server, daily learning content is designed and delivered to the devices. This content includes video materials, texts, quizzes, and practical exercises.

[0630] Step 4:

[0631] Users access content through their devices and progress through their learning. Users reinforce their knowledge by watching learning materials and solving assignments. If questions arise, users can use the question function on their devices to make inquiries.

[0632] Step 5:

[0633] The generating AI receives questions from users and provides immediate answers. The server presents relevant additional materials to support the user's understanding.

[0634] Step 6:

[0635] The device records the user's learning progress. This progress includes the number of completed assignments, test results, and teacher evaluations. This data is sent to the server as a learning history.

[0636] Step 7:

[0637] The server analyzes progress data to identify areas where the user is struggling. Based on the analysis results, the educational plan is adjusted, and content is redesigned to strengthen remedial instruction in specific areas.

[0638] Step 8:

[0639] The server generates and delivers periodic evaluation tests to the terminal. Users take these tests and set their next learning goals based on the results. Based on the test results, the server provides the user with feedback and suggestions for improvement.

[0640] Step 9:

[0641] Users receive feedback and prepare for the next learning cycle. The server creates updated educational plans and continuously optimizes the learning process.

[0642] (Example 1)

[0643] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0644] Traditional education systems struggle to provide personalized education for individual learners, and uniform curricula lead to decreased learning efficiency. Furthermore, they fail to adequately address the needs of diverse learners with varying educational goals due to insufficient adjustment of dynamic educational plans and the cultivation of cultural knowledge. Additionally, they lack means to quickly resolve user questions that arise during learning.

[0645] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0646] In this invention, the server includes means for generating an educational plan that conforms to learning objectives based on individual information, means for presenting learning data according to the generated educational plan, means for recording the user's learning progress and transmitting it to a database for analysis, means for dynamically adjusting the educational plan based on the analysis results, and means for generating variable educational content based on instructional statements using a generation AI. This makes it possible to provide users with efficient and personalized educational plans.

[0647] "Individual information" refers to personalized information about each learner, such as the user's age, grade level, and educational goals.

[0648] An "educational plan" refers to learning content and curriculum optimized based on individual information.

[0649] "Learning data" refers to educational materials such as videos, texts, and workbooks provided based on the educational plan.

[0650] "Learning progress" refers to information that shows the progress of educational activities, such as assignments completed by the user and test results.

[0651] A "database" is a system for collecting and managing recorded information on learning progress and educational plans.

[0652] "Analysis results" refer to the evaluation results of the user's level of understanding and the educational plan obtained by analyzing learning progress data.

[0653] "Dynamic adjustment" refers to the process of modifying and updating the educational plan as needed based on the analysis results.

[0654] "Generative AI" is a technology that uses artificial intelligence to create new educational content from instructions and prompts.

[0655] An "instruction statement" is a text-based command given to a generation AI to generate specific educational content.

[0656] This invention implements an educational system in which three elements—a server, a terminal, and a user—operate together as a single unit.

[0657] The server receives individual information registered by users, compares it with the Japanese compulsory education curriculum database, and automatically generates an educational plan that conforms to the learning objectives. Based on this plan, the server provides learning data such as videos, texts, and workbooks optimized for each user. Specifically, a generation AI model is used as the software, and customized learning materials are created by inputting prompts.

[0658] The terminal displays learning data retrieved from the server to the user. As the user learns, their progress is automatically recorded and sent to the server. This allows the learning progress to be updated in real time, and the server uses this data to analyze the progress.

[0659] To address user questions during their learning process, the system includes a real-time question-answering function. When a user enters a question via their device, the server uses AI generation to quickly generate an answer, supporting the user's learning.

[0660] Furthermore, the server promotes a deeper understanding of Japanese culture among users through interactive cultural content. This includes quizzes and explanations on traditional events, historical background, and cultural knowledge, providing a multicultural educational experience.

[0661] For example, when learning new kanji characters, the device visually displays how to write them and provides examples of pronunciation and usage to aid user understanding. Examples of prompts to input into the generation AI model include, "Generate a quiz about Japanese history for 5th graders," and "Provide content that shows how to learn new kanji characters for 2nd year middle school students." In this way, it is possible to provide users with a flexible and effective educational experience.

[0662] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0663] Step 1: Generating an Educational Plan

[0664] The server receives individual information entered by the user (age, grade level, educational goals, etc.). Based on this input, it accesses the Japanese compulsory education curriculum database and generates an educational plan optimized for the user. In this process, the curriculum is dynamically selected according to age and learning level, and an educational plan is generated as output with individual educational goals set.

[0665] Step 2: Presentation of training data

[0666] Based on the educational plan, the server selects appropriate learning data (video materials, text materials, workbooks, etc.) and sends it to the terminal. The terminal receives this data and displays it on the screen when the user begins learning. At this stage, the learning content is provided as output data from the server and is visually displayed to the user by the terminal.

[0667] Step 3: Record and submit your learning progress

[0668] The device automatically records the user's learning activities (such as completed assignments and test results). This data is sent to the server as a progress log. The server receives and aggregates the progress logs and creates output data that centrally manages the user's learning progress.

[0669] Step 4: Analysis of progress data

[0670] The server analyzes the received progress data to evaluate the user's understanding and learning speed. This involves using data analysis techniques to calculate the user's accuracy rate and problem-solving time, and outputting analysis results that evaluate learning efficiency.

[0671] Step 5: Adjusting the Education Plan

[0672] Based on the analysis results, the server dynamically adjusts the educational plan. Here, it uses a generation AI model to create additional teaching materials for areas where understanding is lacking, and updates the educational plan as output, providing new educational resources.

[0673] Step 6: Real-time question answering

[0674] If a user encounters a question during their learning process, they input the question through their device. The server analyzes the question using a generative AI model and generates an appropriate answer. This answer is then immediately provided to the user, supporting their learning.

[0675] Step 7: Providing Cultural Content

[0676] The server generates and delivers interactive content about Japanese culture to the user's device. The user then uses this content to deepen their knowledge of the culture. In this process, the server selects and generates cultural content, and as output, provides an interactive learning experience through the device.

[0677] (Application Example 1)

[0678] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0679] In today's educational environment, there is a demand for personalized learning experiences tailored to individual learners. However, traditional educational systems struggle to provide appropriate educational plans and content in real time while considering individual learning progress and comprehension levels. Furthermore, interactive educational methods for deepening understanding of Japanese culture are limited. In addition, there is a lack of effective means to resolve learners' questions on the spot.

[0680] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0681] In this invention, the server includes a device for generating educational plans based on a child's learning objectives, a mechanism for presenting educational materials delivered according to the individual educational plan, means for recording and analyzing the user's learning progress, and a robotic device for presenting educational content using sound and visuals. This enables the provision of personalized learning plans, real-time question answering, and effective learning of Japanese culture.

[0682] A "device for generating educational plans based on children's learning objectives" is a system for formulating individualized educational strategies tailored to the learner's age, interests, and level of understanding.

[0683] A "mechanism for providing educational materials delivered according to individual educational plans" is a system for providing learners with teaching materials and learning content that are compatible with their educational plans.

[0684] "Means for recording and analyzing users' learning progress" refers to methods for recording how far learners have progressed in their studies and analyzing their progress based on that data.

[0685] A "robot device that presents educational content using sound and visuals" is a robot-type device that provides educational content to learners by utilizing sound and video technology.

[0686] A "real-time prompt for generating answers to questions" refers to an input instruction in an algorithm or system that immediately generates a response to a learner's question.

[0687] "Learning materials related to Japanese culture" refers to educational content about Japanese traditions, customs, and history.

[0688] To implement this invention, it is necessary to build a system in which a server, a terminal, and a user work together in cooperation. First, the server receives individual information of the learner as input and generates an educational plan optimized for the learner's learning objectives based on that information. This plan reflects the learner's age, grade level, and specific learning objectives.

[0689] The device displays relevant educational content to learners according to this educational plan. This content includes videos, text, and interactive cultural learning materials, designed to effectively support learning. The device continuously records progress and test results, sending them to the server. Based on this information, the server analyzes it, adjusts the educational plan as needed, and suggests appropriate educational content tailored to the learner's progress.

[0690] In addition, the device is equipped with robotic functions that can be operated by gestures and voice, presenting educational content through an interactive and visual experience. Specifically, it provides audio and visual presentation functions, for example, by offering explanations accompanied by actual movements when teaching how to write or pronounce kanji characters.

[0691] If a user has a question, they can input it through their device. The server uses a generative AI model to answer the question in real time, helping learners deepen their understanding on the spot. For example, it can instantly answer questions like, "How do you pronounce the kanji for 'mikan' (orange)?"

[0692] This invention is built using embedded AI platforms such as NVIDIA's Jetson series and utilizes prompts from a generative AI model to generate effective answers to questions. An example of a prompt is, "Generate a kanji learning plan for a second-grade elementary school student. Next, suggest adjusting the learning content based on the following levels of understanding." In this way, the entire system works together to realize a personalized educational experience.

[0693] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0694] Step 1:

[0695] The server receives individualized information from the user, such as age, grade level, and learning objectives. Using this information as input, it generates a personalized learning plan for the learner. The generated plan includes an individualized learning strategy, such as which subjects should be studied in focus. This plan is then sent to the terminal.

[0696] Step 2:

[0697] The device prepares appropriate educational content based on the educational plan sent from the server. Video materials, text materials, and interactive cultural materials are selected and displayed. Specifically, the device projects visual content onto a screen using a projector and provides audio commentary through a speaker. This process is adjusted according to the user's progress.

[0698] Step 3:

[0699] When a user completes each learning session, the device records test results and progress data. This data is collected and sent to a server. The server analyzes the received data to identify areas of learning comprehension and areas where there are challenges. Based on this analysis, the educational plan is automatically adjusted. For example, areas where understanding is weak will have additional content added to reinforce them.

[0700] Step 4:

[0701] When a user has a question, they input it via their device. The server uses a generative AI model to generate a prompt related to this question and prepare an appropriate answer. An immediate answer to the question is generated and presented to the user via their device. This process is designed to resolve any questions the user may have during the learning process and deepen their understanding. By utilizing the "generative AI model," specific questions such as "How do you pronounce the kanji for 'mikan'?" can be answered in both voice and text.

[0702] Step 5:

[0703] The server delivers interactive Japanese cultural content to the terminal. The terminal uses robotic functions to display this content and provides explanations through voice and movement. For example, the terminal can interactively manipulate visual learning materials with audio guides in response to user reactions. This makes learning more effective and engaging.

[0704] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0705] This invention is a system for providing users with a personalized learning experience, aiming to further enhance the quality of learning by incorporating an emotion engine. In addition to generating educational plans, presenting learning content, recording and analyzing progress, and adjusting plans, this system recognizes the user's emotions and utilizes that information to optimize learning.

[0706] The server's initial role is to generate an educational plan based on the user's learning goals and current progress. This plan is rooted in the requirements of Japanese compulsory education and tailored to individual learning needs. The server then schedules learning content according to this plan and delivers it to the user via the terminal.

[0707] The device presents content received from the server to the user. This includes not only video learning materials, exercises, and quizzes, but also the hardware necessary for the emotion engine to recognize emotions from the user's speech and facial expressions.

[0708] This emotion engine analyzes subtle emotional changes in the user in real time during daily learning sessions and sends feedback to the server. The server analyzes this emotional data to evaluate the user's learning quality and motivation, and flexibly adjusts the learning content and how it is presented accordingly. For example, if the user is showing signs of stress or confusion, the server can present easier problems or add content that promotes relaxation.

[0709] Furthermore, the server facilitates effective learning by further tailoring the educational plan based on the progress and sentiment data it analyzes. When a user experiences a moderate sense of accomplishment or positive emotions, the server suggests challenging and amplified learning content to maintain motivation.

[0710] For example, if a user is frustrated because they cannot write kanji correctly, the emotion engine will sense this, and the server will immediately provide feedback. The device will then help the user maintain a positive learning experience by suggesting increasing practice time or switching to easier steps. In this way, the present invention achieves more intuitive and personalized learning by using an emotion engine.

[0711] The following describes the processing flow.

[0712] Step 1:

[0713] Users register with the system using their device and input information such as their child's age, learning goals, and areas of interest. Based on this information, users set learning priorities.

[0714] Step 2:

[0715] Based on the user information received by the server, an individualized educational plan is generated. The plan is customized to maximize the learner's progress and includes content that conforms to Japanese educational requirements.

[0716] Step 3:

[0717] Based on the educational plan generated by the server, learning content is compiled and delivered to the devices. This content includes text materials, videos, and interactive assignments.

[0718] Step 4:

[0719] The device uses sensors to capture the user's voice and facial expressions during training, enabling real-time emotion recognition by an emotion engine.

[0720] Step 5:

[0721] The emotion engine analyzes the user's emotions, identifying stress, confusion, and changes in motivation. This data is immediately sent to the server.

[0722] Step 6:

[0723] The server integrates emotional data and learning progress to adjust content according to the user's emotional state. For example, if the user is feeling stressed, it will present content with a lower difficulty level.

[0724] Step 7:

[0725] The server delivers emotional data-based feedback and support content aimed at improving motivation to the device.

[0726] Step 8:

[0727] The device presents new content to the user, allowing the user to continue learning. The user can progress through the learning process with support from the system.

[0728] Step 9:

[0729] The server periodically evaluates collected learning and sentiment data to generate updated educational plans that further refine long-term educational strategies. This cycle is repeated, providing users with an optimized learning experience.

[0730] (Example 2)

[0731] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0732] Existing learning systems tend to focus solely on knowledge transfer without considering the emotional state of individual learners. This leads to challenges such as difficulty maintaining motivation and decreased learning efficiency. Furthermore, there is insufficient provision of content optimized for cultural backgrounds and learning objectives.

[0733] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0734] In this invention, the server includes means for generating an educational plan based on the learner's goals, means for presenting learning content that conforms to the unit's educational plan, means for recording and analyzing the user's learning progress, and means for analyzing emotional information and adaptively adjusting the learning content based on the analysis results. This makes it possible to provide flexible learning plans that are tailored to the individual learner's emotions and progress.

[0735] "Learner's goals" refer to the specific skills and knowledge acquisition targets that users aim to achieve.

[0736] An "educational plan" refers to educational guidelines and schedules that are constructed based on learners' goals and progress.

[0737] "Learning content" refers to the teaching materials and assignments provided to learners based on the educational plan.

[0738] "User learning progress" refers to an evaluation criterion that shows how much content a learner has learned according to the educational plan.

[0739] "Emotional information" refers to data that indicates the emotions and psychological states expressed by learners during the learning process.

[0740] "Analysis" refers to the process of analyzing collected data and information to derive meaning and trends.

[0741] "Adaptive adjustment" refers to the act of flexibly changing learning plans and content in response to the results of analysis.

[0742] This invention is a system for providing learners with a personalized learning experience. This system is realized by coordinating a server, a terminal, and an emotion engine.

[0743] The server uses AI algorithms to generate individualized learning plans, taking into account the learner's goals and progress. These plans are optimized to meet the learner's specific learning needs and comply with Japanese compulsory education standards. Based on these plans, the server schedules and delivers the necessary learning content to the user's device. This process utilizes a database system capable of handling large amounts of data and optimized network protocols.

[0744] The terminal provides an interface for presenting learning content received from the server to the learner. It can present content in various formats, such as video materials and quizzes. Furthermore, the terminal incorporates an emotion engine and is equipped with hardware for real-time monitoring of the learner's emotional state using speech and facial recognition technologies. This includes a webcam and a high-sensitivity microphone.

[0745] The emotion engine analyzes the learner's voice tone and facial expressions, and feeds the resulting emotional information back to the server. The server analyzes this feedback and assesses whether the learner is stressed or relaxed. Based on this, the server adaptively adjusts the content to enable the learner to continue learning in a more effective way.

[0746] For example, if a learner becomes frustrated while practicing difficult kanji characters, the emotion engine detects this. The server immediately receives this information and sends new instructions to the learner. The device then presents the learner with options to increase practice time or switch to easier practice problems.

[0747] An example of a prompt for a generative AI model is, "If the emotion engine detects that the user is experiencing stress, what kind of learning content should be provided?" Based on this prompt, the AI ​​model generates the most suitable content.

[0748] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0749] Step 1:

[0750] The server retrieves the user's learning goals and past learning records from a database. Based on this data, it uses an AI algorithm to generate an individualized learning plan. Specifically, it analyzes the learning content necessary to achieve the goals and constructs step-by-step learning steps. It receives the user's learning history and set goals as input and generates an individually optimized learning plan as output.

[0751] Step 2:

[0752] The server schedules the necessary learning content based on the generated educational plan. It creates a list of content for each learning point and determines the appropriate timing to present them to the user. It receives educational plan data as input and generates a list of scheduled content as output. Specifically, it determines which content to present and in what order, and prepares it for delivery to the terminal.

[0753] Step 3:

[0754] The terminal presents learning content received from the server to the user. This content includes videos, learning materials, quizzes, and more. The terminal's interface allows users to easily access this content. It receives content data from the server as input and presents visual and auditory information to the user as output.

[0755] Step 4:

[0756] The device uses a built-in emotion engine to monitor the user's emotional state in real time. It uses microphones and cameras to sense and analyze the user's voice and facial expressions. It takes user audio and video data as input and obtains the results of the emotion analysis as output. Specifically, it determines whether the user is feeling frustrated or anxious.

[0757] Step 5:

[0758] The server analyzes the sentiment analysis results sent from the terminal and makes adjustments to enhance learning effectiveness. It changes the difficulty level of content or adds new content as needed. It receives sentiment analysis data as input and generates adjusted educational plans and content as output. For example, if a user is experiencing stress, it might add relaxation-promoting materials.

[0759] Step 6:

[0760] The server monitors overall learning progress and periodically updates the educational plan. This process uses comprehensive data analysis that combines user progress records and sentiment data. Learning progress data and sentiment status are taken as input, and an updated educational plan is generated as output. This ensures that the learning experience is always optimized for the user.

[0761] (Application Example 2)

[0762] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0763] Traditional educational support systems have struggled to fully understand the emotions and motivations of each learner and provide appropriate content and feedback in real time, resulting in a decline in the quality of learning. Furthermore, it has been difficult to reduce the stress and frustration children experience during learning and to provide a positive learning experience.

[0764] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0765] In this invention, the server includes means for generating a learning plan tailored to a child's educational goals, means for presenting educational materials provided based on the individual learning plan, means for recording and evaluating the user's learning progress, means for adjusting the learning plan based on the evaluation results, and means for recognizing emotional information and adjusting the learning content based on said information. This enables the provision of appropriate educational content tailored to the learner's emotions, resulting in a personalized learning experience.

[0766] "Children" refers to young people who are eligible to receive learning support.

[0767] "Educational objectives" refer to the specific standards of knowledge and skills that learners are expected to achieve.

[0768] A "learning plan" refers to a schedule or curriculum that is systematically designed to achieve educational goals.

[0769] "Means" refers to the methods or devices employed to achieve a specific objective.

[0770] "Educational materials" refer to teaching materials and reference materials provided to learners.

[0771] "To present" refers to delivering information or content to learners visually or aurally.

[0772] "Progress" refers to the process or stage of results toward achieving a specific goal.

[0773] "Evaluation" refers to judging progress and results based on specific criteria.

[0774] "To adjust" refers to changing settings or plans to an optimal state depending on the situation and needs.

[0775] "Emotional information" refers to data and signals that indicate a learner's emotions and psychological state.

[0776] "Adjusting" refers to changing the services or functions provided according to the user's condition and needs.

[0777] The system for realizing this application implements each function with the server, terminal, and user as the main subjects. The server generates a learning plan based on the child's educational goals. This includes creating an appropriate curriculum that reflects the user's current learning progress and emotional state. The server also sends learning materials and content to the terminal in accordance with the generated learning plan.

[0778] The terminal displays content received from the server to the user and monitors the user's facial expressions and voice in real time using hardware such as cameras and microphones. This data is processed by an emotion recognition engine to determine the user's emotional state. The software used includes an emotion recognition algorithm and an AI for generating educational plans.

[0779] Specifically, if a user's facial expression indicates dissatisfaction while working through the learning materials, the server can use that information to switch to easier problems or suggest taking a break during the learning process. Furthermore, if the server detects that the user is calm, it can encourage them to tackle slightly more difficult problems.

[0780] For example, if a user is having difficulty writing kanji characters, the system's emotion engine will detect this, and the server will generate a flexible response based on the user's learning progress. An example of a prompt might be, "Analyze the emotions the child is feeling based on facial expression and voice data, and adjust the learning program accordingly."

[0781] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0782] Step 1:

[0783] The server receives the user's educational goals and current learning progress as input and generates a learning plan. The program analyzes this data and selects the necessary educational content. The output is a curriculum tailored to the user. Specifically, this involves referencing a database of past learning history and applying an educational AI model.

[0784] Step 2:

[0785] The server selects the necessary learning content based on the generated learning plan and sends it to the terminal. The output is the learning materials and information displayed to the user. In this step, videos, quizzes, practice questions, etc., are selected according to the user's progress level.

[0786] Step 3:

[0787] The terminal presents learning content received from the server to the user. The input is educational materials sent from the server. The output is the learning material content displayed on the user's screen. In addition to display, interactive materials accept user responses.

[0788] Step 4:

[0789] The device uses its built-in camera and microphone to collect emotional information as input, capturing the user's facial expressions and voice data in real time. The output is processed emotional data. The collected data is analyzed by an emotion recognition algorithm to determine the user's emotional state.

[0790] Step 5:

[0791] The server adjusts existing learning plans and content based on sentiment information received from the terminal. The input is analyzed sentiment data, and the output is the adjusted learning plan and content. Specifically, if dissatisfaction is detected, actions such as lowering the difficulty level are taken.

[0792] Step 6:

[0793] The user continues learning based on the new learning content and suggestions presented on the device. The output is the user's progress data. This data is fed back as input to step 1, continuously optimizing the system's operation.

[0794] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0795] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0796] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0797] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0798] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0799] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0800] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0801] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0802] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0803] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0804] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0805] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0806] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0807] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0808] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0809] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0810] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0811] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0812] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0813] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0814] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0815] The following is further disclosed regarding the embodiments described above.

[0816] (Claim 1)

[0817] A means of generating an educational plan tailored to a child's learning goals,

[0818] A means of presenting learning content delivered based on individualized educational plans,

[0819] A means for recording and analyzing the user's learning progress,

[0820] Means for adjusting the educational plan based on the analysis results,

[0821] A system that includes this.

[0822] (Claim 2)

[0823] The system according to claim 1, which generates responses to questions in real time.

[0824] (Claim 3)

[0825] The system according to claim 1 for interactively supplying educational content related to Japanese culture.

[0826] "Example 1"

[0827] (Claim 1)

[0828] A means for generating an educational plan that is suitable for learning objectives based on individual information,

[0829] A means of presenting learning data according to the generated educational plan,

[0830] A means of recording the user's learning progress, sending it to a database for analysis,

[0831] A means for dynamically adjusting the educational plan based on the analysis results,

[0832] A method for generating variable educational content based on instructional text using a generation AI,

[0833] A system that includes this.

[0834] (Claim 2)

[0835] The system according to claim 1, which generates responses to user inquiries in real time.

[0836] (Claim 3)

[0837] The system according to claim 1, which provides interactive cultural data.

[0838] "Application Example 1"

[0839] (Claim 1)

[0840] A device that generates an educational plan based on children's learning objectives,

[0841] A mechanism that presents educational materials delivered according to individual educational plans,

[0842] A means for recording and analyzing the learning progress of users,

[0843] Means for adjusting the educational plan based on the analysis results,

[0844] A robotic device that presents educational content using sound and visuals,

[0845] A system that includes this.

[0846] (Claim 2)

[0847] The system according to claim 1, which provides learning support by using prompts that generate answers to questions in real time.

[0848] (Claim 3)

[0849] The system according to claim 1, which interactively provides learning materials related to Japanese culture and supports cultural understanding.

[0850] "Example 2 of combining an emotion engine"

[0851] (Claim 1)

[0852] A means of generating an educational plan based on learner goals,

[0853] A means of presenting learning content that conforms to the unit's educational plan,

[0854] A means for recording and analyzing the learning progress of users,

[0855] A means of adjusting the educational plan based on the analysis results,

[0856] A means of analyzing emotional information and adaptively adjusting learning content based on the analysis results,

[0857] A system that includes this.

[0858] (Claim 2)

[0859] The system according to claim 1, which generates responses to questions in real time.

[0860] (Claim 3)

[0861] The system according to claim 1, which provides cross-cultural educational content in both directions.

[0862] "Application example 2 when combining with an emotional engine"

[0863] (Claim 1)

[0864] A means of generating a learning plan tailored to a child's educational goals,

[0865] A means of presenting educational materials provided based on an individualized learning plan,

[0866] A means for recording and evaluating the user's learning progress,

[0867] A means of adjusting the learning plan based on the evaluation results,

[0868] A means for recognizing emotional information and adjusting learning content based on that information,

[0869] A system that includes this.

[0870] (Claim 2)

[0871] The system according to claim 1, which generates a response in real time.

[0872] (Claim 3)

[0873] The system according to claim 1, which provides cultural educational content in an interactive manner. [Explanation of symbols]

[0874] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of generating an educational plan tailored to a child's learning goals, A means of presenting learning content delivered based on individualized educational plans, A means for recording and analyzing the user's learning progress, Means for adjusting the educational plan based on the analysis results, A system that includes this.

2. The system according to claim 1, which generates responses to questions in real time.

3. The system according to claim 1 for interactively supplying educational content related to Japanese culture.

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