system

Abstract

We provide the system. [Solution] An information processing means that automatically generates an optimal curriculum based on the user's skill level and goals, A user interface means that presents a generated curriculum and processes interactive input from the user, A progress management system that analyzes user learning progress and behavior and provides real-time feedback, A question answering means that analyzes voice and text input to generate answers to user questions, 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 method for controlling a persona chatbot, which is 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 character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern information society, the lack of digital literacy has a great impact on social participation and work efficiency. In particular, individuals without technical knowledge and people living in different cultural circles have limited opportunities to appropriately learn how to handle information devices and beneficial ways to use the Internet. Against this background, there is a need for an efficient and effective learning support system that suits the skill level and learning goals of each individual. In particular, there is a lack of a mechanism for managing progress in real time and resolving doubts on the spot, and many users are struggling to acquire digital technology.

Means for Solving the Problems

[0005] This invention solves the above problems by providing an information processing system with an automatic curriculum generation function that is tailored to the user's skill level and goals. The generated curriculum is presented via a user interface, allowing the user to input information interactively and resolve questions on the spot. It also includes a progress management function that manages learning progress in real time and provides feedback as needed. Furthermore, by having means to accurately analyze voice and text input and provide question answers, the system facilitates the user's learning experience and supports the improvement of digital literacy. Through these means, it is possible to provide effective digital education that is compatible with multiple languages ​​and cultures.

[0006] "Skill level" is an indicator that shows the degree of an individual's technical or knowledge-based abilities.

[0007] A "curriculum" is a plan of learning activities and materials designed to achieve specific educational objectives.

[0008] "Information processing means" refers to a set of devices or processes used to collect, analyze, and transform data.

[0009] A "user interface" refers to the components, such as screen displays and input devices, that a user uses when interacting with a system.

[0010] A "progress management tool" is a function that tracks the user's learning progress and goal achievement, and provides appropriate guidance and feedback.

[0011] A "question answering system" is a system or function that receives inquiries from users and provides appropriate information or solutions.

[0012] "Multilingualism" refers to the ability or state of being able to communicate in multiple different languages.

[0013] "Multiculturalism" refers to the efforts and state of being that show consideration for people with different cultural backgrounds and respect the characteristics of each culture. [Brief explanation of the drawing]

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

Embodiments for Carrying Out the Invention

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

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

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

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

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

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

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

[0022] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0035] This invention is implemented as an individualized instruction system aimed at improving users' digital literacy. This system functions through the interaction of three parties: a server, a terminal, and a user.

[0036] First, the user accesses the system through a terminal and enters their login information. The terminal sends this information to the server, which retrieves the user's profile data from the database.

[0037] Next, the server automatically generates a curriculum using its AI generation function, based on the user's skill level and learning objectives. This curriculum includes selected learning materials and practice problems, and its difficulty level is adjusted as needed.

[0038] The generated curriculum is sent to the device and displayed in the user interface. Through this interface, the user learns from and interacts with the provided learning materials.

[0039] If a user encounters any unclear points or questions during their learning process, they can input them via voice or text through their device. The server receives this input, uses its question-answering function to generate appropriate answers, and sends them back to the device in real time.

[0040] Furthermore, the server utilizes progress management mechanisms to track users' learning behavior in real time. This allows it to evaluate users' understanding and achievement levels, and provide feedback and additional learning materials based on the results.

[0041] For example, when a user learns how to use new software, the server generates a beginner-friendly curriculum and displays a visual tutorial on the interface. If the user asks, "I don't know how to save," the server provides clear instructions via voice or text, allowing the user to perform the action immediately.

[0042] Thus, the embodiments for carrying out the present invention are adapted to individual learning needs, are user-friendly, and support effective acquisition of digital skills.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user launches the application on their device and enters their username and password on the login screen.

[0046] Step 2:

[0047] The terminal sends the entered authentication information to the server. The server retrieves the user profile from the database and performs authentication. If authentication is successful, the session is started.

[0048] Step 3:

[0049] The server automatically generates an appropriate learning curriculum using an AI algorithm based on the user's skill level and learning goals.

[0050] Step 4:

[0051] The server sends the generated curriculum to the terminal. The terminal displays this in its user interface, allowing the user to begin learning.

[0052] Step 5:

[0053] Users view curriculum-based learning materials and complete assignments. They can enter questions via voice or text if they encounter any difficulties during their learning.

[0054] Step 6:

[0055] The terminal receives user input and sends it to the server. The server analyzes the question and generates an answer using AI.

[0056] Step 7:

[0057] The server sends the generated answers back to the terminal. The terminal displays the answers to the user, supporting smooth learning.

[0058] Step 8:

[0059] The server tracks the user's learning progress using a progress management function and collects progress data in real time. It then generates feedback tailored to the user's level of understanding.

[0060] Step 9:

[0061] Users review the feedback provided, revise their learning content as needed, and prepare for the next session.

[0062] Step 10:

[0063] When a user finishes learning, they initiate a logout procedure on their device. The device sends a logout request to the server, and the server terminates the session.

[0064] (Example 1)

[0065] 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."

[0066] In today's digital society, there is a need to provide flexible and effective learning experiences tailored to the diverse abilities and goals of individual users. However, traditional education systems generally only offer uniform materials, making personalization to meet diverse user needs difficult. Furthermore, the provision of learning environments that take into account multiple languages ​​and cultural backgrounds is insufficient. It is necessary to solve these problems and realize learning support optimized for each individual.

[0067] 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.

[0068] In this invention, the server includes information processing means for automatically generating an optimal learning plan based on the user's abilities and goals; user output means for presenting the generated learning plan and processing interactive input from the user; and progress tracking means for analyzing the user's learning progress and behavior and providing real-time evaluation and improvement suggestions. This makes it possible to provide a personalized learning experience that meets the individual needs and goals of each user, and to realize educational support that is adaptable to users with multilingual and multicultural backgrounds.

[0069] "User capability" refers to the level of knowledge and skills an individual possesses.

[0070] "Goals" refer to the specific objectives of learning or skill improvement that the user is trying to achieve.

[0071] A "learning plan" refers to a set of learning guidelines and a curriculum that are dynamically generated based on the user's abilities and goals.

[0072] "Information processing means" refers to a function that analyzes digital data and automatically generates an optimal learning plan for the user using a generated AI model.

[0073] "User output means" refers to an interface function that presents the generated learning plan to the user and enables interaction with it.

[0074] "Progress tracking means" refers to a function that monitors the user's learning status in real time and evaluates their progress and level of understanding.

[0075] "Question and answer generation means" refers to a function that generates appropriate answers to user questions in both voice and text.

[0076] "Digital skills" refer to the ability to process information and solve problems using computers and the internet.

[0077] "Educational support tools" refer to auxiliary functions and resources that provide users with an effective learning experience.

[0078] "Multilingual support" refers to the ability to interact with users in multiple languages ​​and to provide support tailored to their respective cultural backgrounds.

[0079] "Profile information" refers to data that records a user's past learning history and current learning needs.

[0080] This invention is a digital skills enhancement system that addresses individual learning needs and functions through the mutual cooperation of a server, terminal, and user. When implementing this invention, appropriate hardware and software are used to process data and provide the user with an optimal learning experience.

[0081] The server accesses the database to retrieve profile information tailored to the user's abilities and goals, and performs advanced information processing. The generative AI model used here automatically generates a learning plan based on the user's profile. In this process, natural language processing models such as OpenAI's GPT series are used.

[0082] The device provides a user interface, allowing users to review generated learning plans and progress through their studies. Users can manage their learning progress and receive real-time feedback through the device. Furthermore, if users have questions, they can ask them via text or voice input and receive accurate answers from the server.

[0083] For example, when a user learns how to use new software, the server generates a beginner-friendly learning plan and displays a visual tutorial on the terminal. If the user enters a question such as, "How do I save a file with this software?", the server can provide specific steps to answer it.

[0084] As described above, the present invention is a system that utilizes input examples of prompt sentences generated by an AI model to provide flexible and effective educational support to individual users.

[0085] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0086] Step 1:

[0087] The user accesses the login screen via their device and enters their username and password. The device then sends this login information to the server. The server authenticates the user based on the received information and retrieves the user's profile data from the database. The user's profile information is then output and passed on to the next step.

[0088] Step 2:

[0089] The server uses the acquired profile data to analyze the user's abilities and goals. Based on this data, a generative AI model operates to automatically generate an appropriate learning plan. Specifically, it selects learning materials and practice problems according to the user's skill level and performs data calculations to adjust the difficulty level. As output, an optimized learning plan is generated and sent to the terminal.

[0090] Step 3:

[0091] The terminal provides input to display the received learning plan on the user interface. Through this interface, the user can monitor their learning progress and take specific actions to begin learning. The terminal provides output that tracks the user's progress in real time and stores data for reporting to the server.

[0092] Step 4:

[0093] If a user has questions during the learning process, they can use their device to input the question in voice or text format. The device then sends this user question to the server. The server analyzes the question and processes the data using a generative AI model to generate an appropriate answer. As output, the server sends the generated answer to the device for the user to receive.

[0094] Step 5:

[0095] The server receives input that allows for detailed analysis of the user's learning behavior using progress tracking mechanisms. This includes data such as the number of completed learning materials and the accuracy rate of answers. Based on this data, the server evaluates the user's level of understanding and performs data calculations to configure and provide additional learning materials and feedback as needed. As output, feedback and a new learning plan are generated and delivered to the user via the terminal.

[0096] (Application Example 1)

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

[0098] In modern society, acquiring digital skills is essential, but a challenge remains: effective learning environments tailored to individual users are not readily available. In particular, the lack of support that caters to individual progress and needs in home learning is a significant problem. Furthermore, acquiring digital skills, which often involve complex operations, highlights the need for instruction using natural language interaction with voice recognition.

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

[0100] In this invention, the server includes information processing means for automatically generating an optimal learning plan based on the user's skill level and goals, operation screen means for presenting the generated learning plan and processing interactive input from the user, and dialogue support means for enabling natural interaction with the user via a home robot and assisting in the improvement of digital skills. As a result, the user receives individually optimized learning support for digital skills and can effectively acquire skills even in a home environment.

[0101] "User skill level" is a measure that indicates the degree of proficiency and technical ability possessed by a user.

[0102] A "learning plan" is a combination of learning materials and activities designed to improve a user's skills.

[0103] An "information processing system" is a mechanism for receiving data, analyzing it, and generating output tailored to a specific purpose.

[0104] An "operation screen means" is a mechanism that provides an interface for users to interact with the system.

[0105] A "progress management tool" is a function that tracks and evaluates the user's learning activities in real time and provides feedback based on that.

[0106] A "question answering system" is a mechanism that analyzes user-submitted questions in both voice and text format and generates appropriate answers.

[0107] A "household robot" is an autonomous mechanical device used in a home environment that provides various forms of support through natural interaction with the user.

[0108] A "dialogue support system" is a mechanism that assists with voice and text-based communication with users, effectively supporting their learning.

[0109] A system implementing this invention functions through a series of processes including a user, a server, a terminal, and a home robot.

[0110] The server utilizes a generative AI model to generate an optimal learning plan based on the user's skill level and goals. The generated learning plan is sent from the server to the terminal and displayed on the operation screen. The terminal functions as a user interface, where the user progresses through the learning process and makes inputs as needed.

[0111] The home robot understands user questions through voice recognition and uses a generative AI model to answer them. This supports the user through natural dialogue. Specifically, if the robot asks a user, "I don't know the basic operations of image editing software," it can respond in an instructive and simple way, "Save it from the menu," thereby facilitating the user's learning process.

[0112] As a means of progress management, the server tracks the user's learning behavior in real time and records that behavior in a database. This allows the server to provide feedback and additional learning resources according to the user's progress.

[0113] Furthermore, the following example prompts can be used to effectively question the generative AI model:

[0114] "Please teach me the basic operations of image editing software for beginners."

[0115] "What kind of teaching materials would be effective as the next step?"

[0116] In this way, the present invention provides a system that effectively supports the improvement of digital skills in a home environment.

[0117] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0118] Step 1:

[0119] The server is accessed by the user through their terminal, and they enter their login information. Based on this input, the server retrieves the user's profile data from the database. This retrieved profile data includes the user's past learning history, skill level, and learning goals. This is used to establish the basis for the next learning plan.

[0120] Step 2:

[0121] The server uses a generative AI model to generate an appropriate learning plan based on the user's profile data. Using the profile and current learning goals as input, the AI ​​model selects the most suitable learning materials and exercises, and adjusts their difficulty level. As a result, a specific curriculum is output.

[0122] Step 3:

[0123] The terminal receives the learning plan sent from the server and displays it on the operation screen. The user can proceed with their learning while viewing this operation screen. The information provided here includes visual learning materials and interactive exercises.

[0124] Step 4:

[0125] If a user encounters any unclear points or questions during their learning process, they can input them via voice or text through their device. These questions are sent to a server, which uses a question-answering mechanism and a generative AI model to generate appropriate answers, which are then sent back to the device. This allows users to resolve their questions immediately.

[0126] Step 5:

[0127] Home robots use speech recognition to support learning through natural conversations with users. When a user asks a question, the robot sends prompts to an AI model based on the recognized speech input and obtains answers. Specific operations include processes such as "converting speech to text, sending this text to the AI ​​model, and returning the generated answer to the user in speech."

[0128] Step 6:

[0129] The server utilizes progress management tools to track users' learning progress in real time. It receives user learning behavior data as input and records it in a database. This allows for the provision of feedback and adjustments to learning materials for subsequent sessions. As a result, a personalized learning experience is provided for each user.

[0130] 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.

[0131] This invention is a learning system aimed at improving users' digital literacy, and by incorporating an emotion engine, it provides a flexible learning experience that responds to the user's emotional state. This system operates in cooperation with a server, terminal, and user.

[0132] First, the user accesses the system from their device, logs in, and enters their personal page. The device sends authentication information from the user to the server, which then uses that information to retrieve the user profile and initiate a session. The profile includes skill level, learning history, and set learning goals.

[0133] The server automatically generates a curriculum using AI based on profile data. This curriculum provides appropriate learning materials and challenges for the user and sends them to the device. The user interface displays this curriculum and provides an interactive learning environment.

[0134] Here, the emotion engine constantly monitors the user's input. When the user enters questions and answers via voice or text, the device sends this data to the server. The server's emotion engine analyzes the user's emotions from the input data and has a mechanism to detect changes in stress and motivation. For example, if a user has been studying for a long time, the emotion engine will detect signs of decreased concentration and suggest a short break as a mitigation measure.

[0135] Based on the emotion engine's analysis results, the server provides real-time feedback through the user interface. For example, if the emotion engine determines that the user is confused or overwhelmed by a difficult task, the server can provide hints or supplementary information.

[0136] In this manner, the system of the present invention adapts to each user's individual learning needs and emotional state, realizing a more effective and personalized learning experience. This promotes improvement in digital literacy while simultaneously maintaining motivation for learning.

[0137] The following describes the processing flow.

[0138] Step 1:

[0139] The user logs into the system using a terminal and enters their username and password.

[0140] Step 2:

[0141] The terminal sends the entered authentication information to the server. The server retrieves the corresponding user profile from the database, and if authentication is successful, starts a session.

[0142] Step 3:

[0143] The server automatically generates personalized learning curricula using generative AI based on the user's profile data. These curricula include learning materials and exercises tailored to the user's skill level and goals.

[0144] Step 4:

[0145] The server sends the generated curriculum to the terminal, which displays it in the user interface. The user then begins learning according to this curriculum.

[0146] Step 5:

[0147] The user enters questions via voice or text while learning. The device receives these and sends them to the server.

[0148] Step 6:

[0149] The server analyzes the received question and uses an emotion engine to analyze the user's emotional state. If the user is dissatisfied or confused, the emotion engine will detect it.

[0150] Step 7:

[0151] Based on the analysis results of the emotion engine, the server can generate appropriate answers to questions and can also provide encouraging messages and additional hints for the user.

[0152] Step 8:

[0153] The server sends the generated answers and feedback back to the terminal, which then presents them to the user through the user interface. The user reviews the provided information and continues learning.

[0154] Step 9:

[0155] The server uses progress management features to track users' learning progress. In particular, it evaluates users' stress levels and motivation, and adjusts the curriculum content if necessary.

[0156] Step 10:

[0157] When a user completes a learning session, they log out on their device, and the device sends this request to the server. The server then safely terminates the session.

[0158] (Example 2)

[0159] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0160] In today's learning environment, there is a demand for flexible and effective educational plans tailored to each user's skill level and individual learning goals. However, conventional systems have struggled to provide learning support that responds to users' emotional states and to offer individualized feedback in real time, limiting the improvement of learning efficiency. Therefore, there is a need for a system that provides a personalized learning experience that reflects users' emotional states and realizes effective digital education.

[0161] 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.

[0162] In this invention, the server includes data processing means for automatically generating an optimal educational plan based on the user's skill level and learning objectives; display means for presenting the generated educational plan and processing interactive input from the user; and sentiment analysis means for analyzing the user's emotional state and providing real-time adjustments to the learning pace and feedback accordingly. This enables a flexible and effective learning experience that meets the individual needs of each user.

[0163] A "user" refers to an individual or group that uses this system for learning.

[0164] "Skill level" refers to the degree of knowledge and skills a user already possesses, and serves as a benchmark for progressing through the learning process.

[0165] "Learning objectives" refer to the specific results or goals that users aim to achieve when using the system.

[0166] An "educational plan" refers to the arrangement and structure of learning content that is appropriately built based on the user's skill level and learning objectives.

[0167] "Data processing means" refers to functions for collecting and analyzing information about users to generate optimal educational plans.

[0168] "Display means" refers to a function that presents the generated educational plan to the user visually or audibly.

[0169] "Emotional state" refers to the psychological or emotional changes that a user exhibits during learning, and is a factor that influences the progress of their learning.

[0170] "Providing in real time" means responding immediately to users' learning processes and providing feedback and support.

[0171] "Emotional analysis tools" refer to functions that analyze user input data, evaluate their emotional state, and provide appropriate support for learning.

[0172] This invention is a learning system that incorporates sentiment analysis, aiming to improve users' digital literacy. In implementing this invention, the server, terminal, and user work together.

[0173] The server uses high-performance data processing equipment to generate educational plans based on user profile data stored in the database. Specifically, the server leverages a generative AI model to automatically create optimal educational plans tailored to the user's skill level and learning objectives. A generally available high-performance server platform is used for program processing.

[0174] The device functions as a user interface, displaying the generated educational plan to the user. This is achieved through an application running on a PC, tablet, or smartphone. The user provides voice and text feedback on the displayed plan, and this input data is sent to the server.

[0175] As users interact with the device and progress through the learning process according to the presented educational plan, they provide various inputs (questions, responses, etc.). These inputs are analyzed by the server's sentiment analysis system, and feedback is provided that is appropriately adjusted according to the user's emotional state. For example, if a user is facing a difficult task, the server provides appropriate hints and advice in real time.

[0176] As a concrete example, a prompt statement is written in the following format:

[0177] "When a person is studying for an extended period and their emotional engine detects signs of decreased concentration, what kind of break would be most effective to suggest?"

[0178] As described above, the present invention improves digital literacy by adapting to the individual learning needs and emotional states of users and providing a personalized learning experience.

[0179] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0180] Step 1:

[0181] The server handles the user login process. It receives login information sent from the terminal as input data, searches the database, and performs authentication. If authentication is successful, it retrieves the user's profile information and starts a session. The output is a session start success notification and profile data.

[0182] Step 2:

[0183] The server automatically generates educational plans based on user profiles using a generative AI model. Input data includes the user's skill level, past learning history, and learning goals. The AI ​​model analyzes this data and outputs the optimal educational plan. Specifically, the AI ​​model selects teaching materials and practice problems through an algorithm.

[0184] Step 3:

[0185] The terminal presents the user with the educational plan received from the server. The input is the educational plan data from the server. The terminal displays this data in a user interface and formats it in a way that is easy for the user to access. The output is a curriculum display as visual or auditory information. Specifically, it displays links to learning materials and practice problems on the screen.

[0186] Step 4:

[0187] Users progress through the learning process using a device, asking and answering questions via voice or text. Input is the user's dialogue based on the displayed curriculum. The device sends this input data to a server for sentiment analysis. Output is the transmission of input data to the server.

[0188] Step 5:

[0189] The server analyzes user input data using sentiment analysis tools. Input consists of voice and text data from the terminal. The sentiment analysis engine evaluates the user's emotional state and adjusts the learning environment if necessary. Output includes feedback and adjustment suggestions tailored to the emotional state. Specifically, if a decrease in concentration is detected, the server suggests a break.

[0190] Step 6:

[0191] The terminal receives feedback and adjustment suggestions sent back from the server and presents them to the user. The input is feedback data from the server. The terminal displays this information on its interface and prompts the user to take appropriate action. The output is feedback presentation as visual or auditory information. Specifically, hints and advice are displayed as pop-ups.

[0192] (Application Example 2)

[0193] 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".

[0194] In modern society, improving digital literacy is essential, but personalized learning environments that cater to individuals with diverse backgrounds remain insufficient. Furthermore, there is a need for real-time support that addresses the stress and motivational challenges that arise during learning. Traditional learning systems have struggled to recognize learners' emotional states and automatically provide appropriate feedback based on them.

[0195] 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.

[0196] In this invention, the server includes information processing means for automatically generating an optimal learning program based on the user's skill level and goals, user interface means for presenting the generated learning program and processing interactive input from the user, and adjustment means for automatically suggesting relaxation and entertainment content based on the user's emotional state. This enables learners to obtain an optimized learning experience that is tailored to their own learning progress and emotional state.

[0197] "Information processing means" refers to a device or software that has the function of automatically generating an optimal learning program based on the user's skill level and goals.

[0198] "User interface means" refers to a device or software that presents a generated learning program and provides an interactive display and operation environment for processing interactive input from the user.

[0199] A "progress management tool" is a device or software that analyzes the user's learning progress and behavior, provides real-time feedback, and further analyzes the user's emotional state to provide an adaptive learning experience.

[0200] A "question answering tool" is an algorithm or software that analyzes voice and text input and automatically generates answers to questions from the user.

[0201] "Adjustment means" refers to a device or software that has the function of automatically suggesting relaxation or entertainment content based on the user's emotional state.

[0202] To implement this invention, a server, terminal, and user work together to build a learning system. The server has information processing means that automatically generates an optimal learning program based on the user's skill level and goals using a generation AI model. The generated learning program is displayed on a user interface means via the terminal and accepts interactive input from the user.

[0203] Users access the system and begin learning through devices such as smartphones and tablets. The device collects the user's voice and text input and transmits it to the server. The server receives this data and analyzes the user's emotional state using an emotion engine. If the analysis determines that the user's concentration is low, the server automatically suggests relaxation content using adjustment mechanisms. For example, the server might create a suggestion such as, "Let's take a short break. How about listening to your favorite music to refresh yourself?" and send it to the device.

[0204] As a concrete example, the following is an example of a prompt: "Based on the user's past learning data and current emotional state, please suggest the next most suitable learning material." By sending this prompt to the generating AI model, it is possible to provide the user with an optimal learning experience.

[0205] This system utilizes programming languages ​​such as Python, and for sentiment analysis, it can use software such as IBM Watson® and Google® Cloud Natural Language API. Furthermore, OpenAI's GPT-3® can be used for the generative AI model. This allows users to receive a personalized learning experience tailored to their emotional state and learning progress.

[0206] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0207] Step 1:

[0208] The user accesses the learning system using a device and enters their login information. The device sends the user's authentication data to the server, which receives this data. Upon successful login, the server reads the user's profile information and verifies their skill level and past learning history.

[0209] Step 2:

[0210] The server processes information based on the user's skill level and set learning objectives, and automatically generates a curriculum using a generative AI model. This process analyzes the input profile data, selects the most suitable learning materials and activities, and structures them into a curriculum. As a result, curriculum data tailored to the user is generated.

[0211] Step 3:

[0212] The generated curriculum is sent from the server to the terminal's user interface. The terminal displays this curriculum to the user, providing an interactive learning environment. As the user works on assignments, they can provide feedback and questions via voice or text.

[0213] Step 4:

[0214] User input is sent from the terminal to the server, which uses an emotion engine to analyze the user's emotional state from the input data. Here, natural language processing and emotion analysis techniques are used to determine the user's stress level and whether their motivation for learning has decreased. The analysis results are then obtained as output.

[0215] Step 5:

[0216] Based on the analysis of the user's emotional state, the server uses adjustment mechanisms to generate relaxation content and additional learning hints as needed. For example, if a decrease in concentration is detected, the server might create a relaxation suggestion such as "Let's take a short break." This provides personalized feedback tailored to the user.

[0217] Step 6:

[0218] The generated suggestions and content are sent to the device and presented to the user through the user interface. Users can receive this feedback and use it in their next learning activity, enabling them to continue a learning experience tailored to their own pace and circumstances.

[0219] 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.

[0220] 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.

[0221] 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.

[0222] [Second Embodiment]

[0223] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0224] 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.

[0225] 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).

[0226] 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.

[0227] 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.

[0228] 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).

[0229] 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.

[0230] 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.

[0231] 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.

[0232] 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.

[0233] 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.

[0234] 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".

[0235] This invention is implemented as an individualized instruction system aimed at improving users' digital literacy. This system functions through the interaction of three parties: a server, a terminal, and a user.

[0236] First, the user accesses the system through a terminal and enters their login information. The terminal sends this information to the server, which retrieves the user's profile data from the database.

[0237] Next, the server automatically generates a curriculum using its AI generation function, based on the user's skill level and learning objectives. This curriculum includes selected learning materials and practice problems, and its difficulty level is adjusted as needed.

[0238] The generated curriculum is sent to the device and displayed in the user interface. Through this interface, the user learns from and interacts with the provided learning materials.

[0239] If a user encounters any unclear points or questions during their learning process, they can input them via voice or text through their device. The server receives this input, uses its question-answering function to generate appropriate answers, and sends them back to the device in real time.

[0240] Furthermore, the server utilizes progress management mechanisms to track users' learning behavior in real time. This allows it to evaluate users' understanding and achievement levels, and provide feedback and additional learning materials based on the results.

[0241] For example, when a user learns how to use new software, the server generates a beginner-friendly curriculum and displays a visual tutorial on the interface. If the user asks, "I don't know how to save," the server provides clear instructions via voice or text, allowing the user to perform the action immediately.

[0242] Thus, the embodiments for carrying out the present invention are adapted to individual learning needs, are user-friendly, and support effective acquisition of digital skills.

[0243] The following describes the processing flow.

[0244] Step 1:

[0245] The user launches the application on their device and enters their username and password on the login screen.

[0246] Step 2:

[0247] The terminal sends the entered authentication information to the server. The server retrieves the user profile from the database and performs authentication. If authentication is successful, the session is started.

[0248] Step 3:

[0249] The server automatically generates an appropriate learning curriculum using an AI algorithm based on the user's skill level and learning goals.

[0250] Step 4:

[0251] The server sends the generated curriculum to the terminal. The terminal displays this in its user interface, allowing the user to begin learning.

[0252] Step 5:

[0253] Users view curriculum-based learning materials and complete assignments. They can enter questions via voice or text if they encounter any difficulties during their learning.

[0254] Step 6:

[0255] The terminal receives user input and sends it to the server. The server analyzes the question and generates an answer using AI.

[0256] Step 7:

[0257] The server sends the generated answers back to the terminal. The terminal displays the answers to the user, supporting smooth learning.

[0258] Step 8:

[0259] The server tracks the user's learning progress using a progress management function and collects progress data in real time. It then generates feedback tailored to the user's level of understanding.

[0260] Step 9:

[0261] Users review the feedback provided, revise their learning content as needed, and prepare for the next session.

[0262] Step 10:

[0263] When a user finishes learning, they initiate a logout procedure on their device. The device sends a logout request to the server, and the server terminates the session.

[0264] (Example 1)

[0265] 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."

[0266] In today's digital society, there is a need to provide flexible and effective learning experiences tailored to the diverse abilities and goals of individual users. However, traditional education systems generally only offer uniform materials, making personalization to meet diverse user needs difficult. Furthermore, the provision of learning environments that take into account multiple languages ​​and cultural backgrounds is insufficient. It is necessary to solve these problems and realize learning support optimized for each individual.

[0267] 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.

[0268] In this invention, the server includes information processing means for automatically generating an optimal learning plan based on the user's abilities and goals; user output means for presenting the generated learning plan and processing interactive input from the user; and progress tracking means for analyzing the user's learning progress and behavior and providing real-time evaluation and improvement suggestions. This makes it possible to provide a personalized learning experience that meets the individual needs and goals of each user, and to realize educational support that is adaptable to users with multilingual and multicultural backgrounds.

[0269] "User capability" refers to the level of knowledge and skills an individual possesses.

[0270] "Goals" refer to the specific objectives of learning or skill improvement that the user is trying to achieve.

[0271] A "learning plan" refers to a set of learning guidelines and a curriculum that are dynamically generated based on the user's abilities and goals.

[0272] "Information processing means" refers to a function that analyzes digital data and automatically generates an optimal learning plan for the user using a generated AI model.

[0273] "User output means" refers to an interface function that presents the generated learning plan to the user and enables interaction with it.

[0274] "Progress tracking means" refers to a function that monitors the user's learning status in real time and evaluates their progress and level of understanding.

[0275] "Question and answer generation means" refers to a function that generates appropriate answers to user questions in both voice and text.

[0276] "Digital skills" refer to the ability to process information and solve problems using computers and the internet.

[0277] "Educational support tools" refer to auxiliary functions and resources that provide users with an effective learning experience.

[0278] "Multilingual support" refers to the ability to interact with users in multiple languages ​​and to provide support tailored to their respective cultural backgrounds.

[0279] "Profile information" refers to data that records a user's past learning history and current learning needs.

[0280] The present invention is a digital skills improvement system that caters to individual learning needs and functions through the mutual cooperation of a server, a terminal, and a user. When implementing the present invention, appropriate hardware and software are used to process data and provide an optimal learning experience for the user.

[0281] The server accesses a database to obtain profile information according to the user's capabilities and goals, and performs advanced information processing. The generative AI model used here automatically generates a learning plan based on the user's profile. In this process, a natural language processing model such as OpenAI's GPT series is used.

[0282] The terminal provides a user interface, enables the user to view the generated learning plan, and proceed with learning. The user can manage the progress of learning through the terminal and receive real-time feedback. Furthermore, when the user has questions, they can ask questions through text or voice input and obtain accurate answers from the server.

[0283] As a specific example, when a user is learning how to use new software, the server generates a learning plan for beginners and displays a visual tutorial on the terminal. When the user inputs a question such as "Please teach me how to save a file with this software", the server can provide specific procedures for it.

[0284] As described above, the present invention is a system that utilizes input examples of prompt texts using a generative AI model to achieve flexible and effective educational support for individual users.

[0285] The flow of specific processing in Example 1 will be described using FIG. 11.

[0286] Step 1:

[0287] The user accesses the login screen via their device and enters their username and password. The device then sends this login information to the server. The server authenticates the user based on the received information and retrieves the user's profile data from the database. The user's profile information is then output and passed on to the next step.

[0288] Step 2:

[0289] The server uses the acquired profile data to analyze the user's abilities and goals. Based on this data, a generative AI model operates to automatically generate an appropriate learning plan. Specifically, it selects learning materials and practice problems according to the user's skill level and performs data calculations to adjust the difficulty level. As output, an optimized learning plan is generated and sent to the terminal.

[0290] Step 3:

[0291] The terminal provides input to display the received learning plan on the user interface. Through this interface, the user can monitor their learning progress and take specific actions to begin learning. The terminal provides output that tracks the user's progress in real time and stores data for reporting to the server.

[0292] Step 4:

[0293] If a user has questions during the learning process, they can use their device to input the question in voice or text format. The device then sends this user question to the server. The server analyzes the question and processes the data using a generative AI model to generate an appropriate answer. As output, the server sends the generated answer to the device for the user to receive.

[0294] Step 5:

[0295] The server receives input that allows for detailed analysis of the user's learning behavior using progress tracking mechanisms. This includes data such as the number of completed learning materials and the accuracy rate of answers. Based on this data, the server evaluates the user's level of understanding and performs data calculations to configure and provide additional learning materials and feedback as needed. As output, feedback and a new learning plan are generated and delivered to the user via the terminal.

[0296] (Application Example 1)

[0297] 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 glasses 214 will be referred to as the "terminal."

[0298] In modern society, acquiring digital skills is essential, but a challenge remains: effective learning environments tailored to individual users are not readily available. In particular, the lack of support that caters to individual progress and needs in home learning is a significant problem. Furthermore, acquiring digital skills, which often involve complex operations, highlights the need for instruction using natural language interaction with voice recognition.

[0299] 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.

[0300] In this invention, the server includes information processing means for automatically generating an optimal learning plan based on the user's skill level and goals, operation screen means for presenting the generated learning plan and processing interactive input from the user, and dialogue support means for enabling natural interaction with the user via a home robot and assisting in the improvement of digital skills. As a result, the user receives individually optimized learning support for digital skills and can effectively acquire skills even in a home environment.

[0301] "User skill level" is a measure that indicates the degree of proficiency and technical ability possessed by a user.

[0302] A "learning plan" refers to a combination of a series of teaching materials and activities created for the purpose of improving the user's skills.

[0303] "Information processing means" refers to a mechanism for receiving, analyzing data, and generating an output according to a specific purpose.

[0304] "Operation screen means" refers to a mechanism for providing an interface for the user to interact with the system.

[0305] "Progress management means" refers to a function for tracking and evaluating the user's learning activities in real time and providing feedback based on that.

[0306] "Question and answer means" refers to a mechanism for analyzing questions from the user in voice and text and generating appropriate answers.

[0307] A "household robot" is an autonomous mechanical device used in a household environment that provides various supports through natural interaction with the user.

[0308] "Dialogue support means" refers to a mechanism for assisting communication with the user in voice and text and effectively supporting learning.

[0309] The system for implementing this invention functions through a series of processes including a user, a server, a terminal, and a household robot.

[0310] The server utilizes a generation AI model to generate an optimal learning plan based on the user's skill level and goals. The generated learning plan is sent from the server to the terminal and displayed on the operation screen. The terminal functions as a user interface where the user proceeds with learning and makes inputs as needed.

[0311] The home robot understands user questions through voice recognition and uses a generative AI model to answer them. This supports the user through natural dialogue. Specifically, if the robot asks a user, "I don't know the basic operations of image editing software," it can respond in an instructive and simple way, "Save it from the menu," thereby facilitating the user's learning process.

[0312] As a means of progress management, the server tracks the user's learning behavior in real time and records that behavior in a database. This allows the server to provide feedback and additional learning resources according to the user's progress.

[0313] Furthermore, the following example prompts can be used to effectively question the generative AI model:

[0314] "Please teach me the basic operations of image editing software for beginners."

[0315] "What kind of teaching materials would be effective as the next step?"

[0316] In this way, the present invention provides a system that effectively supports the improvement of digital skills in a home environment.

[0317] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0318] Step 1:

[0319] The server is accessed by the user through their terminal, and they enter their login information. Based on this input, the server retrieves the user's profile data from the database. This retrieved profile data includes the user's past learning history, skill level, and learning goals. This is used to establish the basis for the next learning plan.

[0320] Step 2:

[0321] The server uses a generative AI model to generate an appropriate learning plan based on the user's profile data. Using the profile and current learning goals as input, the AI ​​model selects the most suitable learning materials and exercises, and adjusts their difficulty level. As a result, a specific curriculum is output.

[0322] Step 3:

[0323] The terminal receives the learning plan sent from the server and displays it on the operation screen. The user can proceed with their learning while viewing this operation screen. The information provided here includes visual learning materials and interactive exercises.

[0324] Step 4:

[0325] If a user encounters any unclear points or questions during their learning process, they can input them via voice or text through their device. These questions are sent to a server, which uses a question-answering mechanism and a generative AI model to generate appropriate answers, which are then sent back to the device. This allows users to resolve their questions immediately.

[0326] Step 5:

[0327] Home robots use speech recognition to support learning through natural conversations with users. When a user asks a question, the robot sends prompts to an AI model based on the recognized speech input and obtains answers. Specific operations include processes such as "converting speech to text, sending this text to the AI ​​model, and returning the generated answer to the user in speech."

[0328] Step 6:

[0329] The server utilizes progress management tools to track users' learning progress in real time. It receives user learning behavior data as input and records it in a database. This allows for the provision of feedback and adjustments to learning materials for subsequent sessions. As a result, a personalized learning experience is provided for each user.

[0330] 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.

[0331] This invention is a learning system aimed at improving users' digital literacy, and by incorporating an emotion engine, it provides a flexible learning experience that responds to the user's emotional state. This system operates in cooperation with a server, terminal, and user.

[0332] First, the user accesses the system from their device, logs in, and enters their personal page. The device sends authentication information from the user to the server, which then uses that information to retrieve the user profile and initiate a session. The profile includes skill level, learning history, and set learning goals.

[0333] The server automatically generates a curriculum using AI based on profile data. This curriculum provides appropriate learning materials and challenges for the user and sends them to the device. The user interface displays this curriculum and provides an interactive learning environment.

[0334] Here, the emotion engine constantly monitors the user's input. When the user enters questions and answers via voice or text, the device sends this data to the server. The server's emotion engine analyzes the user's emotions from the input data and has a mechanism to detect changes in stress and motivation. For example, if a user has been studying for a long time, the emotion engine will detect signs of decreased concentration and suggest a short break as a mitigation measure.

[0335] Based on the emotion engine's analysis results, the server provides real-time feedback through the user interface. For example, if the emotion engine determines that the user is confused or overwhelmed by a difficult task, the server can provide hints or supplementary information.

[0336] In this manner, the system of the present invention adapts to each user's individual learning needs and emotional state, realizing a more effective and personalized learning experience. This promotes improvement in digital literacy while simultaneously maintaining motivation for learning.

[0337] The following describes the processing flow.

[0338] Step 1:

[0339] The user logs into the system using a terminal and enters their username and password.

[0340] Step 2:

[0341] The terminal sends the entered authentication information to the server. The server retrieves the corresponding user profile from the database, and if authentication is successful, starts a session.

[0342] Step 3:

[0343] The server automatically generates personalized learning curricula using generative AI based on the user's profile data. These curricula include learning materials and exercises tailored to the user's skill level and goals.

[0344] Step 4:

[0345] The server sends the generated curriculum to the terminal, which displays it in the user interface. The user then begins learning according to this curriculum.

[0346] Step 5:

[0347] The user enters questions via voice or text while learning. The device receives these and sends them to the server.

[0348] Step 6:

[0349] The server analyzes the received question and uses an emotion engine to analyze the user's emotional state. If the user is dissatisfied or confused, the emotion engine will detect it.

[0350] Step 7:

[0351] Based on the analysis results of the emotion engine, the server can generate appropriate answers to questions and can also provide encouraging messages and additional hints for the user.

[0352] Step 8:

[0353] The server sends the generated answers and feedback back to the terminal, which then presents them to the user through the user interface. The user reviews the provided information and continues learning.

[0354] Step 9:

[0355] The server uses progress management features to track users' learning progress. In particular, it evaluates users' stress levels and motivation, and adjusts the curriculum content if necessary.

[0356] Step 10:

[0357] When a user completes a learning session, they log out on their device, and the device sends this request to the server. The server then safely terminates the session.

[0358] (Example 2)

[0359] 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".

[0360] In today's learning environment, there is a demand for flexible and effective educational plans tailored to each user's skill level and individual learning goals. However, conventional systems have struggled to provide learning support that responds to users' emotional states and to offer individualized feedback in real time, limiting the improvement of learning efficiency. Therefore, there is a need for a system that provides a personalized learning experience that reflects users' emotional states and realizes effective digital education.

[0361] 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.

[0362] In this invention, the server includes data processing means for automatically generating an optimal educational plan based on the user's skill level and learning objectives; display means for presenting the generated educational plan and processing interactive input from the user; and sentiment analysis means for analyzing the user's emotional state and providing real-time adjustments to the learning pace and feedback accordingly. This enables a flexible and effective learning experience that meets the individual needs of each user.

[0363] A "user" refers to an individual or group that uses this system for learning.

[0364] "Skill level" refers to the degree of knowledge and skills a user already possesses, and serves as a benchmark for progressing through the learning process.

[0365] "Learning objectives" refer to the specific results or goals that users aim to achieve when using the system.

[0366] An "educational plan" refers to the arrangement and structure of learning content that is appropriately built based on the user's skill level and learning objectives.

[0367] "Data processing means" refers to functions for collecting and analyzing information about users to generate optimal educational plans.

[0368] "Display means" refers to a function that presents the generated educational plan to the user visually or audibly.

[0369] "Emotional state" refers to the psychological or emotional changes that a user exhibits during learning, and is a factor that influences the progress of their learning.

[0370] "Providing in real time" means responding immediately to users' learning processes and providing feedback and support.

[0371] "Emotional analysis tools" refer to functions that analyze user input data, evaluate their emotional state, and provide appropriate support for learning.

[0372] This invention is a learning system that incorporates sentiment analysis, aiming to improve users' digital literacy. In implementing this invention, the server, terminal, and user work together.

[0373] The server uses high-performance data processing equipment to generate educational plans based on user profile data stored in the database. Specifically, the server leverages a generative AI model to automatically create optimal educational plans tailored to the user's skill level and learning objectives. A generally available high-performance server platform is used for program processing.

[0374] The device functions as a user interface, displaying the generated educational plan to the user. This is achieved through an application running on a PC, tablet, or smartphone. The user provides voice and text feedback on the displayed plan, and this input data is sent to the server.

[0375] As users interact with the device and progress through the learning process according to the presented educational plan, they provide various inputs (questions, responses, etc.). These inputs are analyzed by the server's sentiment analysis system, and feedback is provided that is appropriately adjusted according to the user's emotional state. For example, if a user is facing a difficult task, the server provides appropriate hints and advice in real time.

[0376] As a concrete example, a prompt statement is written in the following format:

[0377] "When a person is studying for an extended period and their emotional engine detects signs of decreased concentration, what kind of break would be most effective to suggest?"

[0378] As described above, the present invention improves digital literacy by adapting to the individual learning needs and emotional states of users and providing a personalized learning experience.

[0379] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0380] Step 1:

[0381] The server handles the user login process. It receives login information sent from the terminal as input data, searches the database, and performs authentication. If authentication is successful, it retrieves the user's profile information and starts a session. The output is a session start success notification and profile data.

[0382] Step 2:

[0383] The server automatically generates educational plans based on user profiles using a generative AI model. Input data includes the user's skill level, past learning history, and learning goals. The AI ​​model analyzes this data and outputs the optimal educational plan. Specifically, the AI ​​model selects teaching materials and practice problems through an algorithm.

[0384] Step 3:

[0385] The terminal presents the user with the educational plan received from the server. The input is the educational plan data from the server. The terminal displays this data in a user interface and formats it in a way that is easy for the user to access. The output is a curriculum display as visual or auditory information. Specifically, it displays links to learning materials and practice problems on the screen.

[0386] Step 4:

[0387] Users progress through the learning process using a device, asking and answering questions via voice or text. Input is the user's dialogue based on the displayed curriculum. The device sends this input data to a server for sentiment analysis. Output is the transmission of input data to the server.

[0388] Step 5:

[0389] The server analyzes user input data using sentiment analysis tools. Input consists of voice and text data from the terminal. The sentiment analysis engine evaluates the user's emotional state and adjusts the learning environment if necessary. Output includes feedback and adjustment suggestions tailored to the emotional state. Specifically, if a decrease in concentration is detected, the server suggests a break.

[0390] Step 6:

[0391] The terminal receives feedback and adjustment suggestions sent back from the server and presents them to the user. The input is feedback data from the server. The terminal displays this information on its interface and prompts the user to take appropriate action. The output is feedback presentation as visual or auditory information. Specifically, hints and advice are displayed as pop-ups.

[0392] (Application Example 2)

[0393] 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."

[0394] In modern society, improving digital literacy is essential, but personalized learning environments that cater to individuals with diverse backgrounds remain insufficient. Furthermore, there is a need for real-time support that addresses the stress and motivational challenges that arise during learning. Traditional learning systems have struggled to recognize learners' emotional states and automatically provide appropriate feedback based on them.

[0395] 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.

[0396] In this invention, the server includes information processing means for automatically generating an optimal learning program based on the user's skill level and goals, user interface means for presenting the generated learning program and processing interactive input from the user, and adjustment means for automatically suggesting relaxation and entertainment content based on the user's emotional state. This enables learners to obtain an optimized learning experience that is tailored to their own learning progress and emotional state.

[0397] "Information processing means" refers to a device or software that has the function of automatically generating an optimal learning program based on the user's skill level and goals.

[0398] "User interface means" refers to a device or software that presents a generated learning program and provides an interactive display and operation environment for processing interactive input from the user.

[0399] A "progress management tool" is a device or software that analyzes the user's learning progress and behavior, provides real-time feedback, and further analyzes the user's emotional state to provide an adaptive learning experience.

[0400] A "question answering tool" is an algorithm or software that analyzes voice and text input and automatically generates answers to questions from the user.

[0401] "Adjustment means" refers to a device or software that has the function of automatically suggesting relaxation or entertainment content based on the user's emotional state.

[0402] To implement this invention, a server, terminal, and user work together to build a learning system. The server has information processing means that automatically generates an optimal learning program based on the user's skill level and goals using a generation AI model. The generated learning program is displayed on a user interface means via the terminal and accepts interactive input from the user.

[0403] Users access the system and begin learning through devices such as smartphones and tablets. The device collects the user's voice and text input and transmits it to the server. The server receives this data and analyzes the user's emotional state using an emotion engine. If the analysis determines that the user's concentration is low, the server automatically suggests relaxation content using adjustment mechanisms. For example, the server might create a suggestion such as, "Let's take a short break. How about listening to your favorite music to refresh yourself?" and send it to the device.

[0404] As a concrete example, the following is an example of a prompt: "Based on the user's past learning data and current emotional state, please suggest the next most suitable learning material." By sending this prompt to the generating AI model, it is possible to provide the user with an optimal learning experience.

[0405] This system utilizes programming languages ​​such as Python for its construction, and software like IBM Watson and Google Cloud Natural Language API can be used for sentiment analysis. Furthermore, OpenAI's GPT-3 can be leveraged for the generative AI model. This allows users to receive a personalized learning experience tailored to their emotional state and learning progress.

[0406] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0407] Step 1:

[0408] The user accesses the learning system using a device and enters their login information. The device sends the user's authentication data to the server, which receives this data. Upon successful login, the server reads the user's profile information and verifies their skill level and past learning history.

[0409] Step 2:

[0410] The server processes information based on the user's skill level and set learning objectives, and automatically generates a curriculum using a generative AI model. This process analyzes the input profile data, selects the most suitable learning materials and activities, and structures them into a curriculum. As a result, curriculum data tailored to the user is generated.

[0411] Step 3:

[0412] The generated curriculum is sent from the server to the terminal's user interface. The terminal displays this curriculum to the user, providing an interactive learning environment. As the user works on assignments, they can provide feedback and questions via voice or text.

[0413] Step 4:

[0414] User input is sent from the terminal to the server, which uses an emotion engine to analyze the user's emotional state from the input data. Here, natural language processing and emotion analysis techniques are used to determine the user's stress level and whether their motivation for learning has decreased. The analysis results are then obtained as output.

[0415] Step 5:

[0416] Based on the analysis of the user's emotional state, the server uses adjustment mechanisms to generate relaxation content and additional learning hints as needed. For example, if a decrease in concentration is detected, the server might create a relaxation suggestion such as "Let's take a short break." This provides personalized feedback tailored to the user.

[0417] Step 6:

[0418] The generated suggestions and content are sent to the device and presented to the user through the user interface. Users can receive this feedback and use it in their next learning activity, enabling them to continue a learning experience tailored to their own pace and circumstances.

[0419] 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.

[0420] 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.

[0421] 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.

[0422] [Third Embodiment]

[0423] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0424] 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.

[0425] 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).

[0426] 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.

[0427] 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.

[0428] 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).

[0429] 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.

[0430] 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.

[0431] 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.

[0432] 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.

[0433] 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.

[0434] 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".

[0435] This invention is implemented as an individualized instruction system aimed at improving users' digital literacy. This system functions through the interaction of three parties: a server, a terminal, and a user.

[0436] First, the user accesses the system through a terminal and enters their login information. The terminal sends this information to the server, which retrieves the user's profile data from the database.

[0437] Next, the server automatically generates a curriculum using its AI generation function, based on the user's skill level and learning objectives. This curriculum includes selected learning materials and practice problems, and its difficulty level is adjusted as needed.

[0438] The generated curriculum is sent to the device and displayed in the user interface. Through this interface, the user learns from and interacts with the provided learning materials.

[0439] If a user encounters any unclear points or questions during their learning process, they can input them via voice or text through their device. The server receives this input, uses its question-answering function to generate appropriate answers, and sends them back to the device in real time.

[0440] Furthermore, the server utilizes progress management mechanisms to track users' learning behavior in real time. This allows it to evaluate users' understanding and achievement levels, and provide feedback and additional learning materials based on the results.

[0441] For example, when a user learns how to use new software, the server generates a beginner-friendly curriculum and displays a visual tutorial on the interface. If the user asks, "I don't know how to save," the server provides clear instructions via voice or text, allowing the user to perform the action immediately.

[0442] Thus, the embodiments for carrying out the present invention are adapted to individual learning needs, are user-friendly, and support effective acquisition of digital skills.

[0443] The following describes the processing flow.

[0444] Step 1:

[0445] The user launches the application on their device and enters their username and password on the login screen.

[0446] Step 2:

[0447] The terminal sends the entered authentication information to the server. The server retrieves the user profile from the database and performs authentication. If authentication is successful, the session is started.

[0448] Step 3:

[0449] The server automatically generates an appropriate learning curriculum using an AI algorithm based on the user's skill level and learning goals.

[0450] Step 4:

[0451] The server sends the generated curriculum to the terminal. The terminal displays this in its user interface, allowing the user to begin learning.

[0452] Step 5:

[0453] Users view curriculum-based learning materials and complete assignments. They can enter questions via voice or text if they encounter any difficulties during their learning.

[0454] Step 6:

[0455] The terminal receives user input and sends it to the server. The server analyzes the question and generates an answer using AI.

[0456] Step 7:

[0457] The server sends the generated answers back to the terminal. The terminal displays the answers to the user, supporting smooth learning.

[0458] Step 8:

[0459] The server tracks the user's learning progress using a progress management function and collects progress data in real time. It then generates feedback tailored to the user's level of understanding.

[0460] Step 9:

[0461] Users review the feedback provided, revise their learning content as needed, and prepare for the next session.

[0462] Step 10:

[0463] When a user finishes learning, they initiate a logout procedure on their device. The device sends a logout request to the server, and the server terminates the session.

[0464] (Example 1)

[0465] 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."

[0466] In today's digital society, there is a need to provide flexible and effective learning experiences tailored to the diverse abilities and goals of individual users. However, traditional education systems generally only offer uniform materials, making personalization to meet diverse user needs difficult. Furthermore, the provision of learning environments that take into account multiple languages ​​and cultural backgrounds is insufficient. It is necessary to solve these problems and realize learning support optimized for each individual.

[0467] 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.

[0468] In this invention, the server includes information processing means for automatically generating an optimal learning plan based on the user's abilities and goals; user output means for presenting the generated learning plan and processing interactive input from the user; and progress tracking means for analyzing the user's learning progress and behavior and providing real-time evaluation and improvement suggestions. This makes it possible to provide a personalized learning experience that meets the individual needs and goals of each user, and to realize educational support that is adaptable to users with multilingual and multicultural backgrounds.

[0469] "User capability" refers to the level of knowledge and skills an individual possesses.

[0470] "Goals" refer to the specific objectives of learning or skill improvement that the user is trying to achieve.

[0471] A "learning plan" refers to a set of learning guidelines and a curriculum that are dynamically generated based on the user's abilities and goals.

[0472] "Information processing means" refers to a function that analyzes digital data and automatically generates an optimal learning plan for the user using a generated AI model.

[0473] "User output means" refers to an interface function that presents the generated learning plan to the user and enables interaction with it.

[0474] "Progress tracking means" refers to a function that monitors the user's learning status in real time and evaluates their progress and level of understanding.

[0475] "Question and answer generation means" refers to a function that generates appropriate answers to user questions in both voice and text.

[0476] "Digital skills" refer to the ability to process information and solve problems using computers and the internet.

[0477] "Educational support tools" refer to auxiliary functions and resources that provide users with an effective learning experience.

[0478] "Multilingual support" refers to the ability to interact with users in multiple languages ​​and to provide support tailored to their respective cultural backgrounds.

[0479] "Profile information" refers to data that records a user's past learning history and current learning needs.

[0480] This invention is a digital skills enhancement system that addresses individual learning needs and functions through the mutual cooperation of a server, terminal, and user. When implementing this invention, appropriate hardware and software are used to process data and provide the user with an optimal learning experience.

[0481] The server accesses the database to retrieve profile information tailored to the user's abilities and goals, and performs advanced information processing. The generative AI model used here automatically generates a learning plan based on the user's profile. In this process, natural language processing models such as OpenAI's GPT series are used.

[0482] The device provides a user interface, allowing users to review generated learning plans and progress through their studies. Users can manage their learning progress and receive real-time feedback through the device. Furthermore, if users have questions, they can ask them via text or voice input and receive accurate answers from the server.

[0483] For example, when a user learns how to use new software, the server generates a beginner-friendly learning plan and displays a visual tutorial on the terminal. If the user enters a question such as, "How do I save a file with this software?", the server can provide specific steps to answer it.

[0484] As described above, the present invention is a system that utilizes input examples of prompt sentences generated by an AI model to provide flexible and effective educational support to individual users.

[0485] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0486] Step 1:

[0487] The user accesses the login screen via their device and enters their username and password. The device then sends this login information to the server. The server authenticates the user based on the received information and retrieves the user's profile data from the database. The user's profile information is then output and passed on to the next step.

[0488] Step 2:

[0489] The server uses the acquired profile data to analyze the user's abilities and goals. Based on this data, a generative AI model operates to automatically generate an appropriate learning plan. Specifically, it selects learning materials and practice problems according to the user's skill level and performs data calculations to adjust the difficulty level. As output, an optimized learning plan is generated and sent to the terminal.

[0490] Step 3:

[0491] The terminal provides input to display the received learning plan on the user interface. Through this interface, the user can monitor their learning progress and take specific actions to begin learning. The terminal provides output that tracks the user's progress in real time and stores data for reporting to the server.

[0492] Step 4:

[0493] If a user has questions during the learning process, they can use their device to input the question in voice or text format. The device then sends this user question to the server. The server analyzes the question and processes the data using a generative AI model to generate an appropriate answer. As output, the server sends the generated answer to the device for the user to receive.

[0494] Step 5:

[0495] The server receives input that allows for detailed analysis of the user's learning behavior using progress tracking mechanisms. This includes data such as the number of completed learning materials and the accuracy rate of answers. Based on this data, the server evaluates the user's level of understanding and performs data calculations to configure and provide additional learning materials and feedback as needed. As output, feedback and a new learning plan are generated and delivered to the user via the terminal.

[0496] (Application Example 1)

[0497] 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."

[0498] In modern society, acquiring digital skills is essential, but a challenge remains: effective learning environments tailored to individual users are not readily available. In particular, the lack of support that caters to individual progress and needs in home learning is a significant problem. Furthermore, acquiring digital skills, which often involve complex operations, highlights the need for instruction using natural language interaction with voice recognition.

[0499] 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.

[0500] In this invention, the server includes information processing means for automatically generating an optimal learning plan based on the user's skill level and goals, operation screen means for presenting the generated learning plan and processing interactive input from the user, and dialogue support means for enabling natural interaction with the user via a home robot and assisting in the improvement of digital skills. As a result, the user receives individually optimized learning support for digital skills and can effectively acquire skills even in a home environment.

[0501] "User skill level" is a measure that indicates the degree of proficiency and technical ability possessed by a user.

[0502] A "learning plan" is a combination of learning materials and activities designed to improve a user's skills.

[0503] An "information processing system" is a mechanism for receiving data, analyzing it, and generating output tailored to a specific purpose.

[0504] An "operation screen means" is a mechanism that provides an interface for users to interact with the system.

[0505] A "progress management tool" is a function that tracks and evaluates the user's learning activities in real time and provides feedback based on that.

[0506] A "question answering system" is a mechanism that analyzes user-submitted questions in both voice and text format and generates appropriate answers.

[0507] A "household robot" is an autonomous mechanical device used in a home environment that provides various forms of support through natural interaction with the user.

[0508] A "dialogue support system" is a mechanism that assists with voice and text-based communication with users, effectively supporting their learning.

[0509] A system implementing this invention functions through a series of processes including a user, a server, a terminal, and a home robot.

[0510] The server utilizes a generative AI model to generate an optimal learning plan based on the user's skill level and goals. The generated learning plan is sent from the server to the terminal and displayed on the operation screen. The terminal functions as a user interface, where the user progresses through the learning process and makes inputs as needed.

[0511] The home robot understands user questions through voice recognition and uses a generative AI model to answer them. This supports the user through natural dialogue. Specifically, if the robot asks a user, "I don't know the basic operations of image editing software," it can respond in an instructive and simple way, "Save it from the menu," thereby facilitating the user's learning process.

[0512] As a means of progress management, the server tracks the user's learning behavior in real time and records that behavior in a database. This allows the server to provide feedback and additional learning resources according to the user's progress.

[0513] Furthermore, the following example prompts can be used to effectively question the generative AI model:

[0514] "Please teach me the basic operations of image editing software for beginners."

[0515] "What kind of teaching materials would be effective as the next step?"

[0516] In this way, the present invention provides a system that effectively supports the improvement of digital skills in a home environment.

[0517] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0518] Step 1:

[0519] The server is accessed by the user through their terminal, and they enter their login information. Based on this input, the server retrieves the user's profile data from the database. This retrieved profile data includes the user's past learning history, skill level, and learning goals. This is used to establish the basis for the next learning plan.

[0520] Step 2:

[0521] The server uses a generative AI model to generate an appropriate learning plan based on the user's profile data. Using the profile and current learning goals as input, the AI ​​model selects the most suitable learning materials and exercises, and adjusts their difficulty level. As a result, a specific curriculum is output.

[0522] Step 3:

[0523] The terminal receives the learning plan sent from the server and displays it on the operation screen. The user can proceed with their learning while viewing this operation screen. The information provided here includes visual learning materials and interactive exercises.

[0524] Step 4:

[0525] If a user encounters any unclear points or questions during their learning process, they can input them via voice or text through their device. These questions are sent to a server, which uses a question-answering mechanism and a generative AI model to generate appropriate answers, which are then sent back to the device. This allows users to resolve their questions immediately.

[0526] Step 5:

[0527] Home robots use speech recognition to support learning through natural conversations with users. When a user asks a question, the robot sends prompts to an AI model based on the recognized speech input and obtains answers. Specific operations include processes such as "converting speech to text, sending this text to the AI ​​model, and returning the generated answer to the user in speech."

[0528] Step 6:

[0529] The server utilizes progress management tools to track users' learning progress in real time. It receives user learning behavior data as input and records it in a database. This allows for the provision of feedback and adjustments to learning materials for subsequent sessions. As a result, a personalized learning experience is provided for each user.

[0530] 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.

[0531] This invention is a learning system aimed at improving users' digital literacy, and by incorporating an emotion engine, it provides a flexible learning experience that responds to the user's emotional state. This system operates in cooperation with a server, terminal, and user.

[0532] First, the user accesses the system from their device, logs in, and enters their personal page. The device sends authentication information from the user to the server, which then uses that information to retrieve the user profile and initiate a session. The profile includes skill level, learning history, and set learning goals.

[0533] The server automatically generates a curriculum using AI based on profile data. This curriculum provides appropriate learning materials and challenges for the user and sends them to the device. The user interface displays this curriculum and provides an interactive learning environment.

[0534] Here, the emotion engine constantly monitors the user's input. When the user enters questions and answers via voice or text, the device sends this data to the server. The server's emotion engine analyzes the user's emotions from the input data and has a mechanism to detect changes in stress and motivation. For example, if a user has been studying for a long time, the emotion engine will detect signs of decreased concentration and suggest a short break as a mitigation measure.

[0535] Based on the emotion engine's analysis results, the server provides real-time feedback through the user interface. For example, if the emotion engine determines that the user is confused or overwhelmed by a difficult task, the server can provide hints or supplementary information.

[0536] In this manner, the system of the present invention adapts to each user's individual learning needs and emotional state, realizing a more effective and personalized learning experience. This promotes improvement in digital literacy while simultaneously maintaining motivation for learning.

[0537] The following describes the processing flow.

[0538] Step 1:

[0539] The user logs into the system using a terminal and enters their username and password.

[0540] Step 2:

[0541] The terminal sends the entered authentication information to the server. The server retrieves the corresponding user profile from the database, and if authentication is successful, starts a session.

[0542] Step 3:

[0543] The server automatically generates personalized learning curricula using generative AI based on the user's profile data. These curricula include learning materials and exercises tailored to the user's skill level and goals.

[0544] Step 4:

[0545] The server sends the generated curriculum to the terminal, which displays it in the user interface. The user then begins learning according to this curriculum.

[0546] Step 5:

[0547] The user enters questions via voice or text while learning. The device receives these and sends them to the server.

[0548] Step 6:

[0549] The server analyzes the received question and uses an emotion engine to analyze the user's emotional state. If the user is dissatisfied or confused, the emotion engine will detect it.

[0550] Step 7:

[0551] Based on the analysis results of the emotion engine, the server can generate appropriate answers to questions and can also provide encouraging messages and additional hints for the user.

[0552] Step 8:

[0553] The server sends the generated answers and feedback back to the terminal, which then presents them to the user through the user interface. The user reviews the provided information and continues learning.

[0554] Step 9:

[0555] The server uses progress management features to track users' learning progress. In particular, it evaluates users' stress levels and motivation, and adjusts the curriculum content if necessary.

[0556] Step 10:

[0557] When a user completes a learning session, they log out on their device, and the device sends this request to the server. The server then safely terminates the session.

[0558] (Example 2)

[0559] 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."

[0560] In today's learning environment, there is a demand for flexible and effective educational plans tailored to each user's skill level and individual learning goals. However, conventional systems have struggled to provide learning support that responds to users' emotional states and to offer individualized feedback in real time, limiting the improvement of learning efficiency. Therefore, there is a need for a system that provides a personalized learning experience that reflects users' emotional states and realizes effective digital education.

[0561] 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.

[0562] In this invention, the server includes data processing means for automatically generating an optimal educational plan based on the user's skill level and learning objectives; display means for presenting the generated educational plan and processing interactive input from the user; and sentiment analysis means for analyzing the user's emotional state and providing real-time adjustments to the learning pace and feedback accordingly. This enables a flexible and effective learning experience that meets the individual needs of each user.

[0563] A "user" refers to an individual or group that uses this system for learning.

[0564] "Skill level" refers to the degree of knowledge and skills a user already possesses, and serves as a benchmark for progressing through the learning process.

[0565] "Learning objectives" refer to the specific results or goals that users aim to achieve when using the system.

[0566] An "educational plan" refers to the arrangement and structure of learning content that is appropriately built based on the user's skill level and learning objectives.

[0567] "Data processing means" refers to functions for collecting and analyzing information about users to generate optimal educational plans.

[0568] "Display means" refers to a function that presents the generated educational plan to the user visually or audibly.

[0569] "Emotional state" refers to the psychological or emotional changes that a user exhibits during learning, and is a factor that influences the progress of their learning.

[0570] "Providing in real time" means responding immediately to users' learning processes and providing feedback and support.

[0571] "Emotional analysis tools" refer to functions that analyze user input data, evaluate their emotional state, and provide appropriate support for learning.

[0572] This invention is a learning system that incorporates sentiment analysis, aiming to improve users' digital literacy. In implementing this invention, the server, terminal, and user work together.

[0573] The server uses high-performance data processing equipment to generate educational plans based on user profile data stored in the database. Specifically, the server leverages a generative AI model to automatically create optimal educational plans tailored to the user's skill level and learning objectives. A generally available high-performance server platform is used for program processing.

[0574] The device functions as a user interface, displaying the generated educational plan to the user. This is achieved through an application running on a PC, tablet, or smartphone. The user provides voice and text feedback on the displayed plan, and this input data is sent to the server.

[0575] As users interact with the device and progress through the learning process according to the presented educational plan, they provide various inputs (questions, responses, etc.). These inputs are analyzed by the server's sentiment analysis system, and feedback is provided that is appropriately adjusted according to the user's emotional state. For example, if a user is facing a difficult task, the server provides appropriate hints and advice in real time.

[0576] As a concrete example, a prompt statement is written in the following format:

[0577] "When a person is studying for an extended period and their emotional engine detects signs of decreased concentration, what kind of break would be most effective to suggest?"

[0578] As described above, the present invention improves digital literacy by adapting to the individual learning needs and emotional states of users and providing a personalized learning experience.

[0579] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0580] Step 1:

[0581] The server handles the user login process. It receives login information sent from the terminal as input data, searches the database, and performs authentication. If authentication is successful, it retrieves the user's profile information and starts a session. The output is a session start success notification and profile data.

[0582] Step 2:

[0583] The server automatically generates educational plans based on user profiles using a generative AI model. Input data includes the user's skill level, past learning history, and learning goals. The AI ​​model analyzes this data and outputs the optimal educational plan. Specifically, the AI ​​model selects teaching materials and practice problems through an algorithm.

[0584] Step 3:

[0585] The terminal presents the user with the educational plan received from the server. The input is the educational plan data from the server. The terminal displays this data in a user interface and formats it in a way that is easy for the user to access. The output is a curriculum display as visual or auditory information. Specifically, it displays links to learning materials and practice problems on the screen.

[0586] Step 4:

[0587] Users progress through the learning process using a device, asking and answering questions via voice or text. Input is the user's dialogue based on the displayed curriculum. The device sends this input data to a server for sentiment analysis. Output is the transmission of input data to the server.

[0588] Step 5:

[0589] The server analyzes user input data using sentiment analysis tools. Input consists of voice and text data from the terminal. The sentiment analysis engine evaluates the user's emotional state and adjusts the learning environment if necessary. Output includes feedback and adjustment suggestions tailored to the emotional state. Specifically, if a decrease in concentration is detected, the server suggests a break.

[0590] Step 6:

[0591] The terminal receives feedback and adjustment suggestions sent back from the server and presents them to the user. The input is feedback data from the server. The terminal displays this information on its interface and prompts the user to take appropriate action. The output is feedback presentation as visual or auditory information. Specifically, hints and advice are displayed as pop-ups.

[0592] (Application Example 2)

[0593] 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."

[0594] In modern society, improving digital literacy is essential, but personalized learning environments that cater to individuals with diverse backgrounds remain insufficient. Furthermore, there is a need for real-time support that addresses the stress and motivational challenges that arise during learning. Traditional learning systems have struggled to recognize learners' emotional states and automatically provide appropriate feedback based on them.

[0595] 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.

[0596] In this invention, the server includes information processing means for automatically generating an optimal learning program based on the user's skill level and goals, user interface means for presenting the generated learning program and processing interactive input from the user, and adjustment means for automatically suggesting relaxation and entertainment content based on the user's emotional state. This enables learners to obtain an optimized learning experience that is tailored to their own learning progress and emotional state.

[0597] "Information processing means" refers to a device or software that has the function of automatically generating an optimal learning program based on the user's skill level and goals.

[0598] "User interface means" refers to a device or software that presents a generated learning program and provides an interactive display and operation environment for processing interactive input from the user.

[0599] A "progress management tool" is a device or software that analyzes the user's learning progress and behavior, provides real-time feedback, and further analyzes the user's emotional state to provide an adaptive learning experience.

[0600] A "question answering tool" is an algorithm or software that analyzes voice and text input and automatically generates answers to questions from the user.

[0601] "Adjustment means" refers to a device or software that has the function of automatically suggesting relaxation or entertainment content based on the user's emotional state.

[0602] To implement this invention, a server, terminal, and user work together to build a learning system. The server has information processing means that automatically generates an optimal learning program based on the user's skill level and goals using a generation AI model. The generated learning program is displayed on a user interface means via the terminal and accepts interactive input from the user.

[0603] Users access the system and begin learning through devices such as smartphones and tablets. The device collects the user's voice and text input and transmits it to the server. The server receives this data and analyzes the user's emotional state using an emotion engine. If the analysis determines that the user's concentration is low, the server automatically suggests relaxation content using adjustment mechanisms. For example, the server might create a suggestion such as, "Let's take a short break. How about listening to your favorite music to refresh yourself?" and send it to the device.

[0604] As a concrete example, the following is an example of a prompt: "Based on the user's past learning data and current emotional state, please suggest the next most suitable learning material." By sending this prompt to the generating AI model, it is possible to provide the user with an optimal learning experience.

[0605] This system utilizes programming languages ​​such as Python for its construction, and software like IBM Watson and Google Cloud Natural Language API can be used for sentiment analysis. Furthermore, OpenAI's GPT-3 can be leveraged for the generative AI model. This allows users to receive a personalized learning experience tailored to their emotional state and learning progress.

[0606] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0607] Step 1:

[0608] The user accesses the learning system using a device and enters their login information. The device sends the user's authentication data to the server, which receives this data. Upon successful login, the server reads the user's profile information and verifies their skill level and past learning history.

[0609] Step 2:

[0610] The server processes information based on the user's skill level and set learning objectives, and automatically generates a curriculum using a generative AI model. This process analyzes the input profile data, selects the most suitable learning materials and activities, and structures them into a curriculum. As a result, curriculum data tailored to the user is generated.

[0611] Step 3:

[0612] The generated curriculum is sent from the server to the terminal's user interface. The terminal displays this curriculum to the user, providing an interactive learning environment. As the user works on assignments, they can provide feedback and questions via voice or text.

[0613] Step 4:

[0614] User input is sent from the terminal to the server, which uses an emotion engine to analyze the user's emotional state from the input data. Here, natural language processing and emotion analysis techniques are used to determine the user's stress level and whether their motivation for learning has decreased. The analysis results are then obtained as output.

[0615] Step 5:

[0616] Based on the analysis of the user's emotional state, the server uses adjustment mechanisms to generate relaxation content and additional learning hints as needed. For example, if a decrease in concentration is detected, the server might create a relaxation suggestion such as "Let's take a short break." This provides personalized feedback tailored to the user.

[0617] Step 6:

[0618] The generated suggestions and content are sent to the device and presented to the user through the user interface. Users can receive this feedback and use it in their next learning activity, enabling them to continue a learning experience tailored to their own pace and circumstances.

[0619] 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.

[0620] 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.

[0621] 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.

[0622] [Fourth Embodiment]

[0623] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0624] 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.

[0625] 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).

[0626] 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.

[0627] 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.

[0628] 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).

[0629] 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.

[0630] 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.

[0631] 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.

[0632] 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.

[0633] 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.

[0634] 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.

[0635] 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".

[0636] This invention is implemented as an individualized instruction system aimed at improving users' digital literacy. This system functions through the interaction of three parties: a server, a terminal, and a user.

[0637] First, the user accesses the system through a terminal and enters their login information. The terminal sends this information to the server, which retrieves the user's profile data from the database.

[0638] Next, the server automatically generates a curriculum using its AI generation function, based on the user's skill level and learning objectives. This curriculum includes selected learning materials and practice problems, and its difficulty level is adjusted as needed.

[0639] The generated curriculum is sent to the device and displayed in the user interface. Through this interface, the user learns from and interacts with the provided learning materials.

[0640] If a user encounters any unclear points or questions during their learning process, they can input them via voice or text through their device. The server receives this input, uses its question-answering function to generate appropriate answers, and sends them back to the device in real time.

[0641] Furthermore, the server utilizes progress management mechanisms to track users' learning behavior in real time. This allows it to evaluate users' understanding and achievement levels, and provide feedback and additional learning materials based on the results.

[0642] For example, when a user learns how to use new software, the server generates a beginner-friendly curriculum and displays a visual tutorial on the interface. If the user asks, "I don't know how to save," the server provides clear instructions via voice or text, allowing the user to perform the action immediately.

[0643] Thus, the embodiments for carrying out the present invention are adapted to individual learning needs, are user-friendly, and support effective acquisition of digital skills.

[0644] The following describes the processing flow.

[0645] Step 1:

[0646] The user launches the application on their device and enters their username and password on the login screen.

[0647] Step 2:

[0648] The terminal sends the entered authentication information to the server. The server retrieves the user profile from the database and performs authentication. If authentication is successful, the session is started.

[0649] Step 3:

[0650] The server automatically generates an appropriate learning curriculum using an AI algorithm based on the user's skill level and learning goals.

[0651] Step 4:

[0652] The server sends the generated curriculum to the terminal. The terminal displays this in its user interface, allowing the user to begin learning.

[0653] Step 5:

[0654] Users view curriculum-based learning materials and complete assignments. They can enter questions via voice or text if they encounter any difficulties during their learning.

[0655] Step 6:

[0656] The terminal receives user input and sends it to the server. The server analyzes the question and generates an answer using AI.

[0657] Step 7:

[0658] The server sends the generated answers back to the terminal. The terminal displays the answers to the user, supporting smooth learning.

[0659] Step 8:

[0660] The server tracks the user's learning progress using a progress management function and collects progress data in real time. It then generates feedback tailored to the user's level of understanding.

[0661] Step 9:

[0662] Users review the feedback provided, revise their learning content as needed, and prepare for the next session.

[0663] Step 10:

[0664] When a user finishes learning, they initiate a logout procedure on their device. The device sends a logout request to the server, and the server terminates the session.

[0665] (Example 1)

[0666] 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".

[0667] In today's digital society, there is a need to provide flexible and effective learning experiences tailored to the diverse abilities and goals of individual users. However, traditional education systems generally only offer uniform materials, making personalization to meet diverse user needs difficult. Furthermore, the provision of learning environments that take into account multiple languages ​​and cultural backgrounds is insufficient. It is necessary to solve these problems and realize learning support optimized for each individual.

[0668] 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.

[0669] In this invention, the server includes information processing means for automatically generating an optimal learning plan based on the user's abilities and goals; user output means for presenting the generated learning plan and processing interactive input from the user; and progress tracking means for analyzing the user's learning progress and behavior and providing real-time evaluation and improvement suggestions. This makes it possible to provide a personalized learning experience that meets the individual needs and goals of each user, and to realize educational support that is adaptable to users with multilingual and multicultural backgrounds.

[0670] "User capability" refers to the level of knowledge and skills an individual possesses.

[0671] "Goals" refer to the specific objectives of learning or skill improvement that the user is trying to achieve.

[0672] A "learning plan" refers to a set of learning guidelines and a curriculum that are dynamically generated based on the user's abilities and goals.

[0673] "Information processing means" refers to a function that analyzes digital data and automatically generates an optimal learning plan for the user using a generated AI model.

[0674] "User output means" refers to an interface function that presents the generated learning plan to the user and enables interaction with it.

[0675] "Progress tracking means" refers to a function that monitors the user's learning status in real time and evaluates their progress and level of understanding.

[0676] "Question and answer generation means" refers to a function that generates appropriate answers to user questions in both voice and text.

[0677] "Digital skills" refer to the ability to process information and solve problems using computers and the internet.

[0678] "Educational support tools" refer to auxiliary functions and resources that provide users with an effective learning experience.

[0679] "Multilingual support" refers to the ability to interact with users in multiple languages ​​and to provide support tailored to their respective cultural backgrounds.

[0680] "Profile information" refers to data that records a user's past learning history and current learning needs.

[0681] This invention is a digital skills enhancement system that addresses individual learning needs and functions through the mutual cooperation of a server, terminal, and user. When implementing this invention, appropriate hardware and software are used to process data and provide the user with an optimal learning experience.

[0682] The server accesses the database to retrieve profile information tailored to the user's abilities and goals, and performs advanced information processing. The generative AI model used here automatically generates a learning plan based on the user's profile. In this process, natural language processing models such as OpenAI's GPT series are used.

[0683] The device provides a user interface, allowing users to review generated learning plans and progress through their studies. Users can manage their learning progress and receive real-time feedback through the device. Furthermore, if users have questions, they can ask them via text or voice input and receive accurate answers from the server.

[0684] For example, when a user learns how to use new software, the server generates a beginner-friendly learning plan and displays a visual tutorial on the terminal. If the user enters a question such as, "How do I save a file with this software?", the server can provide specific steps to answer it.

[0685] As described above, the present invention is a system that utilizes input examples of prompt sentences generated by an AI model to provide flexible and effective educational support to individual users.

[0686] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0687] Step 1:

[0688] The user accesses the login screen via their device and enters their username and password. The device then sends this login information to the server. The server authenticates the user based on the received information and retrieves the user's profile data from the database. The user's profile information is then output and passed on to the next step.

[0689] Step 2:

[0690] The server uses the acquired profile data to analyze the user's abilities and goals. Based on this data, a generative AI model operates to automatically generate an appropriate learning plan. Specifically, it selects learning materials and practice problems according to the user's skill level and performs data calculations to adjust the difficulty level. As output, an optimized learning plan is generated and sent to the terminal.

[0691] Step 3:

[0692] The terminal provides input to display the received learning plan on the user interface. Through this interface, the user can monitor their learning progress and take specific actions to begin learning. The terminal provides output that tracks the user's progress in real time and stores data for reporting to the server.

[0693] Step 4:

[0694] If a user has questions during the learning process, they can use their device to input the question in voice or text format. The device then sends this user question to the server. The server analyzes the question and processes the data using a generative AI model to generate an appropriate answer. As output, the server sends the generated answer to the device for the user to receive.

[0695] Step 5:

[0696] The server receives input that allows for detailed analysis of the user's learning behavior using progress tracking mechanisms. This includes data such as the number of completed learning materials and the accuracy rate of answers. Based on this data, the server evaluates the user's level of understanding and performs data calculations to configure and provide additional learning materials and feedback as needed. As output, feedback and a new learning plan are generated and delivered to the user via the terminal.

[0697] (Application Example 1)

[0698] 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".

[0699] In modern society, acquiring digital skills is essential, but a challenge remains: effective learning environments tailored to individual users are not readily available. In particular, the lack of support that caters to individual progress and needs in home learning is a significant problem. Furthermore, acquiring digital skills, which often involve complex operations, highlights the need for instruction using natural language interaction with voice recognition.

[0700] 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.

[0701] In this invention, the server includes information processing means for automatically generating an optimal learning plan based on the user's skill level and goals, operation screen means for presenting the generated learning plan and processing interactive input from the user, and dialogue support means for enabling natural interaction with the user via a home robot and assisting in the improvement of digital skills. As a result, the user receives individually optimized learning support for digital skills and can effectively acquire skills even in a home environment.

[0702] "User skill level" is a measure that indicates the degree of proficiency and technical ability possessed by a user.

[0703] A "learning plan" is a combination of learning materials and activities designed to improve a user's skills.

[0704] An "information processing system" is a mechanism for receiving data, analyzing it, and generating output tailored to a specific purpose.

[0705] An "operation screen means" is a mechanism that provides an interface for users to interact with the system.

[0706] A "progress management tool" is a function that tracks and evaluates the user's learning activities in real time and provides feedback based on that.

[0707] A "question answering system" is a mechanism that analyzes user-submitted questions in both voice and text format and generates appropriate answers.

[0708] A "household robot" is an autonomous mechanical device used in a home environment that provides various forms of support through natural interaction with the user.

[0709] A "dialogue support system" is a mechanism that assists with voice and text-based communication with users, effectively supporting their learning.

[0710] A system implementing this invention functions through a series of processes including a user, a server, a terminal, and a home robot.

[0711] The server utilizes a generative AI model to generate an optimal learning plan based on the user's skill level and goals. The generated learning plan is sent from the server to the terminal and displayed on the operation screen. The terminal functions as a user interface, where the user progresses through the learning process and makes inputs as needed.

[0712] The home robot understands user questions through voice recognition and uses a generative AI model to answer them. This supports the user through natural dialogue. Specifically, if the robot asks a user, "I don't know the basic operations of image editing software," it can respond in an instructive and simple way, "Save it from the menu," thereby facilitating the user's learning process.

[0713] As a means of progress management, the server tracks the user's learning behavior in real time and records that behavior in a database. This allows the server to provide feedback and additional learning resources according to the user's progress.

[0714] Furthermore, the following example prompts can be used to effectively question the generative AI model:

[0715] "Please teach me the basic operations of image editing software for beginners."

[0716] "What kind of teaching materials would be effective as the next step?"

[0717] In this way, the present invention provides a system that effectively supports the improvement of digital skills in a home environment.

[0718] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0719] Step 1:

[0720] The server is accessed by the user through their terminal, and they enter their login information. Based on this input, the server retrieves the user's profile data from the database. This retrieved profile data includes the user's past learning history, skill level, and learning goals. This is used to establish the basis for the next learning plan.

[0721] Step 2:

[0722] The server uses a generative AI model to generate an appropriate learning plan based on the user's profile data. Using the profile and current learning goals as input, the AI ​​model selects the most suitable learning materials and exercises, and adjusts their difficulty level. As a result, a specific curriculum is output.

[0723] Step 3:

[0724] The terminal receives the learning plan sent from the server and displays it on the operation screen. The user can proceed with their learning while viewing this operation screen. The information provided here includes visual learning materials and interactive exercises.

[0725] Step 4:

[0726] If a user encounters any unclear points or questions during their learning process, they can input them via voice or text through their device. These questions are sent to a server, which uses a question-answering mechanism and a generative AI model to generate appropriate answers, which are then sent back to the device. This allows users to resolve their questions immediately.

[0727] Step 5:

[0728] Home robots use speech recognition to support learning through natural conversations with users. When a user asks a question, the robot sends prompts to an AI model based on the recognized speech input and obtains answers. Specific operations include processes such as "converting speech to text, sending this text to the AI ​​model, and returning the generated answer to the user in speech."

[0729] Step 6:

[0730] The server utilizes progress management tools to track users' learning progress in real time. It receives user learning behavior data as input and records it in a database. This allows for the provision of feedback and adjustments to learning materials for subsequent sessions. As a result, a personalized learning experience is provided for each user.

[0731] 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.

[0732] This invention is a learning system aimed at improving users' digital literacy, and by incorporating an emotion engine, it provides a flexible learning experience that responds to the user's emotional state. This system operates in cooperation with a server, terminal, and user.

[0733] First, the user accesses the system from their device, logs in, and enters their personal page. The device sends authentication information from the user to the server, which then uses that information to retrieve the user profile and initiate a session. The profile includes skill level, learning history, and set learning goals.

[0734] The server automatically generates a curriculum using AI based on profile data. This curriculum provides appropriate learning materials and challenges for the user and sends them to the device. The user interface displays this curriculum and provides an interactive learning environment.

[0735] Here, the emotion engine constantly monitors the user's input. When the user enters questions and answers via voice or text, the device sends this data to the server. The server's emotion engine analyzes the user's emotions from the input data and has a mechanism to detect changes in stress and motivation. For example, if a user has been studying for a long time, the emotion engine will detect signs of decreased concentration and suggest a short break as a mitigation measure.

[0736] Based on the emotion engine's analysis results, the server provides real-time feedback through the user interface. For example, if the emotion engine determines that the user is confused or overwhelmed by a difficult task, the server can provide hints or supplementary information.

[0737] In this manner, the system of the present invention adapts to each user's individual learning needs and emotional state, realizing a more effective and personalized learning experience. This promotes improvement in digital literacy while simultaneously maintaining motivation for learning.

[0738] The following describes the processing flow.

[0739] Step 1:

[0740] The user logs into the system using a terminal and enters their username and password.

[0741] Step 2:

[0742] The terminal sends the entered authentication information to the server. The server retrieves the corresponding user profile from the database, and if authentication is successful, starts a session.

[0743] Step 3:

[0744] The server automatically generates personalized learning curricula using generative AI based on the user's profile data. These curricula include learning materials and exercises tailored to the user's skill level and goals.

[0745] Step 4:

[0746] The server sends the generated curriculum to the terminal, which displays it in the user interface. The user then begins learning according to this curriculum.

[0747] Step 5:

[0748] The user enters questions via voice or text while learning. The device receives these and sends them to the server.

[0749] Step 6:

[0750] The server analyzes the received question and uses an emotion engine to analyze the user's emotional state. If the user is dissatisfied or confused, the emotion engine will detect it.

[0751] Step 7:

[0752] Based on the analysis results of the emotion engine, the server can generate appropriate answers to questions and can also provide encouraging messages and additional hints for the user.

[0753] Step 8:

[0754] The server sends the generated answers and feedback back to the terminal, which then presents them to the user through the user interface. The user reviews the provided information and continues learning.

[0755] Step 9:

[0756] The server uses progress management features to track users' learning progress. In particular, it evaluates users' stress levels and motivation, and adjusts the curriculum content if necessary.

[0757] Step 10:

[0758] When a user completes a learning session, they log out on their device, and the device sends this request to the server. The server then safely terminates the session.

[0759] (Example 2)

[0760] 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".

[0761] In today's learning environment, there is a demand for flexible and effective educational plans tailored to each user's skill level and individual learning goals. However, conventional systems have struggled to provide learning support that responds to users' emotional states and to offer individualized feedback in real time, limiting the improvement of learning efficiency. Therefore, there is a need for a system that provides a personalized learning experience that reflects users' emotional states and realizes effective digital education.

[0762] 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.

[0763] In this invention, the server includes data processing means for automatically generating an optimal educational plan based on the user's skill level and learning objectives; display means for presenting the generated educational plan and processing interactive input from the user; and sentiment analysis means for analyzing the user's emotional state and providing real-time adjustments to the learning pace and feedback accordingly. This enables a flexible and effective learning experience that meets the individual needs of each user.

[0764] A "user" refers to an individual or group that uses this system for learning.

[0765] "Skill level" refers to the degree of knowledge and skills a user already possesses, and serves as a benchmark for progressing through the learning process.

[0766] "Learning objectives" refer to the specific results or goals that users aim to achieve when using the system.

[0767] An "educational plan" refers to the arrangement and structure of learning content that is appropriately built based on the user's skill level and learning objectives.

[0768] "Data processing means" refers to functions for collecting and analyzing information about users to generate optimal educational plans.

[0769] "Display means" refers to a function that presents the generated educational plan to the user visually or audibly.

[0770] "Emotional state" refers to the psychological or emotional changes that a user exhibits during learning, and is a factor that influences the progress of their learning.

[0771] "Providing in real time" means responding immediately to users' learning processes and providing feedback and support.

[0772] "Emotional analysis tools" refer to functions that analyze user input data, evaluate their emotional state, and provide appropriate support for learning.

[0773] This invention is a learning system that incorporates sentiment analysis, aiming to improve users' digital literacy. In implementing this invention, the server, terminal, and user work together.

[0774] The server uses high-performance data processing equipment to generate educational plans based on user profile data stored in the database. Specifically, the server leverages a generative AI model to automatically create optimal educational plans tailored to the user's skill level and learning objectives. A generally available high-performance server platform is used for program processing.

[0775] The device functions as a user interface, displaying the generated educational plan to the user. This is achieved through an application running on a PC, tablet, or smartphone. The user provides voice and text feedback on the displayed plan, and this input data is sent to the server.

[0776] As users interact with the device and progress through the learning process according to the presented educational plan, they provide various inputs (questions, responses, etc.). These inputs are analyzed by the server's sentiment analysis system, and feedback is provided that is appropriately adjusted according to the user's emotional state. For example, if a user is facing a difficult task, the server provides appropriate hints and advice in real time.

[0777] As a concrete example, a prompt statement is written in the following format:

[0778] "When a person is studying for an extended period and their emotional engine detects signs of decreased concentration, what kind of break would be most effective to suggest?"

[0779] As described above, the present invention improves digital literacy by adapting to the individual learning needs and emotional states of users and providing a personalized learning experience.

[0780] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0781] Step 1:

[0782] The server handles the user login process. It receives login information sent from the terminal as input data, searches the database, and performs authentication. If authentication is successful, it retrieves the user's profile information and starts a session. The output is a session start success notification and profile data.

[0783] Step 2:

[0784] The server automatically generates educational plans based on user profiles using a generative AI model. Input data includes the user's skill level, past learning history, and learning goals. The AI ​​model analyzes this data and outputs the optimal educational plan. Specifically, the AI ​​model selects teaching materials and practice problems through an algorithm.

[0785] Step 3:

[0786] The terminal presents the user with the educational plan received from the server. The input is the educational plan data from the server. The terminal displays this data in a user interface and formats it in a way that is easy for the user to access. The output is a curriculum display as visual or auditory information. Specifically, it displays links to learning materials and practice problems on the screen.

[0787] Step 4:

[0788] Users progress through the learning process using a device, asking and answering questions via voice or text. Input is the user's dialogue based on the displayed curriculum. The device sends this input data to a server for sentiment analysis. Output is the transmission of input data to the server.

[0789] Step 5:

[0790] The server analyzes user input data using sentiment analysis tools. Input consists of voice and text data from the terminal. The sentiment analysis engine evaluates the user's emotional state and adjusts the learning environment if necessary. Output includes feedback and adjustment suggestions tailored to the emotional state. Specifically, if a decrease in concentration is detected, the server suggests a break.

[0791] Step 6:

[0792] The terminal receives feedback and adjustment suggestions sent back from the server and presents them to the user. The input is feedback data from the server. The terminal displays this information on its interface and prompts the user to take appropriate action. The output is feedback presentation as visual or auditory information. Specifically, hints and advice are displayed as pop-ups.

[0793] (Application Example 2)

[0794] 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".

[0795] In modern society, improving digital literacy is essential, but personalized learning environments that cater to individuals with diverse backgrounds remain insufficient. Furthermore, there is a need for real-time support that addresses the stress and motivational challenges that arise during learning. Traditional learning systems have struggled to recognize learners' emotional states and automatically provide appropriate feedback based on them.

[0796] 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.

[0797] In this invention, the server includes information processing means for automatically generating an optimal learning program based on the user's skill level and goals, user interface means for presenting the generated learning program and processing interactive input from the user, and adjustment means for automatically suggesting relaxation and entertainment content based on the user's emotional state. This enables learners to obtain an optimized learning experience that is tailored to their own learning progress and emotional state.

[0798] "Information processing means" refers to a device or software that has the function of automatically generating an optimal learning program based on the user's skill level and goals.

[0799] "User interface means" refers to a device or software that presents a generated learning program and provides an interactive display and operation environment for processing interactive input from the user.

[0800] A "progress management tool" is a device or software that analyzes the user's learning progress and behavior, provides real-time feedback, and further analyzes the user's emotional state to provide an adaptive learning experience.

[0801] A "question answering tool" is an algorithm or software that analyzes voice and text input and automatically generates answers to questions from the user.

[0802] "Adjustment means" refers to a device or software that has the function of automatically suggesting relaxation or entertainment content based on the user's emotional state.

[0803] To implement this invention, a server, terminal, and user work together to build a learning system. The server has information processing means that automatically generates an optimal learning program based on the user's skill level and goals using a generation AI model. The generated learning program is displayed on a user interface means via the terminal and accepts interactive input from the user.

[0804] Users access the system and begin learning through devices such as smartphones and tablets. The device collects the user's voice and text input and transmits it to the server. The server receives this data and analyzes the user's emotional state using an emotion engine. If the analysis determines that the user's concentration is low, the server automatically suggests relaxation content using adjustment mechanisms. For example, the server might create a suggestion such as, "Let's take a short break. How about listening to your favorite music to refresh yourself?" and send it to the device.

[0805] As a concrete example, the following is an example of a prompt: "Based on the user's past learning data and current emotional state, please suggest the next most suitable learning material." By sending this prompt to the generating AI model, it is possible to provide the user with an optimal learning experience.

[0806] This system utilizes programming languages ​​such as Python for its construction, and software like IBM Watson and Google Cloud Natural Language API can be used for sentiment analysis. Furthermore, OpenAI's GPT-3 can be leveraged for the generative AI model. This allows users to receive a personalized learning experience tailored to their emotional state and learning progress.

[0807] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0808] Step 1:

[0809] The user accesses the learning system using a device and enters their login information. The device sends the user's authentication data to the server, which receives this data. Upon successful login, the server reads the user's profile information and verifies their skill level and past learning history.

[0810] Step 2:

[0811] The server processes information based on the user's skill level and set learning objectives, and automatically generates a curriculum using a generative AI model. This process analyzes the input profile data, selects the most suitable learning materials and activities, and structures them into a curriculum. As a result, curriculum data tailored to the user is generated.

[0812] Step 3:

[0813] The generated curriculum is sent from the server to the terminal's user interface. The terminal displays this curriculum to the user, providing an interactive learning environment. As the user works on assignments, they can provide feedback and questions via voice or text.

[0814] Step 4:

[0815] User input is sent from the terminal to the server, which uses an emotion engine to analyze the user's emotional state from the input data. Here, natural language processing and emotion analysis techniques are used to determine the user's stress level and whether their motivation for learning has decreased. The analysis results are then obtained as output.

[0816] Step 5:

[0817] Based on the analysis of the user's emotional state, the server uses adjustment mechanisms to generate relaxation content and additional learning hints as needed. For example, if a decrease in concentration is detected, the server might create a relaxation suggestion such as "Let's take a short break." This provides personalized feedback tailored to the user.

[0818] Step 6:

[0819] The generated suggestions and content are sent to the device and presented to the user through the user interface. Users can receive this feedback and use it in their next learning activity, enabling them to continue a learning experience tailored to their own pace and circumstances.

[0820] 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.

[0821] 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.

[0822] 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.

[0823] 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.

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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."

[0829] 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.

[0830] 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.

[0831] 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.

[0832] 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.

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] The following is further disclosed regarding the embodiments described above.

[0842] (Claim 1)

[0843] An information processing means that automatically generates an optimal curriculum based on the user's skill level and goals,

[0844] A user interface means that presents a generated curriculum and processes interactive input from the user,

[0845] A progress management system that analyzes user learning progress and behavior and provides real-time feedback,

[0846] A question answering means that analyzes voice and text input to generate answers to user questions,

[0847] A system that includes this.

[0848] (Claim 2)

[0849] The system according to claim 1, which supports multiple languages ​​and adjusts the curriculum and user interface to suit users from multiple cultural backgrounds.

[0850] (Claim 3)

[0851] The system according to claim 1, further optimizing the next learning session using the user's past learning history and profile data.

[0852] "Example 1"

[0853] (Claim 1)

[0854] An information processing means that automatically generates an optimal learning plan based on the user's abilities and goals,

[0855] A user output means that presents a generated learning plan and processes interactive input from the user,

[0856] A progress tracking system that analyzes user learning progress and behavior, and provides real-time evaluation and improvement suggestions,

[0857] A question and answer generation means that analyzes voice and text input to generate answers to user questions,

[0858] An educational support system that aims to improve digital skills and adapts the curriculum according to individual learning needs,

[0859] A system that includes this.

[0860] (Claim 2)

[0861] The system according to claim 1, which supports multiple languages ​​and adjusts the learning plan and user output means to adapt to users from multiple cultural backgrounds.

[0862] (Claim 3)

[0863] The system according to claim 1, further optimizing the next learning session by utilizing the user's past learning history and profile information.

[0864] "Application Example 1"

[0865] (Claim 1)

[0866] An information processing means that automatically generates an optimal learning plan based on the user's skill level and goals,

[0867] An operation screen means that presents a generated learning plan and processes interactive input from the user,

[0868] A progress management system that analyzes users' learning progress and behavior and provides real-time evaluations,

[0869] A question answering means that analyzes voice and text input to generate answers to user questions,

[0870] A dialogue support means that enables natural user interaction through a home robot and supports the improvement of digital technology,

[0871] A system that includes this.

[0872] (Claim 2)

[0873] The system according to claim 1, which supports multiple languages ​​and adjusts the learning plan and user interface to suit users from multiple cultural backgrounds.

[0874] (Claim 3)

[0875] The system according to claim 1, further optimizing the next learning activity by utilizing the user's past learning history and profile data.

[0876] "Example 2 of combining an emotion engine"

[0877] (Claim 1)

[0878] A data processing means that automatically generates an optimal educational plan based on the user's skill level and learning objectives,

[0879] A display means that presents the generated educational plan and processes interactive input from the user,

[0880] A sentiment analysis tool that analyzes the user's emotional state and provides real-time adjustments to the learning pace and feedback accordingly,

[0881] An answer generation means that analyzes voice and text input to generate answers to user questions,

[0882] A system that includes this.

[0883] (Claim 2)

[0884] The system according to claim 1, which supports multiple languages ​​and adjusts educational plans and display means to accommodate users with multiple cultural backgrounds.

[0885] (Claim 3)

[0886] The system according to claim 1, which further optimizes the next learning session by utilizing the user's past educational history and profile information.

[0887] "Application example 2 when combining with an emotional engine"

[0888] (Claim 1)

[0889] An information processing means that automatically generates an optimal learning program based on the user's skill level and goals,

[0890] A user interface means that presents the generated learning program and processes interactive input from the user,

[0891] A progress management system that analyzes the user's learning progress and behavior, provides real-time feedback, analyzes their emotional state, and provides an adaptive learning experience.

[0892] A question answering means that analyzes voice and text input to generate answers to user questions,

[0893] An adjustment mechanism that automatically suggests relaxation and entertainment content based on the user's emotional state,

[0894] A system that includes this.

[0895] (Claim 2)

[0896] The system according to claim 1, which supports multiple languages ​​and adjusts the learning program and user interface to suit users from multiple cultural backgrounds.

[0897] (Claim 3)

[0898] The system according to claim 1, further optimizing the next learning session using the user's past learning history and profile data, and generating individually tailored learning materials and feedback using a generative AI model. [Explanation of symbols]

[0899] 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. An information processing means that automatically generates an optimal curriculum based on the user's skill level and goals, A user interface means that presents a generated curriculum and processes interactive input from the user, A progress management system that analyzes user learning progress and behavior and provides real-time feedback, A question answering means that analyzes voice and text input to generate answers to user questions, A system that includes this.

2. The system according to claim 1, which supports multiple languages ​​and adjusts the curriculum and user interface to suit users from multiple cultural backgrounds.

3. The system according to claim 1, further optimizing the next learning session using the user's past learning history and profile data.

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