System

Abstract

A system is provided.SOLUTION: A system comprising: a terminal for inputting contents that a user wants to learn; a server having natural language processing means for receiving and analyzing the learning contents input from the terminal; means for proposing an optimum learning course based on an analysis result; means for providing a confirmation test based on a learning progress situation of the user; and means for applying a discount to a specific communication service user based on communication line information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In recent years, changes in the skills required by society and companies have created a demand for efficient and easy ways to relearn. However, many online learning services require users to select the appropriate learning course themselves, which can lead to problems such as biased learning content, insufficient preparation for confirmation tests and exams, and the need to prepare and purchase learning materials. Furthermore, few services offer benefits such as discounts based on communication service usage. The objective of this invention is to solve these problems and provide an environment where many people can learn efficiently and easily. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means. The online learning system of the present invention provides a terminal for users to input the content they want to learn, and includes a server with natural language processing means for receiving and analyzing the learning content input from the terminal. The server proposes an optimal learning course based on the analysis results and provides confirmation tests based on the user's learning progress. The server also provides test preparation content to users and applies discounts to specific communication service users based on communication line information. This allows users to study efficiently and easily, maximizing the effectiveness of their learning.

[0006] "User" refers to an individual or organization that uses the online learning system to relearn.

[0007] "Device" refers to an electronic device, such as a PC or mobile device, that a user uses to access the online learning system.

[0008] "Server" refers to the computer system that processes and manages data at the core of the online learning system.

[0009] "Input Form" refers to a field on a web page where a user can enter information about what they want to learn.

[0010] "Natural language processing means" refers to technology for analyzing the text data entered by the user and understanding its meaning.

[0011] "Learning Course" refers to a series of learning programs and materials suggested based on what the user wants to learn.

[0012] A "confirmation test" is a test provided according to the user's learning progress, and refers to a tool for checking the user's level of understanding of the learning content.

[0013] "Exam Preparation Content" refers to specialized study materials and practice tests that enable users to study for a particular qualification or certification exam.

[0014] "Communication line information" refers to information that indicates the status of the communication services that the user is using.

[0015] "Means for applying discounts" refers to a mechanism for reducing part of the service fee for users who meet certain conditions. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] ---

[0038] This invention relates to an online learning system using PCs and mobile devices. The system of the present invention has a terminal for inputting the content to be learned, a server that receives and analyzes the input content, a server function that proposes the optimal learning course, a server function that provides confirmation tests and test preparation content, and a server function that applies discounts based on communication line information. Each function is described in detail below.

[0039] ---

[0040] Enter what you want to learn

[0041] Users access the learning system's website from a web browser on their PC or mobile device. They enter what they want to learn into the input form on the website. For example, if they want to learn "data science," they enter that information into the form and click the submit button.

[0042] ---

[0043] Receiving and parsing input

[0044] The server receives the desired learning content sent from the device. After receiving it, it uses natural language processing to analyze the text of the input content and extracts key keywords. For example, if "data science" is input, the server analyzes this keyword and searches for related learning courses.

[0045] ---

[0046] Suggestion of the best course of study

[0047] The server searches the database for the most appropriate learning course based on the analysis results. To minimize latency, it is desirable to pre-index a large amount of learning data. It then suggests highly relevant learning courses to the user. For example, the server might display courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science" on the user's device.

[0048] ---

[0049] View and select a course

[0050] The device receives the course information sent from the server and displays it to the user. The user selects the desired course from the displayed courses and clicks the "Start" button for the course. For example, if the user selects "Python for Data Science," they click on that course.

[0051] ---

[0052] Providing learning content

[0053] The server retrieves the learning materials, videos, and exercises corresponding to the user's selected course from the database and delivers them to the user's device. The device displays the delivered content and allows the user to progress with their studies. For example, video lectures can be played and PDF learning materials can be downloaded.

[0054] ---

[0055] Providing confirmation tests

[0056] The server provides confirmation tests at appropriate times according to the user's learning progress. The tests consist of multiple choice and written questions to verify the user's level of understanding. When the user answers the confirmation test and clicks the submit button, the server receives the answers and grades them using an automated evaluation system.

[0057] ---

[0058] Providing Feedback

[0059] The server generates feedback for the user based on the results of the confirmation test and sends it to the device. The device displays this feedback, allowing the user to understand their level of understanding and weak points. For example, the feedback might be, "You got 80% correct. You need to practice more on loop syntax."

[0060] ---

[0061] Providing exam preparation content

[0062] Users can input information about specific qualification exams and certification tests. The server then retrieves the appropriate test preparation content from the database and delivers it to the device. The device then displays the received test preparation content, allowing the user to use it to prepare for the exam.

[0063] ---

[0064] Discounts applied

[0065] The server checks the user's communication line information and applies discounts to users of specific communication services. For example, if a user uses a specific communication service, the server calculates the discount price and displays the discounted fee information on the terminal.

[0066] ---

[0067] In this way, the online learning system of the present invention provides an environment in which users can learn efficiently and easily, maximizing the effectiveness of their learning.

[0068] The processing flow will be explained below.

[0069] Step 1:

[0070] The user accesses the learning system website using the browser on their PC or mobile device, enters the content they want to learn into the input form, and clicks the submit button.

[0071] Step 2:

[0072] The device sends the user's input to the server, where it is temporarily stored.

[0073] Step 3:

[0074] The server uses a natural language processing engine to analyze the user's input and extract key keywords. For example, if a user inputs that they want to learn "data science," the server will extract the keyword "data science."

[0075] Step 4:

[0076] The server searches the database for relevant learning courses based on the extracted keywords, creates a list of learning courses, and selects the most suitable course for the user.

[0077] Step 5:

[0078] The server sends the selected course list to the user's device, which then displays the received course list on the screen for the user to select.

[0079] Step 6:

[0080] The user selects the desired course from the displayed learning courses and clicks the "Start" button for the selected course. The terminal sends the selection information to the server.

[0081] Step 7:

[0082] The server retrieves the learning materials, videos, and exercises corresponding to the user's selected course from a database and delivers them to the device in sequence. The device then displays the received content, allowing the user to proceed with their learning.

[0083] Step 8:

[0084] The server tracks the user's learning progress and provides a confirmation test to the user's device at the appropriate time, which then displays the test on the screen.

[0085] Step 9:

[0086] The user takes the test and enters their answers. The device sends the answers to a server, which then grades them with an automated scoring system and generates a result.

[0087] Step 10:

[0088] The server generates feedback based on the results of the verification test and sends it to the user's device, which then displays the feedback to the user.

[0089] Step 11:

[0090] The user enters information about the qualification exam or certification exam they wish to take. The device sends the entered information to the server. The server retrieves exam preparation content from the database and distributes it to the user's device.

[0091] Step 12:

[0092] The server checks the user's communication line information and applies a discount if a specific communication service is used. The server calculates the discount price and displays the discounted fee information on the terminal.

[0093] ---

[0094] Through the above processing steps, the user can proceed with efficient and effective learning.

[0095] Example 1

[0096] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0097] In recent years, demand for online learning systems has increased, but systems that can propose optimal learning courses for individual users and respond flexibly based on their learning progress are not yet fully developed. Additional features, such as discount application based on communication line information, are also lacking. Therefore, there is a need for a system that allows users to efficiently and effectively learn the content they want to learn.

[0098] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0099] In this invention, the server includes means using a generative AI model to analyze the user's text input, means for providing a validation test based on the user's learning progress, and means for receiving the user's validation test answers and scoring them using an automated assessment system, thereby enabling personalized learning course suggestions, progress management, and discount application.

[0100] A "terminal" is a device that allows a user to input information and check the display, and includes devices such as PCs and mobile terminals.

[0101] A "server" is a computer system that receives, analyzes, stores, and transmits information over a network.

[0102] "Natural language processing means" refers to means that use technologies and algorithms to analyze input text information and understand its meaning.

[0103] A "course" is a collection of study materials, lectures, and exercises designed for a user to study.

[0104] A "confirmation test" is a multiple-choice or written test to measure a user's level of understanding.

[0105] "Exam Preparation Content" refers to study materials and practice questions designed to help students pass a particular qualification or certification exam.

[0106] "Communication line information" refers to information about the provider and contract plan of the communication service used by the user.

[0107] A "generative AI model" is a machine learning algorithm or model for natural language processing and data analysis.

[0108] An "automated evaluation system" is a system that analyzes user responses and performs mechanical evaluations.

[0109] "Feedback" is advice or instruction provided to a user based on their learning progress or test results.

[0110] This invention relates to an online learning system using PCs and mobile devices. It includes a terminal for users to input the content they want to learn, a server that receives and analyzes the input, a server that proposes the optimal learning course based on the analysis results, a server that provides confirmation tests according to learning progress, a server that provides test preparation content, and a server that applies discounts based on communication line information. Each function is described in detail below.

[0111] First, users access the learning system's website from their PC or mobile device, enter the subject they want to learn (e.g., "data science") into the input form on the website, and click the submit button.

[0112] The server then receives the desired learning content sent from the device. After receiving it, the server uses a generative AI model (e.g., the BERT model) to analyze the text of the input and extract key keywords. For example, if "data science" is input, the server analyzes this keyword and searches a database for related learning courses. This database contains data indexed using, for example, Elasticsearch.

[0113] The server searches the indexed data for the most suitable learning courses and displays the most relevant courses on the user's device. For example, it might suggest courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science." The user can select the desired course from the displayed courses and click on it.

[0114] The learning materials, videos, and exercises corresponding to the selected course are delivered from the server. This includes learning materials stored in Amazon S3, for example. Users can view the delivered content on their devices and proceed with their studies. Specifically, video lectures are played and learning materials in PDF format can be downloaded.

[0115] Furthermore, the server provides confirmation tests according to the user's learning progress. These tests include multiple-choice and essay questions to check the user's level of understanding. When the user answers the confirmation test and submits the answers, the server receives the answers and scores them using an automated evaluation system (e.g., AutoML). The server then generates feedback based on the results of the confirmation test and sends it to the device. For example, the server may provide feedback such as, "You got 80% correct. You need to practice more on loop syntax."

[0116] Users can also enter information about specific qualification exams and certification tests. Based on this, the server retrieves appropriate test preparation content from the database and delivers it to the user's device. Users can use the received test preparation content to advance their exam preparation. For example, content such as "TOEIC Preparation Course" is provided.

[0117] Finally, the server checks the user's communication line information and applies discounts to users of specific communication services. For example, if the user is using a specific communication service, the server calculates the discount price and displays the discounted fee information on the terminal.

[0118] Prompt Sentence Examples

[0119] "What are the best online courses for Python for Data Science?"

[0120] In this way, the online learning system of the present invention provides an environment in which users can study efficiently and easily, maximizing the effectiveness of their learning.

[0121] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0122] Step 1:

[0123] Users access the learning system's website from a web browser on their PC or mobile device. They enter the subject they want to learn (e.g., "data science") into the input form and click the submit button. The input is text data of the subject they want to learn, and the output is data sent to the server as an HTTP POST request.

[0124] Step 2:

[0125] The server receives an HTTP POST request from the device for the content the user wants to learn. It uses a generative AI model (e.g., the BERT model) to analyze the input text and extract key keywords. Specifically, it tokenizes the text data and applies a natural language processing algorithm to identify important words and phrases. The input is the text data of the content the user wants to learn, and the output is the analysis results (key keywords).

[0126] Step 3:

[0127] The server uses the analyzed keywords to search the database for the most suitable learning courses. This search process uses a search engine (e.g., Elasticsearch) that utilizes indexed data. Specifically, the server scores the relevance of learning courses based on the keywords and lists the most suitable courses. The input is the main keywords, and the output is a list of the most suitable learning courses.

[0128] Step 4:

[0129] The terminal receives the list of optimal learning courses sent from the server and displays it to the user. The user selects the desired course (e.g., "Python for Data Science") from the displayed courses and clicks the select button. Here, the input is the list of learning courses, and the output is the specific course selected by the user.

[0130] Step 5:

[0131] The server retrieves the learning materials, videos, and exercises corresponding to the learning course selected by the user from a database. This database is stored, for example, using a cloud storage service (e.g., Amazon S3). The retrieved content is then delivered to the user's device. The input is the selected learning course, and the output is the learning materials, videos, and exercises (specific content).

[0132] Step 6:

[0133] The device receives the distributed learning content and displays it to the user. The user watches video lectures and downloads learning materials in PDF format to progress with their studies. Here, the input is the distributed learning content, and the output is the screen display for the user to study and the downloaded learning materials.

[0134] Step 7:

[0135] The server provides a confirmation test based on the user's learning progress. Specifically, it analyzes the user's access history and study time data to generate an appropriate test. The test includes multiple-choice and essay questions and is sent to the user. The input is the user's learning progress data, and the output is the generated confirmation test.

[0136] Step 8:

[0137] The terminal receives the confirmation test sent from the server and displays it to the user. The user answers the test and clicks the send button to send the answer data to the server. The input is the confirmation test and the output is the user's test answer.

[0138] Step 9:

[0139] The server receives the user's test answers and scores them using an automated evaluation system (e.g., AutoML). Feedback is generated based on the analysis results and sent to the user's device. The feedback includes the accuracy rate and areas for improvement in learning. The input is the user's test answers, and the output is the generated feedback.

[0140] Step 10:

[0141] The device receives the feedback sent from the server and displays it to the user. The user can understand their own level of understanding and weaknesses and can revise their study plan. The input is the feedback, and the output is the displayed feedback.

[0142] Step 11:

[0143] When a user inputs information about a specific qualification or certification exam, the server searches the database for appropriate exam preparation content and delivers it to the terminal. The input is the qualification or certification exam information, and the output is the exam preparation content.

[0144] Step 12:

[0145] The terminal receives the test preparation content sent from the server and displays it to the user, who can use it to prepare for the test. The input is the test preparation content, and the output is a display for the user to use in their studies.

[0146] Step 13:

[0147] The server checks the user's communication line information and applies discounts to specific communication service users. It verifies number portability information, calculates the discount, and sends it to the terminal. The input is communication line information, and the output is discount application information.

[0148] Step 14:

[0149] The terminal receives the discount application information sent from the server and displays it to the user. The user can check the discounted price information. The input is the discount application information, and the output is the discounted price displayed to the user.

[0150] Through these steps, the online learning system provides an environment that allows users to learn efficiently and easily, maximizing learning effectiveness.

[0151] (Application example 1)

[0152] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0153] Conventional online learning systems often limit the effectiveness of learning because they make it difficult for students to learn face-to-face or engage in real-time dialogue, and require students to manage their own progress independently. Furthermore, the process of efficiently inputting the content users want to learn and selecting the most appropriate course from a variety of courses is cumbersome. Furthermore, they are unable to fully accommodate the communication status and device environment of specific students, making it difficult to provide an individually optimized learning experience. New technological solutions are needed to solve these problems.

[0154] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0155] In this invention, the server includes a terminal for a user to input content they wish to learn, natural language processing means for receiving and analyzing the learning content input from the terminal, means for the server to suggest an optimal learning course based on the analysis results, means for the server to provide a confirmation test based on the user's learning progress, means for the server to provide test preparation content to the user, means for applying discounts to specific communication service users based on communication line information, means for the user to view and operate learning content in a virtual store using smart glasses, a head-mounted display, or other display device, means for the server to input content they wish to learn through voice recognition, and means for the server to visually display an appropriate learning course in a virtual reality environment. This solves the problem of users having difficulty in self-directed learning and provides a more immersive learning experience.

[0156] "What you want to learn" refers to the learning topics or themes that users select and enter based on their learning goals or interests.

[0157] A "terminal" is an electronic device used by a user to input data or view content, including smart glasses and head-mounted displays.

[0158] "Natural language processing means" refers to technology that analyzes text data entered by users and extracts meaning and important keywords.

[0159] A "server" is a central processing unit that receives input data from users, analyzes and processes it, and returns an appropriate response.

[0160] "Optimal learning course" refers to the educational program or content that best suits the user's learning needs.

[0161] "Study progress status" is information that indicates how much progress the user has made in the course of their studies.

[0162] A "review test" is a test provided to assess what a user has learned, and includes questions to check their understanding and memory.

[0163] "Exam Preparation Content" means study materials and practice questions provided to prepare for a particular qualification or certification exam.

[0164] "Communication line information" refers to information regarding the Internet connection and data communications used by the user.

[0165] A "means for applying discounts" is a mechanism for applying discounts and reducing fees to communication service users who meet certain conditions.

[0166] A "virtual store" is a virtual space that users can access via the Internet and purchase goods and services.

[0167] "Smart glasses" are glasses-type wearable devices equipped with a display function that can display and operate information.

[0168] A "head-mounted display" is a display device that the user wears on their head and can provide immersive images.

[0169] "Speech recognition" is a technology that converts a user's speech into text data in real time.

[0170] A "virtual reality environment" is a virtual space in which users are immersed in a computer-generated 3D space, providing a realistic experience.

[0171] The present invention aims to provide users with an immersive learning experience by incorporating a virtual reality environment into an online learning system. Specific embodiments of the present invention will be described below.

[0172] System Program

[0173] Hardware

[0174] Smart glasses: A wearable device in the form of glasses with a display function

[0175] Head-mounted display (HMD): A display device worn on the head.

[0176] Server: A central processing unit that receives, analyzes, and provides data

[0177] software

[0178] Natural Language Processing (NLP) systems: Analyze user input data and extract meaning and keywords (e.g., Google Cloud Natural Language API)

[0179] Virtual reality (VR) development platforms: Generate 3D spaces and provide interactive learning experiences (e.g., Unity 3D)

[0180] Learning Management System (LMS): Manages and delivers learning courses (e.g., Moodle)

[0181] Program processing description

[0182] 1. Enter what you want to learn

[0183] Users wear smart glasses or an HMD and voice-input what they want to learn in the virtual store.

[0184] Voice data is captured through the built-in microphone of smart glasses or HMDs and transmitted to a natural language processing system.

[0185] 2. Receiving and analyzing input

[0186] The server uses voice recognition to convert the user's voice input into text and uses a natural language processing system to extract keywords.

[0187] The server searches the learning management system for relevant learning courses based on the extracted keywords.

[0188] 3. Recommending the best course of study

[0189] The server searches for relevant learning courses and displays the results on the user's smart glasses or HMD.

[0190] Users can select the most appropriate course from the displayed list and begin learning.

[0191] 4. Offering study courses

[0192] The server sequentially delivers teaching materials and videos based on the course selected by the user.

[0193] Users can learn in a virtual reality environment through smart glasses or an HMD.

[0194] 5. Testing and providing feedback

[0195] The server provides confirmation tests according to the learning progress and scores the user's answers with an automated evaluation system.

[0196] Feedback is generated based on the results and displayed on the user's device.

[0197] 6. Provision of exam preparation content

[0198] When a user inputs the content they need to prepare for a specific exam, the server searches for and provides the preparation content based on that information.

[0199] 7. Discount Application

[0200] The server checks the user's communication line information and applies discounts to users of specific communication services.

[0201] Specific examples

[0202] 1. User A puts on the smart glasses and says, "I want to learn Python."

[0203] 2. The server recognizes "Python" as a keyword and suggests the related courses "Python for Data Science" and "Advanced Python."

[0204] 3. User A selects "Python for Data Science" and watches the course materials and videos in a virtual reality environment.

[0205] 4. During the learning process, the server provides a confirmation test, and after completion, feedback such as "You got 80% correct. You need more practice on loop syntax" is displayed.

[0206] Prompt Sentence Examples

[0207] Simulate a system that suggests learning content to users through voice control in a virtual learning salon. If a user types "I want to learn Python," explain what courses would be suggested and what learning content would be provided. Also, describe the technical implementation of the system.

[0208] This allows users to study in a virtual reality environment, providing a greater sense of immersion and learning effectiveness than traditional online learning systems.

[0209] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0210] Step 1:

[0211] Users wear smart glasses or a head-mounted display (HMD) and voice-input what they want to learn in the virtual store.

[0212] Input: User speech (e.g., "I want to learn Python")

[0213] How it works: Audio data is captured through the smart gadget's built-in microphone.

[0214] Output: Audio data is generated.

[0215] Step 2:

[0216] The server uses voice recognition to convert the user's voice input into text data.

[0217] Input: Audio data

[0218] How it works: The server uses a speech recognition engine (e.g., Google Cloud Speech-to-Text) to convert the audio data into text.

[0219] Output: Text data (e.g., "I want to learn Python")

[0220] Step 3:

[0221] The server analyzes the text data using natural language processing (NLP) and extracts keywords.

[0222] Input: Text data

[0223] How it works: The server uses a natural language processing engine (e.g., Google Cloud Natural Language API) to analyze the input text. The analysis extracts key keywords.

[0224] Output: Extracted keywords (e.g. "Python")

[0225] Step 4:

[0226] The server searches for relevant learning courses from a learning management system (LMS) based on the extracted keywords.

[0227] Input: Extracted keywords

[0228] How it works: The server searches the LMS database for learning courses related to the extracted keywords.

[0229] Output: A list of related learning courses (e.g., "Python for Data Science," "Advanced Python")

[0230] Step 5:

[0231] The server displays the search results on the user's smart glasses or HMD.

[0232] Input: A list of related courses

[0233] How it works: The server uses a virtual reality (VR) development platform (e.g. Unity 3D) to visually display the results on the user's smart gadget.

[0234] Output: A list of displayed courses

[0235] Step 6:

[0236] The user selects from the displayed learning courses and begins learning.

[0237] Input: Select a course of study (e.g., "Python for Data Science")

[0238] Operation: The user selects the desired course using the operation interface of the smart gadget and sends the selection information to the server.

[0239] Output: Information about the course selected by the user

[0240] Step 7:

[0241] The server delivers teaching materials and videos sequentially based on the course selected by the user.

[0242] Input: Course information selected by the user

[0243] How it works: The server retrieves the learning materials and videos corresponding to the selected course from the LMS and sends them to the user's smart gadget.

[0244] Output: Delivered learning materials and videos

[0245] Step 8:

[0246] Users can view educational materials and videos and progress through their studies in a virtual reality environment.

[0247] Input: Delivered learning materials and videos

[0248] How it works: Users view and interact with learning content in a virtual reality environment through smart glasses or an HMD.

[0249] Output: Learning progress data

[0250] Step 9:

[0251] The server provides confirmation tests according to the learning progress, and the user's answers are scored by an automated evaluation system.

[0252] Input: Learning progress data

[0253] How it works: The server provides a prompt at the appropriate time and automatically scores the user's answers.

[0254] Output: Verification test results

[0255] Step 10:

[0256] The server generates feedback based on the results of the validation test and displays it on the user's smart gadget.

[0257] Input: Verification test result

[0258] How it works: The server generates feedback and displays it to the user, showing their progress and suggesting areas for improvement.

[0259] Output: Feedback information (e.g., "You got it 80% right. You need more practice with loop syntax.")

[0260] Step 11:

[0261] Users input the content they need to prepare for a specific exam, and the server searches for and provides the preparation content based on that information.

[0262] Input: Test preparation input (e.g., "Data Science Certification Exam")

[0263] How it works: The server retrieves relevant test preparation content from the LMS and delivers it to the user's smart gadget.

[0264] Output: Provided exam prep content

[0265] Step 12:

[0266] The server checks the user's communication line information and applies discounts to users of specific communication services.

[0267] Input: Communication line information

[0268] How it works: The server analyzes the line information, calculates the applicable discounts, and notifies the user.

[0269] Output: Discount information

[0270] Through the above steps, the present invention can provide users with an efficient and effective learning environment.

[0271] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0272] ---

[0273] This invention relates to an online learning system using PCs and mobile devices. The system of the present invention includes a terminal for inputting the content to be learned, a server that receives and analyzes the input content, a server function for proposing optimal learning courses, a server function for providing confirmation tests and exam preparation content, a server function for applying discounts based on communication line information, and an emotion engine that recognizes the user's emotions. Each function is described in detail below.

[0274] ---

[0275] Input and analyze what you want to learn

[0276] Users access the learning system's website from a web browser on their PC or mobile device. They enter what they want to learn into the input form on the website. For example, if they want to learn "data science," they enter that information into the form and click the submit button.

[0277] The server receives the desired learning content sent from the device and analyzes the text using a natural language processing engine. It extracts key keywords and searches the database for relevant learning courses based on those keywords. For example, if the keyword "data science" is entered, the server will pick up courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science."

[0278] ---

[0279] Course suggestions and selection

[0280] The server sends the selected course list to the user's device, which then displays the list on the screen. The user selects the desired course from the displayed courses and clicks the "Start" button for the selected course. For example, if the user selects "Python for Data Science," they click on that course.

[0281] ---

[0282] Providing learning content and an emotional engine

[0283] The server retrieves the learning materials, videos, and exercises corresponding to the user's selected course from the database and delivers them to the device. The device displays the received content, allowing the user to proceed with their learning. For example, a video lecture can be played and PDF learning materials can be downloaded.

[0284] At the same time, the device uses an emotion engine to monitor the user's state and provide feedback and content accordingly. The device collects the user's facial expressions, voice, typing speed, and other behavioral data and sends it to the server. The server uses this data to analyze the user's emotional state and makes adjustments such as temporarily lowering the difficulty of the learning course if the user is feeling stressed.

[0285] ---

[0286] Providing confirmation tests and feedback

[0287] The server tracks the user's learning progress and provides confirmation tests at appropriate times. The tests consist of multiple choice and written questions to verify the user's level of understanding. When the user answers the confirmation test and clicks the submit button, the server receives the answers and grades them using an automated evaluation system.

[0288] The server generates feedback for the user based on the results of the confirmation test and sends it to the device. The device displays this feedback, allowing the user to understand their level of understanding and weak points. For example, the feedback might be, "You got 80% right. You need more practice with loop syntax."

[0289] ---

[0290] Providing exam preparation content

[0291] Users can input information about specific qualification exams or certification tests. Based on the entered exam information, the server retrieves appropriate exam preparation content from a database and delivers it to the device. The device then displays the received exam preparation content, allowing users to use it to prepare for the exam.

[0292] ---

[0293] Discounts applied

[0294] The server checks the user's communication line information and applies discounts to users of specific communication services. For example, if a user uses a specific communication service, the server calculates the discount price and displays the discounted fee information on the terminal.

[0295] ---

[0296] In this way, the online learning system of the present invention allows users to learn efficiently and easily, and optimizes the learning experience through emotion recognition, thereby providing an environment that maximizes learning effectiveness.

[0297] The processing flow will be explained below.

[0298] Step 1:

[0299] The user accesses the learning system website using the browser on their PC or mobile device, enters the content they want to learn into the input form, and clicks the submit button.

[0300] Step 2:

[0301] The device sends the user's input to the server, where it is temporarily stored.

[0302] Step 3:

[0303] The server uses a natural language processing engine to analyze the user's input and extract key keywords. For example, if a user inputs that they want to learn "data science," the server will extract the keyword "data science."

[0304] Step 4:

[0305] The server searches the database for relevant learning courses based on the extracted keywords, creates a list of learning courses, and selects the most suitable course for the user.

[0306] Step 5:

[0307] The server sends the selected course list to the user's device, which then displays the received course list on the screen for the user to select.

[0308] Step 6:

[0309] The user selects the desired course from the displayed learning courses and clicks the "Start" button for the selected course. The terminal sends the selection information to the server.

[0310] Step 7:

[0311] The server retrieves the learning materials, videos, and exercises corresponding to the user's selected course from a database and delivers them to the device in sequence. The device then displays the received content, allowing the user to proceed with their learning.

[0312] Step 8:

[0313] The device uses an emotion engine to collect the user's facial expression, voice, typing speed and other behavioral data, and then transmits the collected emotion data to the server.

[0314] Step 9:

[0315] The server analyzes the received emotional data and recognizes the user's learning state. If the user is feeling stressed, the difficulty level of the learning course and the presentation method will be adjusted.

[0316] Step 10:

[0317] The server tracks the user's learning progress and provides confirmation tests at appropriate times, which are then displayed on the device's screen.

[0318] Step 11:

[0319] The user takes the test and enters their answers. The device sends the answers to a server, which then grades them with an automated scoring system and generates a result.

[0320] Step 12:

[0321] The server generates feedback based on the results of the verification test and sends it to the user's device, which then displays the feedback to the user.

[0322] Step 13:

[0323] The user enters information about the qualification exam or certification exam they wish to take. The device sends the entered information to the server. The server retrieves exam preparation content from the database and distributes it to the user's device.

[0324] Step 14:

[0325] The server checks the user's communication line information and applies a discount if a specific communication service is used. The server calculates the discount price and displays the discounted fee information on the terminal.

[0326] Example 2

[0327] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0328] While conventional online learning systems offer basic functions such as providing optimal learning courses based on the content users input as they wish to learn, providing confirmation tests, and providing exam preparation content, they lack more advanced personalized learning support, such as optimizing the learning experience by taking into account the user's emotional state or applying discounts based on communication line information. This makes it difficult to maximize learning effectiveness and maintain motivation to learn.

[0329] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0330] In this invention, the server includes an information processing terminal for inputting content that the user wants to learn, natural language processing engine means for receiving and analyzing the learning content input from the terminal, means for the information processing device having a function of suggesting an optimal learning course based on the analysis results, means for the information processing device having a function of providing a confirmation test based on the user's learning progress, means for the information processing device having a function of providing test preparation content to the user, emotion recognition engine means for the information processing device having a function of monitoring the user's emotional state and optimizing the learning experience, and means for applying discounts to specific communication service users based on communication line information. This allows users to be provided with more highly personalized learning support, maximizing learning effectiveness and maintaining motivation to learn.

[0331] "User" refers to an individual or corporation that uses the online learning system to input what they want to learn and receive learning content.

[0332] "Information processing terminal" refers to a computer or mobile terminal that allows users to input study content and display study courses and content.

[0333] "Information processing device" refers to servers and cloud computing resources that handle all aspects of the learning system, such as receiving and analyzing the content to be learned, proposing learning courses, providing confirmation tests, and providing exam preparation content.

[0334] A "natural language processing engine" refers to a software engine that analyzes the text data of the learning content entered by the user and extracts important keywords.

[0335] "Study course suggestion function" refers to a function that suggests the most suitable study course to the user based on the results of analysis by the natural language processing engine.

[0336] "Confirmation test provision function" refers to a function for providing confirmation tests at appropriate times based on the user's learning progress.

[0337] "Exam preparation content provision function" refers to a function that provides users with appropriate exam preparation content based on the exam information entered by the user.

[0338] An "emotion recognition engine" is an engine that analyzes a user's facial expressions, voice, and behavioral data to recognize their emotional state and optimize the learning experience.

[0339] "Communication line information" refers to information about the internet line and communication services used by the user.

[0340] The "discount application function" refers to a function for applying a discount to a specific communication service user based on communication line information.

[0341] The present invention relates to an online learning system that includes an information processing terminal used by a user, an information processing device having a natural language processing engine, an emotion recognition engine, and a discount application function based on communication line information. The following describes in detail an embodiment of the present invention.

[0342] Input and analyze what you want to learn

[0343] Users access the online learning system using a web browser on an information processing device such as a PC or mobile device. They enter what they want to learn into the input form on the website and click the submit button. For example, they might enter "data science." The information processing device analyzes the input text using a natural language processing engine implemented in Python and extracts key keywords. The information processing device then searches for related learning courses in a MySQL database and suggests the most suitable course.

[0344] Course suggestions and selection

[0345] The information processing device sends a list of learning courses to be suggested to the user to the information processing terminal. The terminal uses JavaScript to display the list of learning courses on the screen. The user selects the desired course from the displayed course and clicks the start button. For example, the user selects "Python for Data Science."

[0346] Providing learning content and an emotional engine

[0347] The information processing device retrieves content related to the learning course selected by the user from a database and sequentially delivers it to the user's device. The device displays the received content in HTML format, allowing the user to proceed with their learning. For example, video lectures may be played and learning materials in PDF format may be available for download. The device also collects the user's emotional data from the webcam and microphone and transmits it to the server in real time. The information processing device analyzes the user's emotional state using an emotion recognition engine based on TensorFlow and provides feedback, such as adjusting the difficulty of the learning content, if the user is feeling stressed.

[0348] Providing confirmation tests and feedback

[0349] The information processing device tracks the user's learning progress and provides confirmation tests at appropriate times. The user answers the confirmation test and clicks the submit button. The information processing device receives the answers and scores them using an automated evaluation system implemented in Ruby. Feedback is generated based on the scoring results and sent to the device. The device displays the feedback on the screen, allowing the user to understand their level of understanding and areas for improvement.

[0350] Providing exam preparation content

[0351] Users can input specific exam information, for example, "AWS Certified Solutions Architect." The information processing device retrieves appropriate exam preparation content from a database based on that information and delivers it to the user's device. The device then displays the received content in HTML format, allowing the user to continue preparing for the exam.

[0352] Discounts applied

[0353] The information processing device checks the user's communication line information and applies a discount to users of a specific communication service. For example, if the user is a subscriber of a specific communication carrier, the information processing device calculates the discount price and transmits the fee information to the terminal. The terminal displays the discount information on its screen.

[0354] Examples of concrete examples and prompts

[0355] Specific examples

[0356] Learning content: "Data Science"

[0357] Suggested courses: "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science."

[0358] Course selected: "Python for Data Science"

[0359] Learning content: video lectures, PDF materials

[0360] Test result: "80% correct. I need more practice with loop syntax."

[0361] Exam Information: "AWS Certified Solutions Architect"

[0362] Exam preparation content provided: "AWS exam question bank" and "AWS related materials"

[0363] Prompt Sentence Examples

[0364] 1. "I received the Python for Data Science course materials, what's next?"

[0365] 2. "If my learning progress is slow, how can I improve it?"

[0366] 3. "Please give me feedback on the questions I got wrong on the confirmation test."

[0367] 4. "Which test prep content is most effective?"

[0368] As described above, the online learning system of the present invention allows users to study efficiently and easily, and optimizes the learning experience through emotion recognition, thereby maximizing learning effectiveness.

[0369] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0370] Step 1:

[0371] A user accesses the learning system's website from a web browser. The user uses an information processing terminal to enter a specified URL and display the online learning system's home page. The input here is the user's action (URL input and access), and the output is the website's home page displayed on the terminal. Specifically, the web browser sends an HTTP request, and the server returns an HTTP response.

[0372] Step 2:

[0373] The user enters what they want to learn into the input form and clicks the submit button. For example, enter "data science" into the text box and submit. The input is what the user wants to learn (text data), and the output is that this data is sent to the server. Specifically, the user enters text on the keyboard and clicks the "Submit" button.

[0374] Step 3:

[0375] The server receives the learning content sent from the device and analyzes it using a natural language processing engine. The input is the text data sent by the user, and the main keywords are extracted as a result of the analysis. Specifically, the server uses an NLP engine implemented in Python to extract the keyword "data science" from the text. The output is a list of keywords.

[0376] Step 4:

[0377] The server searches the database for relevant learning courses based on the analyzed keywords. The input is the extracted keyword list, and the output is a list of learning courses retrieved from the database. The server uses SQL queries to search the MySQL database and retrieve courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science."

[0378] Step 5:

[0379] The server sends the selected course list to the user's device. The input is the list of courses, and the output is that this list is displayed on the device. Specifically, the server sends the course list in JSON format as an HTTP response, and the device receives it.

[0380] Step 6:

[0381] The terminal displays the received learning course list on the screen. The input is the course list received from the server, and the output is a list of learning courses that the user can view. Specifically, it uses JavaScript to generate HTML content and displays it to the user as a list.

[0382] Step 7:

[0383] The user selects the desired course and clicks the start button. For example, select "Python for Data Science." The input is the user's selection action, and the output is the ID of the selected course being sent to the server. Specifically, the user clicks on the course with the mouse and presses the "Start" button.

[0384] Step 8:

[0385] The server retrieves content corresponding to the user's selected learning course from the database. The input is the selected course ID, and the output is the corresponding learning material and video data. Specifically, the server retrieves learning materials and videos from the MySQL database using SQL queries.

[0386] Step 9:

[0387] The server sequentially distributes the acquired learning content to the user's device. The input is the acquired learning content, and the output is the teaching materials and videos distributed to the device. Specifically, the server sends the content as an HTTP response, and the device receives it.

[0388] Step 10:

[0389] The device displays the received learning content, allowing the user to progress through their studies. The input is the received content data, and the output is the learning materials and videos displayed to the user. Specifically, the device uses HTML and JavaScript to render the learning materials and videos and display them on the screen.

[0390] Step 11:

[0391] The device collects user emotional data from a webcam and microphone and sends it to a server. The input is the user's facial expression, voice, typing speed, etc., and the output is the transmission of the collected emotional data. Specifically, the device acquires sensor data in real time and sends it to the server via an API.

[0392] Step 12:

[0393] The server uses an emotion recognition engine to analyze the user's emotional data and provide feedback as needed. The input is the collected emotional data, and the output is feedback information. Specifically, it analyzes emotions using a TensorFlow model and adjusts the learning difficulty, such as lowering the learning difficulty, if the user is feeling stressed.

[0394] Step 13:

[0395] The server tracks the user's learning progress and provides confirmation tests at appropriate times. The input is the learning log data, and the output is the content of the confirmation test. Specifically, the server monitors the progress and generates a confirmation test when certain conditions are met.

[0396] Step 14:

[0397] The user answers the confirmation test and clicks the "Submit" button. The input is the user's test answer, and the output is the answer data sent to the server. Specifically, the user answers the questions on the screen and presses the "Submit" button.

[0398] Step 15:

[0399] The server receives the answers and grades them with an automated evaluation system. The input is the user's test answer data, and the output is the test score. Specifically, the evaluation system, implemented in Ruby, analyzes the answers and calculates the score.

[0400] Step 16:

[0401] The server generates feedback and sends it to the user's device. The input is the scoring result data, and the output is feedback information. Specifically, the server generates feedback including correct / incorrect answers and advice, and sends it to the device.

[0402] Step 17:

[0403] The device displays feedback, allowing the user to understand their level of understanding and areas for improvement. The input is feedback data, and the output is feedback that is displayed to the user. Specifically, the feedback is displayed on the screen using HTML and JavaScript.

[0404] Step 18:

[0405] The user enters exam information and clicks the submit button. For example, they enter "AWS Certified Solutions Architect." The input is the user's exam information, and the output is the data sent to the server. Specifically, the user enters text and clicks the "Submit" button.

[0406] Step 19:

[0407] The server retrieves the appropriate exam preparation content from the database based on the exam information. The input is the exam information data, and the output is the retrieved exam preparation content. Specifically, the server uses SQL queries to retrieve the relevant content.

[0408] Step 20:

[0409] The server delivers the acquired test preparation content to the user's device. The input is the test preparation content, and the output is the content delivered to the device. Specifically, the server sends the content as an HTTP response, and the device receives it.

[0410] Step 21:

[0411] The device displays the received test preparation content, which the user can use to prepare for the test. The input is the received content data, and the output is the content that is displayed to the user. Specifically, the content is rendered using HTML and JavaScript and displayed on the screen.

[0412] Step 22:

[0413] The server checks the user's communication line information and applies discounts to specific communication service users. The input is communication line information, and the output is the calculated discount price. Specifically, the server analyzes the IP address and determines whether the discount applies.

[0414] Step 23:

[0415] The server calculates the discount price and displays the price information on the terminal. The input is the discount price calculation data, and the output is the price information displayed on the terminal. Specifically, the server sends the calculation result in JSON format to the terminal, and the terminal displays it on the screen.

[0416] These are the specific processing steps of the online learning system of the present invention, which allows users to learn efficiently and easily, and also optimizes the learning experience through emotion recognition.

[0417] (Application example 2)

[0418] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0419] Online learning systems are required to not only suggest appropriate learning courses based on the user's learning content and progress and provide confirmation tests, but also to monitor the user's emotional state to optimize the learning experience. However, many current online learning systems lack the functionality to consider the user's emotional state and do not provide sufficient support to maximize learning efficiency. Furthermore, insufficient feedback and adjustment of the learning experience according to the user's emotional state leads to a decrease in users' motivation to learn and a decrease in learning effectiveness.

[0420] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a terminal for the user to input the content they want to learn, natural language processing means for receiving and analyzing the learning content input from the terminal, means for proposing an optimal learning course based on the analysis results, means for providing a confirmation test based on the user's learning progress, means for providing test preparation content to the user, means for applying discounts to specific communication service users based on communication line information, emotion recognition means for monitoring the user's emotional state and providing feedback, and means for adjusting the learning experience according to the emotional state. This makes it possible to grasp the user's emotional state in real time and provide an optimal learning experience according to that state.

[0421] "Terminal" means a device that allows a user to input what they want to learn and receive and display learning content.

[0422] A "server" is a computer system that receives, analyzes, and processes learning content sent by users.

[0423] "Natural language processing means" is a technology for analyzing text entered by a user and extracting key keywords and related information.

[0424] "Learning Course" means a series of educational content or lectures offered for User learning.

[0425] A "validation test" is a test provided to assess a user's learning progress and includes questions that measure the user's understanding.

[0426] "Exam Preparation Content" refers to study materials and practice questions that users need to pass a particular exam or certification.

[0427] "Communication line information" is data that indicates information about the Internet connection and mobile communications used by the user.

[0428] A "means for applying discounts" is a system that provides discounts on learning courses or service fees to users who meet certain conditions.

[0429] "Emotion recognition means" is a technology that detects and analyzes a user's emotional state from their facial expressions, voice, behavior, etc.

[0430] "Feedback" refers to guidance and advice provided based on a user's learning progress and emotional state.

[0431] "Means for adjusting the learning experience" refers to technology that dynamically changes the difficulty and content of a learning course depending on the user's emotional state.

[0432] This invention relates to an online learning system that inputs what a user wants to learn, suggests an optimal learning course based on that input, and monitors the user's emotional state to provide feedback.

[0433] The online learning system of the present invention consists of the following components: First, a user inputs the content they want to learn using a terminal. This terminal can be any device such as a PC, smartphone, smart glasses, or head-mounted display, and is connected to a server via a network.

[0434] The server receives the learning content sent by the user from the device and analyzes it using a natural language processing engine, which uses, for example, Google's NLU API or other common natural language analysis technologies, to extract the user's learning objectives and keywords.

[0435] The server then searches the database for the most suitable learning course based on the extracted keywords and suggests it to the user. At this stage, the server also monitors the user's learning progress and provides timely review tests and exam preparation content.

[0436] Furthermore, the system uses emotion recognition to monitor the user's emotional state in real time. This emotion recognition is achieved by analyzing the user's facial expressions, voice, typing speed, and other behavioral data. The server uses this data to determine the user's emotional state and adjust the learning experience accordingly. This technology can temporarily lower the difficulty of the learning course if the user is feeling stressed, thereby maintaining the user's motivation and efficiency in learning.

[0437] As a concrete example, consider a case where a user wants to learn "data science." In this case, the user enters the keyword "data science" into their device, and the server analyzes this keyword using a natural language processing engine. After analysis, the server suggests optimal learning courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science." When the user selects "Python for Data Science" and begins learning, the server monitors their emotional state in real time and adjusts the learning experience. It also provides confirmation tests at appropriate times according to the user's learning progress and provides feedback based on the results.

[0438] Examples of prompts to input to a generative AI model include:

[0439] "Enter what you want to learn. Include specific keywords, such as 'data science.'"

[0440] In this way, the online learning system of the present invention allows users to learn efficiently and easily, and optimizes the learning experience through emotion recognition, thereby maximizing learning effectiveness.

[0441] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0442] Step 1:

[0443] The user enters the content they wish to learn from a terminal. The user enters the text of what they want to learn into the input form on the terminal and clicks the send button. For example, they enter "data science." The entered content is sent from the terminal to the server. The input data is in text format. The output is the text data sent to the server.

[0444] Step 2:

[0445] The server receives the learning content sent from the device and analyzes it using a natural language processing engine. The input is the text data entered by the user, and the output is the extraction results of key keywords. In this process, the text data is analyzed and the keyword "data science" is extracted. Based on the analysis results, related learning courses are searched for in the database.

[0446] Step 3:

[0447] Based on the analysis results, the server generates a list of optimal learning courses and sends it to the device. The input is the extracted keywords and learning course information from the database, and the output is a list of learning courses. Specifically, it suggests courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science." The device displays the list.

[0448] Step 4:

[0449] The user selects the desired course from the suggested learning courses on the terminal and clicks the "Start" button for the selected course. The input is the learning course selection information, and the output is the selection information sent to the server. The server receives the user's selection and retrieves the learning materials for the selected course from the database.

[0450] Step 5:

[0451] The server retrieves the learning materials and videos corresponding to the learning course selected by the user and delivers them to the terminal in sequence. The input is the information about the selected learning course, and the output is the distribution data of the learning materials and videos. Specifically, the video lecture is played and the learning materials in PDF format can be downloaded.

[0452] Step 6:

[0453] The server uses emotion recognition means to monitor the user's emotional state and analyze it in real time. The input is behavioral data such as the user's facial expressions, voice, and typing speed, and the output is the analysis of the user's emotional state. The device sends this data to the server, which generates feedback based on the analysis results. For example, if the user is feeling stressed, the server will display feedback such as "Relax and continue studying."

[0454] Step 7:

[0455] The server tracks the user's learning progress and provides confirmation tests at appropriate times. The input is learning progress data, and the output is the confirmation test data. The user answers the confirmation test and sends it to the server. The server grades the test with an automatic evaluation system and returns the results to the device as feedback.

[0456] Step 8:

[0457] When a user inputs information about a specific exam or certification, the server provides the most appropriate exam preparation content based on that information. The input is the exam information, and the output is the distribution data of the exam preparation content. Specifically, preparation materials such as past exam questions and mock exams are provided.

[0458] Step 9:

[0459] The server checks the user's communication line information and applies discounts to specific communication service users. The input is communication line information, and the output is the discounted price information. The server calculates the discounted price and displays the discounted information on the terminal.

[0460] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0461] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0462] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0463] [Second embodiment]

[0464] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0465] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0466] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0467] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0468] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0469] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0470] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0471] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0472] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0473] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0474] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0475] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0476] ---

[0477] This invention relates to an online learning system using PCs and mobile devices. The system of the present invention has a terminal for inputting the content to be learned, a server that receives and analyzes the input content, a server function that proposes the optimal learning course, a server function that provides confirmation tests and test preparation content, and a server function that applies discounts based on communication line information. Each function is described in detail below.

[0478] ---

[0479] Enter what you want to learn

[0480] Users access the learning system's website from a web browser on their PC or mobile device. They enter what they want to learn into the input form on the website. For example, if they want to learn "data science," they enter that information into the form and click the submit button.

[0481] ---

[0482] Receiving and parsing input

[0483] The server receives the desired learning content sent from the device. After receiving it, it uses natural language processing to analyze the text of the input content and extracts key keywords. For example, if "data science" is input, the server analyzes this keyword and searches for related learning courses.

[0484] ---

[0485] Suggestion of the best course of study

[0486] The server searches the database for the most appropriate learning course based on the analysis results. To minimize latency, it is desirable to pre-index a large amount of learning data. It then suggests highly relevant learning courses to the user. For example, the server might display courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science" on the user's device.

[0487] ---

[0488] View and select a course

[0489] The device receives the course information sent from the server and displays it to the user. The user selects the desired course from the displayed courses and clicks the "Start" button for the course. For example, if the user selects "Python for Data Science," they click on that course.

[0490] ---

[0491] Providing learning content

[0492] The server retrieves the learning materials, videos, and exercises corresponding to the user's selected course from the database and delivers them to the user's device. The device displays the delivered content and allows the user to progress with their studies. For example, video lectures can be played and PDF learning materials can be downloaded.

[0493] ---

[0494] Providing confirmation tests

[0495] The server provides confirmation tests at appropriate times according to the user's learning progress. The tests consist of multiple choice and written questions to verify the user's level of understanding. When the user answers the confirmation test and clicks the submit button, the server receives the answers and grades them using an automated evaluation system.

[0496] ---

[0497] Providing feedback

[0498] The server generates feedback for the user based on the results of the confirmation test and sends it to the device. The device displays this feedback, allowing the user to understand their level of understanding and weak points. For example, the feedback might be, "You got 80% correct. You need to practice more on loop syntax."

[0499] ---

[0500] Providing exam preparation content

[0501] Users can input information about specific qualification exams and certification tests. The server then retrieves the appropriate test preparation content from the database and delivers it to the device. The device then displays the received test preparation content, allowing the user to use it to prepare for the exam.

[0502] ---

[0503] Discounts applied

[0504] The server checks the user's communication line information and applies discounts to users of specific communication services. For example, if a user uses a specific communication service, the server calculates the discount price and displays the discounted fee information on the terminal.

[0505] ---

[0506] In this way, the online learning system of the present invention provides an environment in which users can learn efficiently and easily, maximizing the effectiveness of their learning.

[0507] The processing flow will be explained below.

[0508] Step 1:

[0509] The user accesses the learning system website using the browser on their PC or mobile device, enters the content they want to learn into the input form, and clicks the submit button.

[0510] Step 2:

[0511] The device sends the user's input to the server, where it is temporarily stored.

[0512] Step 3:

[0513] The server uses a natural language processing engine to analyze the user's input and extract key keywords. For example, if a user inputs that they want to learn "data science," the server will extract the keyword "data science."

[0514] Step 4:

[0515] The server searches the database for relevant learning courses based on the extracted keywords, creates a list of learning courses, and selects the most suitable course for the user.

[0516] Step 5:

[0517] The server sends the selected course list to the user's terminal, which displays the received course list on the screen and allows the user to select a course.

[0518] Step 6:

[0519] The user selects the desired course from the displayed learning courses and clicks the "Start" button for the selected course. The terminal sends the selection information to the server.

[0520] Step 7:

[0521] The server retrieves the learning materials, videos, and exercises corresponding to the user's selected course from a database and delivers them to the device in sequence. The device then displays the received content, allowing the user to proceed with their learning.

[0522] Step 8:

[0523] The server tracks the user's learning progress and provides a confirmation test to the user's device at the appropriate time, which then displays the test on the screen.

[0524] Step 9:

[0525] The user takes the test and enters their answers. The device sends the answers to a server, which then grades them with an automated scoring system and generates a result.

[0526] Step 10:

[0527] The server generates feedback based on the results of the verification test and sends it to the user's device, which then displays the feedback to the user.

[0528] Step 11:

[0529] The user enters information about the qualification exam or certification exam they wish to take. The device sends the entered information to the server. The server retrieves exam preparation content from the database and distributes it to the user's device.

[0530] Step 12:

[0531] The server checks the user's communication line information and applies a discount if a specific communication service is used. The server calculates the discount price and displays the discounted fee information on the terminal.

[0532] ---

[0533] Through the above processing steps, the user can proceed with efficient and effective learning.

[0534] Example 1

[0535] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0536] In recent years, demand for online learning systems has increased, but systems that can propose optimal learning courses for individual users and respond flexibly based on their learning progress are not yet fully developed. Additional features, such as discount application based on communication line information, are also lacking. Therefore, there is a need for a system that allows users to efficiently and effectively learn the content they want to learn.

[0537] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0538] In this invention, the server includes means using a generative AI model to analyze the user's text input, means for providing a validation test based on the user's learning progress, and means for receiving the user's validation test answers and scoring them using an automated assessment system, thereby enabling personalized learning course suggestions, progress management, and discount application.

[0539] A "terminal" is a device that allows a user to input information and check the display, and includes devices such as PCs and mobile terminals.

[0540] A "server" is a computer system that receives, analyzes, stores, and transmits information over a network.

[0541] "Natural language processing means" refers to means that use technologies and algorithms to analyze input text information and understand its meaning.

[0542] A "course" is a collection of study materials, lectures, and exercises designed for a user to study.

[0543] A "confirmation test" is a multiple-choice or written test to measure a user's level of understanding.

[0544] "Exam Preparation Content" refers to study materials and practice questions designed to help students pass a particular qualification or certification exam.

[0545] "Communication line information" refers to information about the provider and contract plan of the communication service used by the user.

[0546] A "generative AI model" is a machine learning algorithm or model for natural language processing and data analysis.

[0547] An "automated evaluation system" is a system that analyzes user responses and performs mechanical evaluations.

[0548] "Feedback" is advice or instruction provided to a user based on their learning progress or test results.

[0549] This invention relates to an online learning system using PCs and mobile devices. It includes a terminal for users to input the content they want to learn, a server that receives and analyzes the input, a server that proposes the optimal learning course based on the analysis results, a server that provides confirmation tests according to learning progress, a server that provides test preparation content, and a server that applies discounts based on communication line information. Each function is described in detail below.

[0550] First, users access the learning system's website from their PC or mobile device, enter the subject they want to learn (e.g., "data science") into the input form on the website, and click the submit button.

[0551] The server then receives the desired learning content sent from the device. After receiving it, the server uses a generative AI model (e.g., the BERT model) to analyze the text of the input and extract key keywords. For example, if "data science" is input, the server analyzes this keyword and searches a database for related learning courses. This database contains data indexed using, for example, Elasticsearch.

[0552] The server searches the indexed data for the most suitable learning courses and displays the most relevant courses on the user's device. For example, it might suggest courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science." The user can select the desired course from the displayed courses and click on it.

[0553] The learning materials, videos, and exercises corresponding to the selected course are delivered from the server. This includes learning materials stored in Amazon S3, for example. Users can view the delivered content on their devices and proceed with their studies. Specifically, video lectures are played and learning materials in PDF format can be downloaded.

[0554] Furthermore, the server provides confirmation tests according to the user's learning progress. These tests include multiple-choice and essay questions to check the user's level of understanding. When the user answers the confirmation test and submits the answers, the server receives the answers and scores them using an automated evaluation system (e.g., AutoML). The server then generates feedback based on the results of the confirmation test and sends it to the device. For example, the server may provide feedback such as, "You got 80% correct. You need to practice more on loop syntax."

[0555] Users can also enter information about specific qualification exams and certification tests. Based on this, the server retrieves appropriate test preparation content from the database and delivers it to the user's device. Users can use the received test preparation content to advance their exam preparation. For example, content such as "TOEIC Preparation Course" is provided.

[0556] Finally, the server checks the user's communication line information and applies discounts to users of specific communication services. For example, if the user is using a specific communication service, the server calculates the discount price and displays the discounted fee information on the terminal.

[0557] Prompt Sentence Examples

[0558] "What are the best online courses for Python for Data Science?"

[0559] In this way, the online learning system of the present invention provides an environment in which users can study efficiently and easily, maximizing the effectiveness of their learning.

[0560] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0561] Step 1:

[0562] Users access the learning system's website from a web browser on their PC or mobile device. They enter the subject they want to learn (e.g., "data science") into the input form and click the submit button. The input is text data of the subject they want to learn, and the output is data sent to the server as an HTTP POST request.

[0563] Step 2:

[0564] The server receives an HTTP POST request from the device for the content the user wants to learn. It uses a generative AI model (e.g., the BERT model) to analyze the input text and extract key keywords. Specifically, it tokenizes the text data and applies a natural language processing algorithm to identify important words and phrases. The input is the text data of the content the user wants to learn, and the output is the analysis results (key keywords).

[0565] Step 3:

[0566] The server uses the analyzed keywords to search the database for the most suitable learning courses. This search process uses a search engine (e.g., Elasticsearch) that utilizes indexed data. Specifically, the server scores the relevance of learning courses based on the keywords and lists the most suitable courses. The input is the main keywords, and the output is a list of the most suitable learning courses.

[0567] Step 4:

[0568] The terminal receives the list of optimal learning courses sent from the server and displays it to the user. The user selects the desired course (e.g., "Python for Data Science") from the displayed courses and clicks the select button. Here, the input is the list of learning courses, and the output is the specific course selected by the user.

[0569] Step 5:

[0570] The server retrieves the learning materials, videos, and exercises corresponding to the learning course selected by the user from a database. This database is stored, for example, using a cloud storage service (e.g., Amazon S3). The retrieved content is then delivered to the user's device. The input is the selected learning course, and the output is the learning materials, videos, and exercises (specific content).

[0571] Step 6:

[0572] The device receives the distributed learning content and displays it to the user. The user watches video lectures and downloads learning materials in PDF format to progress with their studies. Here, the input is the distributed learning content, and the output is the screen display for the user to study and the downloaded learning materials.

[0573] Step 7:

[0574] The server provides a confirmation test based on the user's learning progress. Specifically, it analyzes the user's access history and study time data to generate an appropriate test. The test includes multiple-choice and essay questions and is sent to the user. The input is the user's learning progress data, and the output is the generated confirmation test.

[0575] Step 8:

[0576] The terminal receives the confirmation test sent from the server and displays it to the user. The user answers the test and clicks the send button to send the answer data to the server. The input is the confirmation test and the output is the user's test answer.

[0577] Step 9:

[0578] The server receives the user's test answers and scores them using an automated evaluation system (e.g., AutoML). Feedback is generated based on the analysis results and sent to the user's device. The feedback includes the accuracy rate and areas for improvement in learning. The input is the user's test answers, and the output is the generated feedback.

[0579] Step 10:

[0580] The device receives the feedback sent from the server and displays it to the user. The user can understand their own level of understanding and weaknesses and can revise their study plan. The input is the feedback, and the output is the displayed feedback.

[0581] Step 11:

[0582] When a user inputs information about a specific qualification or certification exam, the server searches the database for appropriate exam preparation content and delivers it to the terminal. The input is the qualification or certification exam information, and the output is the exam preparation content.

[0583] Step 12:

[0584] The terminal receives the test preparation content sent from the server and displays it to the user, who can use it to prepare for the test. The input is the test preparation content, and the output is a display for the user to use in their studies.

[0585] Step 13:

[0586] The server checks the user's communication line information and applies discounts to specific communication service users. It verifies number portability information, calculates the discount, and sends it to the terminal. The input is communication line information, and the output is discount application information.

[0587] Step 14:

[0588] The terminal receives the discount application information sent from the server and displays it to the user. The user can check the discounted price information. The input is the discount application information, and the output is the discounted price displayed to the user.

[0589] Through these steps, the online learning system provides an environment that allows users to learn efficiently and easily, maximizing learning effectiveness.

[0590] (Application example 1)

[0591] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0592] Conventional online learning systems often limit the effectiveness of learning because they make it difficult for students to learn face-to-face or engage in real-time dialogue, and require students to manage their own progress independently. Furthermore, the process of efficiently inputting the content users want to learn and selecting the most appropriate course from a variety of courses is cumbersome. Furthermore, they are unable to fully accommodate the communication status and device environment of specific students, making it difficult to provide an individually optimized learning experience. New technological solutions are needed to solve these problems.

[0593] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0594] In this invention, the server includes a terminal for a user to input content they wish to learn, natural language processing means for receiving and analyzing the learning content input from the terminal, means for the server to suggest an optimal learning course based on the analysis results, means for the server to provide a confirmation test based on the user's learning progress, means for the server to provide test preparation content to the user, means for applying discounts to specific communication service users based on communication line information, means for the user to view and operate learning content in a virtual store using smart glasses, a head-mounted display, or other display device, means for the server to input content they wish to learn through voice recognition, and means for the server to visually display an appropriate learning course in a virtual reality environment. This solves the problem of users having difficulty in self-directed learning and provides a more immersive learning experience.

[0595] "What you want to learn" refers to the learning topics or themes that users select and enter based on their learning goals or interests.

[0596] A "terminal" is an electronic device used by a user to input data or view content, including smart glasses and head-mounted displays.

[0597] "Natural language processing means" refers to technology that analyzes text data entered by users and extracts meaning and important keywords.

[0598] A "server" is a central processing unit that receives input data from users, analyzes and processes it, and returns an appropriate response.

[0599] "Optimal learning course" refers to the educational program or content that best suits the user's learning needs.

[0600] "Study progress status" is information that indicates how much progress the user has made in the course of their studies.

[0601] A "review test" is a test provided to assess what a user has learned, and includes questions to check their understanding and memory.

[0602] "Exam Preparation Content" means study materials and practice questions provided to prepare for a particular qualification or certification exam.

[0603] "Communication line information" refers to information regarding the Internet connection and data communications used by the user.

[0604] A "means for applying discounts" is a mechanism for applying discounts and reducing fees to communication service users who meet certain conditions.

[0605] A "virtual store" is a virtual space that users can access via the Internet and purchase goods and services.

[0606] "Smart glasses" are glasses-type wearable devices with display functions that can display and operate information.

[0607] A "head-mounted display" is a display device that the user wears on their head and can provide immersive images.

[0608] "Speech recognition" is a technology that converts a user's speech into text data in real time.

[0609] A "virtual reality environment" is a virtual space in which users are immersed in a computer-generated 3D space, providing a realistic experience.

[0610] The present invention aims to provide users with an immersive learning experience by incorporating a virtual reality environment into an online learning system. Specific embodiments of the present invention will be described below.

[0611] System Program

[0612] Hardware

[0613] Smart glasses: A wearable device in the form of glasses with a display function

[0614] Head-mounted display (HMD): A display device worn on the head.

[0615] Server: A central processing unit that receives, analyzes, and provides data

[0616] software

[0617] Natural Language Processing (NLP) systems: Analyze user input data and extract meaning and keywords (e.g., Google Cloud Natural Language API)

[0618] Virtual reality (VR) development platforms: Generate 3D spaces and provide interactive learning experiences (e.g., Unity 3D)

[0619] Learning Management System (LMS): Manages and delivers learning courses (e.g., Moodle)

[0620] Program processing description

[0621] 1. Enter what you want to learn

[0622] Users wear smart glasses or an HMD and voice-input what they want to learn in the virtual store.

[0623] Voice data is captured through the built-in microphone of smart glasses or HMDs and transmitted to a natural language processing system.

[0624] 2. Receiving and analyzing input

[0625] The server uses voice recognition to convert the user's voice input into text and uses a natural language processing system to extract keywords.

[0626] The server searches the learning management system for relevant learning courses based on the extracted keywords.

[0627] 3. Recommending the best course of study

[0628] The server searches for relevant learning courses and displays the results on the user's smart glasses or HMD.

[0629] Users can select the most appropriate course from the displayed list and begin learning.

[0630] 4. Offering study courses

[0631] The server sequentially delivers teaching materials and videos based on the course selected by the user.

[0632] Users can learn in a virtual reality environment through smart glasses or an HMD.

[0633] 5. Testing and Providing Feedback

[0634] The server provides confirmation tests according to learning progress and scores the user's answers with an automated evaluation system.

[0635] Feedback is generated based on the results and displayed on the user's device.

[0636] 6. Provision of exam preparation content

[0637] When a user inputs the content they need to prepare for a specific exam, the server searches for and provides the preparation content based on that information.

[0638] 7. Discount Application

[0639] The server checks the user's communication line information and applies discounts to users of specific communication services.

[0640] Specific examples

[0641] 1. User A puts on the smart glasses and says, "I want to learn Python."

[0642] 2. The server recognizes "Python" as a keyword and suggests the related courses "Python for Data Science" and "Advanced Python."

[0643] 3. User A selects "Python for Data Science" and watches the course materials and videos in a virtual reality environment.

[0644] 4. During the learning process, the server provides a confirmation test, and after completion, feedback such as "You got 80% correct. You need more practice on loop syntax" is displayed.

[0645] Prompt Sentence Examples

[0646] Simulate a system that suggests learning content to users through voice control in a virtual learning salon. If a user types "I want to learn Python," explain what courses would be suggested and what learning content would be provided. Also, describe the technical implementation of the system.

[0647] This allows users to study in a virtual reality environment, providing a greater sense of immersion and learning effectiveness than traditional online learning systems.

[0648] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0649] Step 1:

[0650] Users wear smart glasses or a head-mounted display (HMD) and voice-input what they want to learn in the virtual store.

[0651] Input: User speech (e.g., "I want to learn Python")

[0652] How it works: Audio data is captured through the smart gadget's built-in microphone.

[0653] Output: Audio data is generated.

[0654] Step 2:

[0655] The server uses voice recognition to convert the user's voice input into text data.

[0656] Input: Audio data

[0657] How it works: The server uses a speech recognition engine (e.g., Google Cloud Speech-to-Text) to convert the audio data into text.

[0658] Output: Text data (e.g., "I want to learn Python")

[0659] Step 3:

[0660] The server analyzes the text data using natural language processing (NLP) and extracts keywords.

[0661] Input: Text data

[0662] How it works: The server uses a natural language processing engine (e.g., Google Cloud Natural Language API) to analyze the input text. The analysis extracts key keywords.

[0663] Output: Extracted keywords (e.g. "Python")

[0664] Step 4:

[0665] The server searches for relevant learning courses from a learning management system (LMS) based on the extracted keywords.

[0666] Input: Extracted keywords

[0667] How it works: The server searches the LMS database for learning courses related to the extracted keywords.

[0668] Output: A list of related learning courses (e.g., "Python for Data Science," "Advanced Python")

[0669] Step 5:

[0670] The server displays the search results on the user's smart glasses or HMD.

[0671] Input: A list of related courses

[0672] How it works: The server uses a virtual reality (VR) development platform (e.g. Unity 3D) to visually display the results on the user's smart gadget.

[0673] Output: A list of displayed courses

[0674] Step 6:

[0675] The user selects from the displayed learning courses and begins learning.

[0676] Input: Select a course of study (e.g., "Python for Data Science")

[0677] Operation: The user selects the desired course using the operation interface of the smart gadget and sends the selection information to the server.

[0678] Output: Information about the course selected by the user

[0679] Step 7:

[0680] The server delivers teaching materials and videos sequentially based on the course selected by the user.

[0681] Input: Course information selected by the user

[0682] How it works: The server retrieves the learning materials and videos corresponding to the selected course from the LMS and sends them to the user's smart gadget.

[0683] Output: Delivered learning materials and videos

[0684] Step 8:

[0685] Users can view educational materials and videos and progress through their studies in a virtual reality environment.

[0686] Input: Delivered learning materials and videos

[0687] How it works: Users view and interact with learning content in a virtual reality environment through smart glasses or an HMD.

[0688] Output: Learning progress data

[0689] Step 9:

[0690] The server provides confirmation tests according to the learning progress, and the user's answers are scored by an automated evaluation system.

[0691] Input: Learning progress data

[0692] How it works: The server provides a prompt at the appropriate time and automatically scores the user's answers.

[0693] Output: Verification test results

[0694] Step 10:

[0695] The server generates feedback based on the results of the validation test and displays it on the user's smart gadget.

[0696] Input: Verification test result

[0697] How it works: The server generates feedback and displays it to the user, showing their progress and suggesting areas for improvement.

[0698] Output: Feedback information (e.g., "You got it 80% right. You need more practice with loop syntax.")

[0699] Step 11:

[0700] Users input the content they need to prepare for a specific exam, and the server searches for and provides the preparation content based on that information.

[0701] Input: Test preparation input (e.g., "Data Science Certification Exam")

[0702] How it works: The server retrieves relevant test preparation content from the LMS and delivers it to the user's smart gadget.

[0703] Output: Provided exam prep content

[0704] Step 12:

[0705] The server checks the user's communication line information and applies discounts to users of specific communication services.

[0706] Input: Communication line information

[0707] How it works: The server analyzes the line information, calculates the applicable discounts, and notifies the user.

[0708] Output: Discount information

[0709] Through the above steps, the present invention can provide users with an efficient and effective learning environment.

[0710] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0711] ---

[0712] This invention relates to an online learning system using PCs and mobile devices. The system of the present invention includes a terminal for inputting the content to be learned, a server that receives and analyzes the input content, a server function for proposing optimal learning courses, a server function for providing confirmation tests and exam preparation content, a server function for applying discounts based on communication line information, and an emotion engine that recognizes the user's emotions. Each function is described in detail below.

[0713] ---

[0714] Input and analyze what you want to learn

[0715] Users access the learning system's website from a web browser on their PC or mobile device. They enter what they want to learn into the input form on the website. For example, if they want to learn "data science," they enter that information into the form and click the submit button.

[0716] The server receives the desired learning content sent from the device and analyzes the text using a natural language processing engine. It extracts key keywords and searches the database for relevant learning courses based on those keywords. For example, if the keyword "data science" is entered, the server will pick up courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science."

[0717] ---

[0718] Course suggestions and selection

[0719] The server sends the selected course list to the user's device, which then displays the list on the screen. The user selects the desired course from the displayed courses and clicks the "Start" button for the selected course. For example, if the user selects "Python for Data Science," they click on that course.

[0720] ---

[0721] Providing learning content and an emotional engine

[0722] The server retrieves the learning materials, videos, and exercises corresponding to the user's selected course from the database and delivers them to the device. The device displays the received content, allowing the user to proceed with their learning. For example, a video lecture can be played and PDF learning materials can be downloaded.

[0723] At the same time, the device uses an emotion engine to monitor the user's state and provide feedback and content accordingly. The device collects the user's facial expressions, voice, typing speed, and other behavioral data and sends it to the server. The server uses this data to analyze the user's emotional state and makes adjustments such as temporarily lowering the difficulty of the learning course if the user is feeling stressed.

[0724] ---

[0725] Providing confirmation tests and feedback

[0726] The server tracks the user's learning progress and provides confirmation tests at appropriate times. The tests consist of multiple choice and written questions to verify the user's level of understanding. When the user answers the confirmation test and clicks the submit button, the server receives the answers and grades them using an automated evaluation system.

[0727] The server generates feedback for the user based on the results of the confirmation test and sends it to the device. The device displays this feedback, allowing the user to understand their level of understanding and weak points. For example, the feedback might be, "You got 80% right. You need more practice with loop syntax."

[0728] ---

[0729] Providing exam preparation content

[0730] Users can input information about specific qualification exams or certification tests. Based on the entered exam information, the server retrieves appropriate exam preparation content from a database and delivers it to the device. The device then displays the received exam preparation content, allowing users to use it to prepare for the exam.

[0731] ---

[0732] Discounts applied

[0733] The server checks the user's communication line information and applies discounts to users of specific communication services. For example, if a user uses a specific communication service, the server calculates the discount price and displays the discounted fee information on the terminal.

[0734] ---

[0735] In this way, the online learning system of the present invention allows users to learn efficiently and easily, and optimizes the learning experience through emotion recognition, thereby providing an environment that maximizes learning effectiveness.

[0736] The processing flow will be explained below.

[0737] Step 1:

[0738] The user accesses the learning system website using the browser on their PC or mobile device, enters the content they want to learn into the input form, and clicks the submit button.

[0739] Step 2:

[0740] The device sends the user's input to the server, where it is temporarily stored.

[0741] Step 3:

[0742] The server uses a natural language processing engine to analyze the user's input and extract key keywords. For example, if a user inputs that they want to learn "data science," the server will extract the keyword "data science."

[0743] Step 4:

[0744] The server searches the database for relevant learning courses based on the extracted keywords, creates a list of learning courses, and selects the most suitable course for the user.

[0745] Step 5:

[0746] The server sends the selected course list to the user's device, which then displays the received course list on the screen for the user to select.

[0747] Step 6:

[0748] The user selects the desired course from the displayed learning courses and clicks the "Start" button for the selected course. The terminal sends the selection information to the server.

[0749] Step 7:

[0750] The server retrieves the learning materials, videos, and exercises corresponding to the user's selected course from a database and delivers them to the device in sequence. The device then displays the received content, allowing the user to proceed with their learning.

[0751] Step 8:

[0752] The device uses an emotion engine to collect the user's facial expression, voice, typing speed and other behavioral data, and then transmits the collected emotion data to the server.

[0753] Step 9:

[0754] The server analyzes the received emotional data and recognizes the user's learning state. If the user is feeling stressed, the difficulty level of the learning course and the presentation method will be adjusted.

[0755] Step 10:

[0756] The server tracks the user's learning progress and provides confirmation tests at appropriate times, which are then displayed on the device's screen.

[0757] Step 11:

[0758] The user takes the test and enters their answers. The device sends the answers to a server, which then grades them with an automated scoring system and generates a result.

[0759] Step 12:

[0760] The server generates feedback based on the results of the verification test and sends it to the user's device, which then displays the feedback to the user.

[0761] Step 13:

[0762] The user enters information about the qualification exam or certification exam they wish to take. The device sends the entered information to the server. The server retrieves exam preparation content from the database and distributes it to the user's device.

[0763] Step 14:

[0764] The server checks the user's communication line information and applies a discount if a specific communication service is used. The server calculates the discount price and displays the discounted fee information on the terminal.

[0765] Example 2

[0766] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0767] While conventional online learning systems offer basic functions such as providing optimal learning courses based on the content users input as they wish to learn, providing confirmation tests, and providing exam preparation content, they lack more advanced personalized learning support, such as optimizing the learning experience by taking into account the user's emotional state or applying discounts based on communication line information. This makes it difficult to maximize learning effectiveness and maintain motivation to learn.

[0768] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0769] In this invention, the server includes an information processing terminal for inputting content that the user wants to learn, natural language processing engine means for receiving and analyzing the learning content input from the terminal, means for the information processing device having a function of suggesting an optimal learning course based on the analysis results, means for the information processing device having a function of providing a confirmation test based on the user's learning progress, means for the information processing device having a function of providing test preparation content to the user, emotion recognition engine means for the information processing device having a function of monitoring the user's emotional state and optimizing the learning experience, and means for applying discounts to specific communication service users based on communication line information. This allows users to be provided with more highly personalized learning support, maximizing learning effectiveness and maintaining motivation to learn.

[0770] "User" refers to an individual or corporation that uses the online learning system to input what they want to learn and receive learning content.

[0771] "Information processing terminal" refers to a computer or mobile terminal that allows users to input study content and display study courses and content.

[0772] "Information processing device" refers to servers and cloud computing resources that handle all aspects of the learning system, such as receiving and analyzing the content to be learned, proposing learning courses, providing confirmation tests, and providing exam preparation content.

[0773] A "natural language processing engine" refers to a software engine that analyzes the text data of the learning content entered by the user and extracts important keywords.

[0774] "Study course suggestion function" refers to a function that suggests the most suitable study course to the user based on the results of analysis by the natural language processing engine.

[0775] "Confirmation test provision function" refers to a function for providing confirmation tests at appropriate times based on the user's learning progress.

[0776] "Exam preparation content provision function" refers to a function that provides users with appropriate exam preparation content based on the exam information entered by the user.

[0777] An "emotion recognition engine" is an engine that analyzes a user's facial expressions, voice, and behavioral data to recognize their emotional state and optimize the learning experience.

[0778] "Communication line information" refers to information about the internet line and communication services used by the user.

[0779] The "discount application function" refers to a function for applying a discount to a specific communication service user based on communication line information.

[0780] The present invention relates to an online learning system that includes an information processing terminal used by a user, an information processing device having a natural language processing engine, an emotion recognition engine, and a discount application function based on communication line information. The following describes in detail an embodiment of the present invention.

[0781] Input and analyze what you want to learn

[0782] Users access the online learning system using a web browser on an information processing device such as a PC or mobile device. They enter what they want to learn into the input form on the website and click the submit button. For example, they might enter "data science." The information processing device analyzes the input text using a natural language processing engine implemented in Python and extracts key keywords. The information processing device then searches for related learning courses in a MySQL database and suggests the most suitable course.

[0783] Course suggestions and selection

[0784] The information processing device sends a list of learning courses to be suggested to the user to the information processing terminal. The terminal uses JavaScript to display the list of learning courses on the screen. The user selects the desired course from the displayed course and clicks the start button. For example, the user selects "Python for Data Science."

[0785] Providing learning content and an emotional engine

[0786] The information processing device retrieves content related to the learning course selected by the user from a database and sequentially delivers it to the user's device. The device displays the received content in HTML format, allowing the user to proceed with their learning. For example, video lectures may be played and learning materials in PDF format may be available for download. The device also collects the user's emotional data from the webcam and microphone and transmits it to the server in real time. The information processing device analyzes the user's emotional state using an emotion recognition engine based on TensorFlow and provides feedback, such as adjusting the difficulty of the learning content, if the user is feeling stressed.

[0787] Providing confirmation tests and feedback

[0788] The information processing device tracks the user's learning progress and provides confirmation tests at appropriate times. The user answers the confirmation test and clicks the submit button. The information processing device receives the answers and scores them using an automated evaluation system implemented in Ruby. Feedback is generated based on the scoring results and sent to the device. The device displays the feedback on the screen, allowing the user to understand their level of understanding and areas for improvement.

[0789] Providing exam preparation content

[0790] Users can input specific exam information, for example, "AWS Certified Solutions Architect." The information processing device retrieves appropriate exam preparation content from a database based on that information and delivers it to the user's device. The device then displays the received content in HTML format, allowing the user to continue preparing for the exam.

[0791] Discounts applied

[0792] The information processing device checks the user's communication line information and applies a discount to users of a specific communication service. For example, if the user is a subscriber of a specific communication carrier, the information processing device calculates the discount price and transmits the fee information to the terminal. The terminal displays the discount information on its screen.

[0793] Examples of concrete examples and prompts

[0794] Specific examples

[0795] Learning content: "Data Science"

[0796] Suggested courses: "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science."

[0797] Course selected: "Python for Data Science"

[0798] Learning content: video lectures, PDF materials

[0799] Test result: "80% correct. I need more practice with loop syntax."

[0800] Exam Information: "AWS Certified Solutions Architect"

[0801] Exam preparation content provided: "AWS exam question bank" and "AWS related materials"

[0802] Prompt Sentence Examples

[0803] 1. "I received the Python for Data Science course materials, what's next?"

[0804] 2. "If my learning progress is slow, how can I improve it?"

[0805] 3. "Please give me feedback on the questions I got wrong on the confirmation test."

[0806] 4. "Which test prep content is most effective?"

[0807] As described above, the online learning system of the present invention allows users to study efficiently and easily, and optimizes the learning experience through emotion recognition, thereby maximizing learning effectiveness.

[0808] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0809] Step 1:

[0810] A user accesses the learning system's website from a web browser. The user uses an information processing terminal to enter a specified URL and display the online learning system's home page. The input here is the user's action (URL input and access), and the output is the website's home page displayed on the terminal. Specifically, the web browser sends an HTTP request, and the server returns an HTTP response.

[0811] Step 2:

[0812] The user enters what they want to learn into the input form and clicks the submit button. For example, enter "data science" into the text box and submit. The input is what the user wants to learn (text data), and the output is that this data is sent to the server. Specifically, the user enters text on the keyboard and clicks the "Submit" button.

[0813] Step 3:

[0814] The server receives the learning content sent from the device and analyzes it using a natural language processing engine. The input is the text data sent by the user, and the main keywords are extracted as a result of the analysis. Specifically, the server uses an NLP engine implemented in Python to extract the keyword "data science" from the text. The output is a list of keywords.

[0815] Step 4:

[0816] The server searches the database for relevant learning courses based on the analyzed keywords. The input is the extracted keyword list, and the output is a list of learning courses retrieved from the database. The server uses SQL queries to search the MySQL database and retrieve courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science."

[0817] Step 5:

[0818] The server sends the selected course list to the user's device. The input is the list of courses, and the output is that this list is displayed on the device. Specifically, the server sends the course list in JSON format as an HTTP response, and the device receives it.

[0819] Step 6:

[0820] The terminal displays the received learning course list on the screen. The input is the course list received from the server, and the output is a list of learning courses that the user can view. Specifically, it uses JavaScript to generate HTML content and displays it to the user as a list.

[0821] Step 7:

[0822] The user selects the desired course and clicks the start button. For example, select "Python for Data Science." The input is the user's selection action, and the output is the ID of the selected course being sent to the server. Specifically, the user clicks on the course with the mouse and presses the "Start" button.

[0823] Step 8:

[0824] The server retrieves content corresponding to the user's selected learning course from the database. The input is the selected course ID, and the output is the corresponding learning material and video data. Specifically, the server retrieves learning materials and videos from the MySQL database using SQL queries.

[0825] Step 9:

[0826] The server sequentially distributes the acquired learning content to the user's device. The input is the acquired learning content, and the output is the teaching materials and videos distributed to the device. Specifically, the server sends the content as an HTTP response, and the device receives it.

[0827] Step 10:

[0828] The device displays the received learning content, allowing the user to progress through their studies. The input is the received content data, and the output is the learning materials and videos displayed to the user. Specifically, the device uses HTML and JavaScript to render the learning materials and videos and display them on the screen.

[0829] Step 11:

[0830] The device collects user emotional data from a webcam and microphone and sends it to a server. The input is the user's facial expression, voice, typing speed, etc., and the output is the transmission of the collected emotional data. Specifically, the device acquires sensor data in real time and sends it to the server via an API.

[0831] Step 12:

[0832] The server uses an emotion recognition engine to analyze the user's emotional data and provide feedback as needed. The input is the collected emotional data, and the output is feedback information. Specifically, it analyzes emotions using a TensorFlow model and adjusts the learning difficulty, such as lowering the learning difficulty, if the user is feeling stressed.

[0833] Step 13:

[0834] The server tracks the user's learning progress and provides confirmation tests at appropriate times. The input is the learning log data, and the output is the content of the confirmation test. Specifically, the server monitors the progress and generates a confirmation test when certain conditions are met.

[0835] Step 14:

[0836] The user answers the confirmation test and clicks the "Submit" button. The input is the user's test answer, and the output is the answer data sent to the server. Specifically, the user answers the questions on the screen and presses the "Submit" button.

[0837] Step 15:

[0838] The server receives the answers and grades them with an automated evaluation system. The input is the user's test answer data, and the output is the test score. Specifically, the evaluation system, implemented in Ruby, analyzes the answers and calculates the score.

[0839] Step 16:

[0840] The server generates feedback and sends it to the user's device. The input is the scoring result data, and the output is feedback information. Specifically, the server generates feedback including correct / incorrect answers and advice, and sends it to the device.

[0841] Step 17:

[0842] The device displays feedback, allowing the user to understand their level of understanding and areas for improvement. The input is feedback data, and the output is feedback that is displayed to the user. Specifically, the feedback is displayed on the screen using HTML and JavaScript.

[0843] Step 18:

[0844] The user enters exam information and clicks the submit button. For example, they enter "AWS Certified Solutions Architect." The input is the user's exam information, and the output is the data sent to the server. Specifically, the user enters text and clicks the "Submit" button.

[0845] Step 19:

[0846] The server retrieves the appropriate exam preparation content from the database based on the exam information. The input is the exam information data, and the output is the retrieved exam preparation content. Specifically, the server uses SQL queries to retrieve the relevant content.

[0847] Step 20:

[0848] The server delivers the acquired test preparation content to the user's device. The input is the test preparation content, and the output is the content delivered to the device. Specifically, the server sends the content as an HTTP response, and the device receives it.

[0849] Step 21:

[0850] The device displays the received test preparation content, which the user can use to prepare for the test. The input is the received content data, and the output is the content that is displayed to the user. Specifically, the content is rendered using HTML and JavaScript and displayed on the screen.

[0851] Step 22:

[0852] The server checks the user's communication line information and applies discounts to specific communication service users. The input is communication line information, and the output is the calculated discount price. Specifically, the server analyzes the IP address and determines whether the discount applies.

[0853] Step 23:

[0854] The server calculates the discount price and displays the price information on the terminal. The input is the discount price calculation data, and the output is the price information displayed on the terminal. Specifically, the server sends the calculation result in JSON format to the terminal, and the terminal displays it on the screen.

[0855] These are the specific processing steps of the online learning system of the present invention, which allows users to learn efficiently and easily, and also optimizes the learning experience through emotion recognition.

[0856] (Application example 2)

[0857] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0858] Online learning systems are required to not only suggest appropriate learning courses based on the user's learning content and progress and provide confirmation tests, but also to monitor the user's emotional state to optimize the learning experience. However, many current online learning systems lack the functionality to consider the user's emotional state and do not provide sufficient support to maximize learning efficiency. Furthermore, insufficient feedback and adjustment of the learning experience according to the user's emotional state leads to a decrease in users' motivation to learn and a decrease in learning effectiveness.

[0859] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a terminal for the user to input the content they want to learn, natural language processing means for receiving and analyzing the learning content input from the terminal, means for proposing an optimal learning course based on the analysis results, means for providing a confirmation test based on the user's learning progress, means for providing test preparation content to the user, means for applying discounts to specific communication service users based on communication line information, emotion recognition means for monitoring the user's emotional state and providing feedback, and means for adjusting the learning experience according to the emotional state. This makes it possible to grasp the user's emotional state in real time and provide an optimal learning experience according to that state.

[0860] "Terminal" means a device that allows a user to input what they want to learn and receive and display learning content.

[0861] A "server" is a computer system that receives, analyzes, and processes learning content sent by users.

[0862] "Natural language processing means" is a technology for analyzing text entered by a user and extracting key keywords and related information.

[0863] "Learning Course" means a series of educational content or lectures offered for User learning.

[0864] A "validation test" is a test provided to assess a user's learning progress and includes questions that measure the user's understanding.

[0865] "Exam Preparation Content" refers to study materials and practice questions that users need to pass a particular exam or certification.

[0866] "Communication line information" is data that indicates information about the Internet connection and mobile communications used by the user.

[0867] A "means for applying discounts" is a system that provides discounts on learning courses or service fees to users who meet certain conditions.

[0868] "Emotion recognition means" is a technology that detects and analyzes a user's emotional state from their facial expressions, voice, behavior, etc.

[0869] "Feedback" refers to guidance and advice provided based on a user's learning progress and emotional state.

[0870] "Means for adjusting the learning experience" refers to technology that dynamically changes the difficulty and content of a learning course depending on the user's emotional state.

[0871] This invention relates to an online learning system that inputs what a user wants to learn, suggests an optimal learning course based on that input, and monitors the user's emotional state to provide feedback.

[0872] The online learning system of the present invention consists of the following components: First, a user inputs the content they want to learn using a terminal. This terminal can be any device such as a PC, smartphone, smart glasses, or head-mounted display, and is connected to a server via a network.

[0873] The server receives the learning content sent by the user from the device and analyzes it using a natural language processing engine, which uses, for example, Google's NLU API or other common natural language analysis technologies, to extract the user's learning objectives and keywords.

[0874] The server then searches the database for the most suitable learning course based on the extracted keywords and suggests it to the user. At this stage, the server also monitors the user's learning progress and provides timely review tests and exam preparation content.

[0875] Furthermore, the system uses emotion recognition to monitor the user's emotional state in real time. This emotion recognition is achieved by analyzing the user's facial expressions, voice, typing speed, and other behavioral data. The server uses this data to determine the user's emotional state and adjust the learning experience accordingly. This technology can temporarily lower the difficulty of the learning course if the user is feeling stressed, thereby maintaining the user's motivation and efficiency in learning.

[0876] As a concrete example, consider a case where a user wants to learn "data science." In this case, the user enters the keyword "data science" into their device, and the server analyzes this keyword using a natural language processing engine. After analysis, the server suggests optimal learning courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science." When the user selects "Python for Data Science" and begins learning, the server monitors their emotional state in real time and adjusts the learning experience. It also provides confirmation tests at appropriate times according to the user's learning progress and provides feedback based on the results.

[0877] Examples of prompts to input to a generative AI model include:

[0878] "Enter what you want to learn. Include specific keywords, such as 'data science.'"

[0879] In this way, the online learning system of the present invention allows users to learn efficiently and easily, and optimizes the learning experience through emotion recognition, thereby maximizing learning effectiveness.

[0880] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0881] Step 1:

[0882] The user enters the content they wish to learn from a terminal. The user enters the text of what they want to learn into the input form on the terminal and clicks the send button. For example, they enter "data science." The entered content is sent from the terminal to the server. The input data is in text format. The output is the text data sent to the server.

[0883] Step 2:

[0884] The server receives the learning content sent from the device and analyzes it using a natural language processing engine. The input is the text data entered by the user, and the output is the extraction results of key keywords. In this process, the text data is analyzed and the keyword "data science" is extracted. Based on the analysis results, related learning courses are searched for in the database.

[0885] Step 3:

[0886] Based on the analysis results, the server generates a list of optimal learning courses and sends it to the device. The input is the extracted keywords and learning course information from the database, and the output is a list of learning courses. Specifically, it suggests courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science." The device displays the list.

[0887] Step 4:

[0888] The user selects the desired course from the suggested learning courses on the terminal and clicks the "Start" button for the selected course. The input is the learning course selection information, and the output is the selection information sent to the server. The server receives the user's selection and retrieves the learning materials for the selected course from the database.

[0889] Step 5:

[0890] The server retrieves the learning materials and videos corresponding to the learning course selected by the user and delivers them to the terminal in sequence. The input is the information about the selected learning course, and the output is the distribution data of the learning materials and videos. Specifically, the video lecture is played and the learning materials in PDF format can be downloaded.

[0891] Step 6:

[0892] The server uses emotion recognition means to monitor the user's emotional state and analyze it in real time. The input is behavioral data such as the user's facial expressions, voice, and typing speed, and the output is the analysis of the user's emotional state. The device sends this data to the server, which generates feedback based on the analysis results. For example, if the user is feeling stressed, the server will display feedback such as "Relax and continue studying."

[0893] Step 7:

[0894] The server tracks the user's learning progress and provides confirmation tests at appropriate times. The input is learning progress data, and the output is the confirmation test data. The user answers the confirmation test and sends it to the server. The server grades the test with an automatic evaluation system and returns the results to the device as feedback.

[0895] Step 8:

[0896] When a user inputs information about a specific exam or certification, the server provides the most appropriate exam preparation content based on that information. The input is the exam information, and the output is the distribution data of the exam preparation content. Specifically, preparation materials such as past exam questions and mock exams are provided.

[0897] Step 9:

[0898] The server checks the user's communication line information and applies discounts to specific communication service users. The input is communication line information, and the output is the discounted price information. The server calculates the discounted price and displays the discounted information on the terminal.

[0899] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0900] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0901] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0902] [Third embodiment]

[0903] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0904] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0905] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0906] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0907] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0908] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0909] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0910] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0911] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0912] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0913] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0914] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0915] ---

[0916] This invention relates to an online learning system using PCs and mobile devices. The system of the present invention has a terminal for inputting the content to be learned, a server that receives and analyzes the input content, a server function that proposes the optimal learning course, a server function that provides confirmation tests and test preparation content, and a server function that applies discounts based on communication line information. Each function is described in detail below.

[0917] ---

[0918] Enter what you want to learn

[0919] Users access the learning system's website from a web browser on their PC or mobile device. They enter what they want to learn into the input form on the website. For example, if they want to learn "data science," they enter that information into the form and click the submit button.

[0920] ---

[0921] Receiving and parsing input

[0922] The server receives the desired learning content sent from the device. After receiving it, it uses natural language processing to analyze the text of the input content and extracts key keywords. For example, if "data science" is input, the server analyzes this keyword and searches for related learning courses.

[0923] ---

[0924] Suggestion of the best course of study

[0925] The server searches the database for the most appropriate learning course based on the analysis results. To minimize latency, it is desirable to pre-index a large amount of learning data. It then suggests highly relevant learning courses to the user. For example, the server might display courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science" on the user's device.

[0926] ---

[0927] View and select study paths

[0928] The device receives the course information sent from the server and displays it to the user. The user selects the desired course from the displayed courses and clicks the "Start" button for the course. For example, if the user selects "Python for Data Science," they click on that course.

[0929] ---

[0930] Providing learning content

[0931] The server retrieves the learning materials, videos, and exercises corresponding to the user's selected course from the database and delivers them to the user's device. The device displays the delivered content and allows the user to progress with their studies. For example, video lectures can be played and PDF learning materials can be downloaded.

[0932] ---

[0933] Providing confirmation tests

[0934] The server provides confirmation tests at appropriate times according to the user's learning progress. The tests consist of multiple choice and written questions to verify the user's level of understanding. When the user answers the confirmation test and clicks the submit button, the server receives the answers and grades them using an automated evaluation system.

[0935] ---

[0936] Providing feedback

[0937] The server generates feedback for the user based on the results of the confirmation test and sends it to the device. The device displays this feedback, allowing the user to understand their level of understanding and weak points. For example, the feedback might be, "You got 80% correct. You need to practice more on loop syntax."

[0938] ---

[0939] Providing exam preparation content

[0940] Users can input information about specific qualification exams and certification tests. The server then retrieves the appropriate test preparation content from the database and delivers it to the device. The device then displays the received test preparation content, allowing the user to use it to prepare for the exam.

[0941] ---

[0942] Discounts applied

[0943] The server checks the user's communication line information and applies discounts to users of specific communication services. For example, if a user uses a specific communication service, the server calculates the discount price and displays the discounted fee information on the terminal.

[0944] ---

[0945] In this way, the online learning system of the present invention provides an environment in which users can learn efficiently and easily, maximizing the effectiveness of their learning.

[0946] The processing flow will be explained below.

[0947] Step 1:

[0948] The user accesses the learning system website using the browser on their PC or mobile device, enters the content they want to learn into the input form, and clicks the submit button.

[0949] Step 2:

[0950] The device sends the user's input to the server, where it is temporarily stored.

[0951] Step 3:

[0952] The server uses a natural language processing engine to analyze the user's input and extract key keywords. For example, if a user inputs that they want to learn "data science," the server will extract the keyword "data science."

[0953] Step 4:

[0954] The server searches the database for relevant learning courses based on the extracted keywords, creates a list of learning courses, and selects the most suitable course for the user.

[0955] Step 5:

[0956] The server sends the selected course list to the user's terminal, which displays the received course list on the screen and allows the user to select a course.

[0957] Step 6:

[0958] The user selects the desired course from the displayed learning courses and clicks the "Start" button for the selected course. The terminal sends the selection information to the server.

[0959] Step 7:

[0960] The server retrieves the learning materials, videos, and exercises corresponding to the user's selected course from a database and delivers them to the device in sequence. The device then displays the received content, allowing the user to proceed with their learning.

[0961] Step 8:

[0962] The server tracks the user's learning progress and provides a confirmation test to the user's device at the appropriate time, which then displays the test on the screen.

[0963] Step 9:

[0964] The user takes the test and enters their answers. The device sends the answers to a server, which then grades them with an automated scoring system and generates a result.

[0965] Step 10:

[0966] The server generates feedback based on the results of the verification test and sends it to the user's device, which then displays the feedback to the user.

[0967] Step 11:

[0968] The user enters information about the qualification exam or certification exam they wish to take. The device sends the entered information to the server. The server retrieves exam preparation content from the database and distributes it to the user's device.

[0969] Step 12:

[0970] The server checks the user's communication line information and applies a discount if a specific communication service is used. The server calculates the discount price and displays the discounted fee information on the terminal.

[0971] ---

[0972] Through the above processing steps, the user can proceed with efficient and effective learning.

[0973] Example 1

[0974] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0975] In recent years, demand for online learning systems has increased, but systems that can propose optimal learning courses for individual users and respond flexibly based on their learning progress are not yet fully developed. Additional features, such as discount application based on communication line information, are also lacking. Therefore, there is a need for a system that allows users to efficiently and effectively learn the content they want to learn.

[0976] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0977] In this invention, the server includes means using a generative AI model to analyze the user's text input, means for providing a validation test based on the user's learning progress, and means for receiving the user's validation test answers and scoring them using an automated assessment system, thereby enabling personalized learning course suggestions, progress management, and discount application.

[0978] A "terminal" is a device that allows a user to input information and check the display, and includes devices such as PCs and mobile terminals.

[0979] A "server" is a computer system that receives, analyzes, stores, and transmits information over a network.

[0980] "Natural language processing means" refers to means that use technologies and algorithms to analyze input text information and understand its meaning.

[0981] A "course" is a collection of study materials, lectures, and exercises designed for a user to study.

[0982] A "confirmation test" is a multiple-choice or written test to measure a user's level of understanding.

[0983] "Exam Preparation Content" refers to study materials and practice questions designed to help students pass a particular qualification or certification exam.

[0984] "Communication line information" refers to information about the provider and contract plan of the communication service used by the user.

[0985] A "generative AI model" is a machine learning algorithm or model for natural language processing and data analysis.

[0986] An "automated evaluation system" is a system that analyzes user responses and performs mechanical evaluations.

[0987] "Feedback" is advice or instruction provided to a user based on their learning progress or test results.

[0988] This invention relates to an online learning system using PCs and mobile devices. It includes a terminal for users to input the content they want to learn, a server that receives and analyzes the input, a server that proposes the optimal learning course based on the analysis results, a server that provides confirmation tests according to learning progress, a server that provides test preparation content, and a server that applies discounts based on communication line information. Each function is described in detail below.

[0989] First, users access the learning system's website from their PC or mobile device, enter the subject they want to learn (e.g., "data science") into the input form on the website, and click the submit button.

[0990] The server then receives the desired learning content sent from the device. After receiving it, the server uses a generative AI model (e.g., the BERT model) to analyze the text of the input and extract key keywords. For example, if "data science" is input, the server analyzes this keyword and searches a database for related learning courses. This database contains data indexed using, for example, Elasticsearch.

[0991] The server searches the indexed data for the most suitable learning courses and displays the most relevant courses on the user's device. For example, it might suggest courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science." The user can select the desired course from the displayed courses and click on it.

[0992] The learning materials, videos, and exercises corresponding to the selected course are delivered from the server. This includes learning materials stored in Amazon S3, for example. Users can view the delivered content on their devices and proceed with their studies. Specifically, video lectures are played and learning materials in PDF format can be downloaded.

[0993] Furthermore, the server provides confirmation tests according to the user's learning progress. These tests include multiple-choice and essay questions to check the user's level of understanding. When the user answers the confirmation test and submits the answers, the server receives the answers and scores them using an automated evaluation system (e.g., AutoML). The server then generates feedback based on the results of the confirmation test and sends it to the device. For example, the server may provide feedback such as, "You got 80% correct. You need to practice more on loop syntax."

[0994] Users can also enter information about specific qualification exams and certification tests. Based on this, the server retrieves appropriate test preparation content from the database and delivers it to the user's device. Users can use the received test preparation content to advance their exam preparation. For example, content such as "TOEIC Preparation Course" is provided.

[0995] Finally, the server checks the user's communication line information and applies discounts to users of specific communication services. For example, if the user is using a specific communication service, the server calculates the discount price and displays the discounted fee information on the terminal.

[0996] Prompt Sentence Examples

[0997] "What are the best online courses for Python for Data Science?"

[0998] In this way, the online learning system of the present invention provides an environment in which users can study efficiently and easily, maximizing the effectiveness of their learning.

[0999] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1000] Step 1:

[1001] Users access the learning system's website from a web browser on their PC or mobile device. They enter the subject they want to learn (e.g., "data science") into the input form and click the submit button. The input is text data of the subject they want to learn, and the output is data sent to the server as an HTTP POST request.

[1002] Step 2:

[1003] The server receives an HTTP POST request from the device for the content the user wants to learn. It uses a generative AI model (e.g., the BERT model) to analyze the input text and extract key keywords. Specifically, it tokenizes the text data and applies a natural language processing algorithm to identify important words and phrases. The input is the text data of the content the user wants to learn, and the output is the analysis results (key keywords).

[1004] Step 3:

[1005] The server uses the analyzed keywords to search the database for the most suitable learning courses. This search process uses a search engine (e.g., Elasticsearch) that utilizes indexed data. Specifically, the server scores the relevance of learning courses based on the keywords and lists the most suitable courses. The input is the main keywords, and the output is a list of the most suitable learning courses.

[1006] Step 4:

[1007] The terminal receives the list of optimal learning courses sent from the server and displays it to the user. The user selects the desired course (e.g., "Python for Data Science") from the displayed courses and clicks the select button. Here, the input is the list of learning courses, and the output is the specific course selected by the user.

[1008] Step 5:

[1009] The server retrieves the learning materials, videos, and exercises corresponding to the learning course selected by the user from a database. This database is stored, for example, using a cloud storage service (e.g., Amazon S3). The retrieved content is then delivered to the user's device. The input is the selected learning course, and the output is the learning materials, videos, and exercises (specific content).

[1010] Step 6:

[1011] The device receives the distributed learning content and displays it to the user. The user watches video lectures and downloads learning materials in PDF format to progress with their studies. Here, the input is the distributed learning content, and the output is the screen display for the user to study and the downloaded learning materials.

[1012] Step 7:

[1013] The server provides a confirmation test based on the user's learning progress. Specifically, it analyzes the user's access history and study time data to generate an appropriate test. The test includes multiple-choice and essay questions and is sent to the user. The input is the user's learning progress data, and the output is the generated confirmation test.

[1014] Step 8:

[1015] The terminal receives the confirmation test sent from the server and displays it to the user. The user answers the test and clicks the send button to send the answer data to the server. The input is the confirmation test and the output is the user's test answer.

[1016] Step 9:

[1017] The server receives the user's test answers and scores them using an automated evaluation system (e.g., AutoML). Feedback is generated based on the analysis results and sent to the user's device. The feedback includes the accuracy rate and areas for improvement in learning. The input is the user's test answers, and the output is the generated feedback.

[1018] Step 10:

[1019] The device receives the feedback sent from the server and displays it to the user. The user can understand their own level of understanding and weaknesses and can revise their study plan. The input is the feedback, and the output is the displayed feedback.

[1020] Step 11:

[1021] When a user inputs information about a specific qualification or certification exam, the server searches the database for appropriate exam preparation content and delivers it to the terminal. The input is the qualification or certification exam information, and the output is the exam preparation content.

[1022] Step 12:

[1023] The terminal receives the test preparation content sent from the server and displays it to the user, who can use it to prepare for the test. The input is the test preparation content, and the output is a display for the user to use in their studies.

[1024] Step 13:

[1025] The server checks the user's communication line information and applies discounts to specific communication service users. It verifies number portability information, calculates the discount, and sends it to the terminal. The input is communication line information, and the output is discount application information.

[1026] Step 14:

[1027] The terminal receives the discount application information sent from the server and displays it to the user. The user can check the discounted price information. The input is the discount application information, and the output is the discounted price displayed to the user.

[1028] Through these steps, the online learning system provides an environment that allows users to learn efficiently and easily, maximizing learning effectiveness.

[1029] (Application example 1)

[1030] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1031] Conventional online learning systems often limit the effectiveness of learning because they make it difficult for students to learn face-to-face or engage in real-time dialogue, and require students to manage their own progress independently. Furthermore, the process of efficiently inputting the content users want to learn and selecting the most appropriate course from a variety of courses is cumbersome. Furthermore, they are unable to fully accommodate the communication status and device environment of specific students, making it difficult to provide an individually optimized learning experience. New technological solutions are needed to solve these problems.

[1032] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1033] In this invention, the server includes a terminal for a user to input content they wish to learn, natural language processing means for receiving and analyzing the learning content input from the terminal, means for the server to suggest an optimal learning course based on the analysis results, means for the server to provide a confirmation test based on the user's learning progress, means for the server to provide test preparation content to the user, means for applying discounts to specific communication service users based on communication line information, means for the user to view and operate learning content in a virtual store using smart glasses, a head-mounted display, or other display device, means for the server to input content they wish to learn through voice recognition, and means for the server to visually display an appropriate learning course in a virtual reality environment. This solves the problem of users having difficulty in self-directed learning and provides a more immersive learning experience.

[1034] "What you want to learn" refers to the learning topics or themes that users select and enter based on their learning goals or interests.

[1035] A "terminal" is an electronic device used by a user to input data or view content, including smart glasses and head-mounted displays.

[1036] "Natural language processing means" refers to technology that analyzes text data entered by users and extracts meaning and important keywords.

[1037] A "server" is a central processing unit that receives input data from users, analyzes and processes it, and returns an appropriate response.

[1038] "Optimal learning course" refers to the educational program or content that best suits the user's learning needs.

[1039] "Study progress status" is information that indicates how much progress the user has made in the course of their studies.

[1040] A "review test" is a test provided to assess what a user has learned, and includes questions to check their understanding and memory.

[1041] "Exam Preparation Content" means study materials and practice questions provided to prepare for a particular qualification or certification exam.

[1042] "Communication line information" refers to information regarding the Internet connection and data communications used by the user.

[1043] A "means for applying discounts" is a mechanism for applying discounts and reducing fees to communication service users who meet certain conditions.

[1044] A "virtual store" is a virtual space that users can access via the Internet and purchase goods and services.

[1045] "Smart glasses" are glasses-type wearable devices equipped with a display function that can display and operate information.

[1046] A "head-mounted display" is a display device that the user wears on their head and can provide immersive images.

[1047] "Speech recognition" is a technology that converts a user's speech into text data in real time.

[1048] A "virtual reality environment" is a virtual space in which users are immersed in a computer-generated 3D space, providing a realistic experience.

[1049] The present invention aims to provide users with an immersive learning experience by incorporating a virtual reality environment into an online learning system. Specific embodiments of the present invention will be described below.

[1050] System Program

[1051] Hardware

[1052] Smart glasses: A wearable device in the form of glasses with a display function

[1053] Head-mounted display (HMD): A display device worn on the head.

[1054] Server: A central processing unit that receives, analyzes, and provides data

[1055] software

[1056] Natural Language Processing (NLP) systems: Analyze user input data and extract meaning and keywords (e.g., Google Cloud Natural Language API)

[1057] Virtual reality (VR) development platforms: Generate 3D spaces and provide interactive learning experiences (e.g., Unity 3D)

[1058] Learning Management System (LMS): Manages and delivers learning courses (e.g., Moodle)

[1059] Program processing description

[1060] 1. Enter what you want to learn

[1061] Users wear smart glasses or an HMD and voice-input what they want to learn in the virtual store.

[1062] Voice data is captured through the built-in microphone of smart glasses or HMDs and transmitted to a natural language processing system.

[1063] 2. Receiving and analyzing input

[1064] The server uses voice recognition to convert the user's voice input into text and uses a natural language processing system to extract keywords.

[1065] The server searches the learning management system for relevant learning courses based on the extracted keywords.

[1066] 3. Recommending the best course of study

[1067] The server searches for relevant learning courses and displays the results on the user's smart glasses or HMD.

[1068] Users can select the most appropriate course from the displayed list and begin learning.

[1069] 4. Offering study courses

[1070] The server sequentially delivers teaching materials and videos based on the course selected by the user.

[1071] Users can learn in a virtual reality environment through smart glasses or an HMD.

[1072] 5. Testing and Providing Feedback

[1073] The server provides confirmation tests according to learning progress and scores the user's answers with an automated evaluation system.

[1074] Feedback is generated based on the results and displayed on the user's device.

[1075] 6. Provision of exam preparation content

[1076] When a user inputs the content they need to prepare for a specific exam, the server searches for and provides the preparation content based on that information.

[1077] 7. Discount Application

[1078] The server checks the user's communication line information and applies discounts to users of specific communication services.

[1079] Specific examples

[1080] 1. User A puts on the smart glasses and says, "I want to learn Python."

[1081] 2. The server recognizes "Python" as a keyword and suggests the related courses "Python for Data Science" and "Advanced Python."

[1082] 3. User A selects "Python for Data Science" and watches the course materials and videos in a virtual reality environment.

[1083] 4. During the learning process, the server provides a confirmation test, and after completion, feedback such as "You got 80% correct. You need more practice on loop syntax" is displayed.

[1084] Prompt Sentence Examples

[1085] Simulate a system that suggests learning content to users through voice control in a virtual learning salon. If a user types "I want to learn Python," explain what courses would be suggested and what learning content would be provided. Also, describe the technical implementation of the system.

[1086] This allows users to study in a virtual reality environment, providing a greater sense of immersion and learning effectiveness than traditional online learning systems.

[1087] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1088] Step 1:

[1089] Users wear smart glasses or a head-mounted display (HMD) and voice-input what they want to learn in the virtual store.

[1090] Input: User speech (e.g., "I want to learn Python")

[1091] How it works: Audio data is captured through the smart gadget's built-in microphone.

[1092] Output: Audio data is generated.

[1093] Step 2:

[1094] The server uses voice recognition to convert the user's voice input into text data.

[1095] Input: Audio data

[1096] How it works: The server uses a speech recognition engine (e.g., Google Cloud Speech-to-Text) to convert the audio data into text.

[1097] Output: Text data (e.g., "I want to learn Python")

[1098] Step 3:

[1099] The server analyzes the text data using natural language processing (NLP) and extracts keywords.

[1100] Input: Text data

[1101] How it works: The server uses a natural language processing engine (e.g., Google Cloud Natural Language API) to analyze the input text. The analysis extracts key keywords.

[1102] Output: Extracted keywords (e.g. "Python")

[1103] Step 4:

[1104] The server searches for relevant learning courses from a learning management system (LMS) based on the extracted keywords.

[1105] Input: Extracted keywords

[1106] How it works: The server searches the LMS database for learning courses related to the extracted keywords.

[1107] Output: A list of related learning courses (e.g., "Python for Data Science," "Advanced Python")

[1108] Step 5:

[1109] The server displays the search results on the user's smart glasses or HMD.

[1110] Input: A list of related courses

[1111] How it works: The server uses a virtual reality (VR) development platform (e.g. Unity 3D) to visually display the results on the user's smart gadget.

[1112] Output: A list of displayed courses

[1113] Step 6:

[1114] The user selects from the displayed learning courses and begins learning.

[1115] Input: Select a course of study (e.g., "Python for Data Science")

[1116] Operation: The user selects the desired course using the operation interface of the smart gadget and sends the selection information to the server.

[1117] Output: Information about the course selected by the user

[1118] Step 7:

[1119] The server delivers teaching materials and videos sequentially based on the course selected by the user.

[1120] Input: Course information selected by the user

[1121] How it works: The server retrieves the learning materials and videos corresponding to the selected course from the LMS and sends them to the user's smart gadget.

[1122] Output: Delivered learning materials and videos

[1123] Step 8:

[1124] Users can view educational materials and videos and progress through their studies in a virtual reality environment.

[1125] Input: Delivered learning materials and videos

[1126] How it works: Users view and interact with learning content in a virtual reality environment through smart glasses or an HMD.

[1127] Output: Learning progress data

[1128] Step 9:

[1129] The server provides confirmation tests according to the learning progress, and the user's answers are scored by an automated evaluation system.

[1130] Input: Learning progress data

[1131] How it works: The server provides a prompt at the appropriate time and automatically scores the user's answers.

[1132] Output: Verification test results

[1133] Step 10:

[1134] The server generates feedback based on the results of the validation test and displays it on the user's smart gadget.

[1135] Input: Verification test result

[1136] How it works: The server generates feedback and displays it to the user, showing their progress and suggesting areas for improvement.

[1137] Output: Feedback information (e.g., "You got it 80% right. You need more practice with loop syntax.")

[1138] Step 11:

[1139] Users input the content they need to prepare for a specific exam, and the server searches for and provides the preparation content based on that information.

[1140] Input: Test preparation input (e.g., "Data Science Certification Exam")

[1141] How it works: The server retrieves relevant test preparation content from the LMS and delivers it to the user's smart gadget.

[1142] Output: Provided exam prep content

[1143] Step 12:

[1144] The server checks the user's communication line information and applies discounts to users of specific communication services.

[1145] Input: Communication line information

[1146] How it works: The server analyzes the line information, calculates the applicable discounts, and notifies the user.

[1147] Output: Discount information

[1148] Through the above steps, the present invention can provide users with an efficient and effective learning environment.

[1149] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1150] ---

[1151] This invention relates to an online learning system using PCs and mobile devices. The system of the present invention includes a terminal for inputting the content to be learned, a server that receives and analyzes the input content, a server function for proposing optimal learning courses, a server function for providing confirmation tests and exam preparation content, a server function for applying discounts based on communication line information, and an emotion engine that recognizes the user's emotions. Each function is described in detail below.

[1152] ---

[1153] Input and analyze what you want to learn

[1154] Users access the learning system's website from a web browser on their PC or mobile device. They enter what they want to learn into the input form on the website. For example, if they want to learn "data science," they enter that information into the form and click the submit button.

[1155] The server receives the desired learning content sent from the device and analyzes the text using a natural language processing engine. It extracts key keywords and searches the database for relevant learning courses based on those keywords. For example, if the keyword "data science" is entered, the server will pick up courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science."

[1156] ---

[1157] Course suggestions and selection

[1158] The server sends the selected course list to the user's device, which then displays the list on the screen. The user selects the desired course from the displayed courses and clicks the "Start" button for the selected course. For example, if the user selects "Python for Data Science," they click on that course.

[1159] ---

[1160] Providing learning content and an emotional engine

[1161] The server retrieves the learning materials, videos, and exercises corresponding to the user's selected course from the database and delivers them to the device. The device displays the received content, allowing the user to proceed with their learning. For example, a video lecture can be played and PDF learning materials can be downloaded.

[1162] At the same time, the device uses an emotion engine to monitor the user's state and provide feedback and content accordingly. The device collects the user's facial expressions, voice, typing speed, and other behavioral data and sends it to the server. The server uses this data to analyze the user's emotional state and makes adjustments such as temporarily lowering the difficulty of the learning course if the user is feeling stressed.

[1163] ---

[1164] Providing confirmation tests and feedback

[1165] The server tracks the user's learning progress and provides confirmation tests at appropriate times. The tests consist of multiple choice and written questions to verify the user's level of understanding. When the user answers the confirmation test and clicks the submit button, the server receives the answers and grades them using an automated evaluation system.

[1166] The server generates feedback for the user based on the results of the confirmation test and sends it to the device. The device displays this feedback, allowing the user to understand their level of understanding and weak points. For example, the feedback might be, "You got 80% right. You need more practice with loop syntax."

[1167] ---

[1168] Providing exam preparation content

[1169] Users can input information about specific qualification exams or certification tests. Based on the input exam information, the server retrieves appropriate exam preparation content from a database and delivers it to the device. The device then displays the received exam preparation content, allowing users to use it to prepare for the exam.

[1170] ---

[1171] Discounts applied

[1172] The server checks the user's communication line information and applies discounts to users of specific communication services. For example, if a user uses a specific communication service, the server calculates the discount price and displays the discounted fee information on the terminal.

[1173] ---

[1174] In this way, the online learning system of the present invention allows users to learn efficiently and easily, and optimizes the learning experience through emotion recognition, thereby providing an environment that maximizes learning effectiveness.

[1175] The processing flow will be explained below.

[1176] Step 1:

[1177] The user accesses the learning system website using the browser on their PC or mobile device, enters the content they want to learn into the input form, and clicks the submit button.

[1178] Step 2:

[1179] The device sends the user's input to the server, where it is temporarily stored.

[1180] Step 3:

[1181] The server uses a natural language processing engine to analyze the user's input and extract key keywords. For example, if a user inputs that they want to learn "data science," the server will extract the keyword "data science."

[1182] Step 4:

[1183] The server searches the database for relevant learning courses based on the extracted keywords, creates a list of learning courses, and selects the most suitable course for the user.

[1184] Step 5:

[1185] The server sends the selected course list to the user's terminal, which displays the received course list on the screen and allows the user to select a course.

[1186] Step 6:

[1187] The user selects the desired course from the displayed learning courses and clicks the "Start" button for the selected course. The terminal sends the selection information to the server.

[1188] Step 7:

[1189] The server retrieves the learning materials, videos, and exercises corresponding to the user's selected course from a database and delivers them to the device in sequence. The device then displays the received content, allowing the user to proceed with their learning.

[1190] Step 8:

[1191] The device uses an emotion engine to collect the user's facial expressions, voice, typing speed and other behavioral data, and then transmits the collected emotion data to the server.

[1192] Step 9:

[1193] The server analyzes the received emotional data and recognizes the user's learning state. If the user is feeling stressed, the difficulty level of the learning course and the presentation method will be adjusted.

[1194] Step 10:

[1195] The server tracks the user's learning progress and provides confirmation tests at appropriate times, which are then displayed on the device's screen.

[1196] Step 11:

[1197] The user takes the test and enters their answers. The device sends the answers to a server, which then grades them with an automated scoring system and generates a result.

[1198] Step 12:

[1199] The server generates feedback based on the results of the verification test and sends it to the user's device, which then displays the feedback to the user.

[1200] Step 13:

[1201] The user enters information about the qualification exam or certification exam they wish to take. The device sends the entered information to the server. The server retrieves exam preparation content from the database and distributes it to the user's device.

[1202] Step 14:

[1203] The server checks the user's communication line information and applies a discount if a specific communication service is used. The server calculates the discount price and displays the discounted fee information on the terminal.

[1204] Example 2

[1205] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1206] While conventional online learning systems offer basic functions such as providing optimal learning courses based on the content users input as they wish to learn, providing confirmation tests, and providing exam preparation content, they lack more advanced personalized learning support, such as optimizing the learning experience by taking into account the user's emotional state or applying discounts based on communication line information. This makes it difficult to maximize learning effectiveness and maintain motivation to learn.

[1207] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1208] In this invention, the server includes an information processing terminal for inputting content that the user wants to learn, natural language processing engine means for receiving and analyzing the learning content input from the terminal, means for the information processing device having a function of suggesting an optimal learning course based on the analysis results, means for the information processing device having a function of providing a confirmation test based on the user's learning progress, means for the information processing device having a function of providing test preparation content to the user, emotion recognition engine means for the information processing device having a function of monitoring the user's emotional state and optimizing the learning experience, and means for applying discounts to specific communication service users based on communication line information. This allows users to be provided with more highly personalized learning support, maximizing learning effectiveness and maintaining motivation to learn.

[1209] "User" refers to an individual or corporation that uses the online learning system to input what they want to learn and receive learning content.

[1210] "Information processing terminal" refers to a computer or mobile terminal that allows users to input study content and display study courses and content.

[1211] "Information processing device" refers to servers and cloud computing resources that handle all aspects of the learning system, such as receiving and analyzing the content to be learned, proposing learning courses, providing confirmation tests, and providing exam preparation content.

[1212] A "natural language processing engine" refers to a software engine that analyzes the text data of the learning content entered by the user and extracts important keywords.

[1213] "Study course suggestion function" refers to a function that suggests the most suitable study course to the user based on the results of analysis by the natural language processing engine.

[1214] "Confirmation test provision function" refers to a function for providing confirmation tests at appropriate times based on the user's learning progress.

[1215] "Exam preparation content provision function" refers to a function that provides users with appropriate exam preparation content based on the exam information entered by the user.

[1216] An "emotion recognition engine" is an engine that analyzes a user's facial expressions, voice, and behavioral data to recognize their emotional state and optimize the learning experience.

[1217] "Communication line information" refers to information about the internet line and communication services used by the user.

[1218] The "discount application function" refers to a function for applying a discount to a specific communication service user based on communication line information.

[1219] The present invention relates to an online learning system that includes an information processing terminal used by a user, an information processing device having a natural language processing engine, an emotion recognition engine, and a discount application function based on communication line information. The following describes an embodiment of the present invention in detail.

[1220] Input and analyze what you want to learn

[1221] Users access the online learning system using a web browser on an information processing device such as a PC or mobile device. They enter what they want to learn into the input form on the website and click the submit button. For example, they might enter "data science." The information processing device analyzes the input text using a natural language processing engine implemented in Python and extracts key keywords. The information processing device then searches for related learning courses in a MySQL database and suggests the most suitable course.

[1222] Course suggestions and selection

[1223] The information processing device sends a list of learning courses to be suggested to the user to the information processing terminal. The terminal uses JavaScript to display the list of learning courses on the screen. The user selects the desired course from the displayed course and clicks the start button. For example, the user selects "Python for Data Science."

[1224] Providing learning content and an emotional engine

[1225] The information processing device retrieves content related to the learning course selected by the user from a database and sequentially delivers it to the user's device. The device displays the received content in HTML format, allowing the user to proceed with their learning. For example, video lectures may be played and learning materials in PDF format may be available for download. The device also collects the user's emotional data from the webcam and microphone and transmits it to the server in real time. The information processing device analyzes the user's emotional state using an emotion recognition engine based on TensorFlow and provides feedback, such as adjusting the difficulty of the learning content, if the user is feeling stressed.

[1226] Providing confirmation tests and feedback

[1227] The information processing device tracks the user's learning progress and provides confirmation tests at appropriate times. The user answers the confirmation test and clicks the submit button. The information processing device receives the answers and scores them using an automated evaluation system implemented in Ruby. Feedback is generated based on the scoring results and sent to the device. The device displays the feedback on the screen, allowing the user to understand their level of understanding and areas for improvement.

[1228] Providing exam preparation content

[1229] Users can input specific exam information, for example, "AWS Certified Solutions Architect." The information processing device retrieves appropriate exam preparation content from a database based on that information and delivers it to the user's device. The device then displays the received content in HTML format, allowing the user to continue preparing for the exam.

[1230] Discounts applied

[1231] The information processing device checks the user's communication line information and applies a discount to users of a specific communication service. For example, if the user is a subscriber of a specific communication carrier, the information processing device calculates the discount price and transmits the fee information to the terminal. The terminal displays the discount information on its screen.

[1232] Examples of concrete examples and prompts

[1233] Specific examples

[1234] Learning content: "Data Science"

[1235] Suggested courses: "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science."

[1236] Course selected: "Python for Data Science"

[1237] Learning content: video lectures, PDF materials

[1238] Test result: "80% correct. I need more practice with loop syntax."

[1239] Exam Information: "AWS Certified Solutions Architect"

[1240] Exam preparation content provided: "AWS exam question bank" and "AWS related materials"

[1241] Prompt Sentence Examples

[1242] 1. "I received the Python for Data Science course materials, what's next?"

[1243] 2. "If my learning progress is slow, how can I improve it?"

[1244] 3. "Please give me feedback on the questions I got wrong on the confirmation test."

[1245] 4. "Which test prep content is most effective?"

[1246] As described above, the online learning system of the present invention allows users to study efficiently and easily, and optimizes the learning experience through emotion recognition, thereby maximizing learning effectiveness.

[1247] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1248] Step 1:

[1249] A user accesses the learning system's website from a web browser. The user uses an information processing terminal to enter a specified URL and display the online learning system's home page. The input here is the user's action (URL input and access), and the output is the website's home page displayed on the terminal. Specifically, the web browser sends an HTTP request, and the server returns an HTTP response.

[1250] Step 2:

[1251] The user enters what they want to learn into the input form and clicks the submit button. For example, enter "data science" into the text box and submit. The input is what the user wants to learn (text data), and the output is that this data is sent to the server. Specifically, the user enters text on the keyboard and clicks the "Submit" button.

[1252] Step 3:

[1253] The server receives the learning content sent from the device and analyzes it using a natural language processing engine. The input is the text data sent by the user, and the main keywords are extracted as a result of the analysis. Specifically, the server uses an NLP engine implemented in Python to extract the keyword "data science" from the text. The output is a list of keywords.

[1254] Step 4:

[1255] The server searches the database for relevant learning courses based on the analyzed keywords. The input is the extracted keyword list, and the output is a list of learning courses retrieved from the database. The server uses SQL queries to search the MySQL database and retrieve courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science."

[1256] Step 5:

[1257] The server sends the selected course list to the user's device. The input is the list of courses, and the output is that this list is displayed on the device. Specifically, the server sends the course list in JSON format as an HTTP response, and the device receives it.

[1258] Step 6:

[1259] The device displays the received learning course list on the screen. The input is the course list received from the server, and the output is a list of learning courses that the user can view. Specifically, it uses JavaScript to generate HTML content and displays it to the user as a list.

[1260] Step 7:

[1261] The user selects the desired course and clicks the start button. For example, select "Python for Data Science." The input is the user's selection action, and the output is the ID of the selected course being sent to the server. Specifically, the user clicks on the course with the mouse and presses the "Start" button.

[1262] Step 8:

[1263] The server retrieves content corresponding to the user's selected learning course from the database. The input is the selected course ID, and the output is the corresponding learning material and video data. Specifically, the server retrieves the learning material and video data from the MySQL database using SQL queries.

[1264] Step 9:

[1265] The server sequentially distributes the acquired learning content to the user's device. The input is the acquired learning content, and the output is the teaching materials and videos distributed to the device. Specifically, the server sends the content as an HTTP response, and the device receives it.

[1266] Step 10:

[1267] The device displays the received learning content, allowing the user to progress through their studies. The input is the received content data, and the output is the learning materials and videos displayed to the user. Specifically, the device uses HTML and JavaScript to render the learning materials and videos and display them on the screen.

[1268] Step 11:

[1269] The device collects user emotional data from a webcam and microphone and sends it to a server. The input is the user's facial expression, voice, typing speed, etc., and the output is the transmission of the collected emotional data. Specifically, the device acquires sensor data in real time and sends it to the server via an API.

[1270] Step 12:

[1271] The server uses an emotion recognition engine to analyze the user's emotional data and provide feedback as needed. The input is the collected emotional data, and the output is feedback information. Specifically, it analyzes emotions using a TensorFlow model and adjusts the learning difficulty, such as lowering the learning difficulty, if the user is feeling stressed.

[1272] Step 13:

[1273] The server tracks the user's learning progress and provides confirmation tests at appropriate times. The input is the learning log data, and the output is the content of the confirmation test. Specifically, the server monitors the progress and generates a confirmation test when certain conditions are met.

[1274] Step 14:

[1275] The user answers the confirmation test and clicks the "Submit" button. The input is the user's test answer, and the output is the answer data sent to the server. Specifically, the user answers the questions on the screen and presses the "Submit" button.

[1276] Step 15:

[1277] The server receives the answers and grades them with an automated evaluation system. The input is the user's test answer data, and the output is the test score. Specifically, the evaluation system, implemented in Ruby, analyzes the answers and calculates the score.

[1278] Step 16:

[1279] The server generates feedback and sends it to the user's device. The input is the scoring result data, and the output is feedback information. Specifically, the server generates feedback including correct / incorrect answers and advice, and sends it to the device.

[1280] Step 17:

[1281] The device displays feedback, allowing the user to understand their level of understanding and areas for improvement. The input is feedback data, and the output is feedback that is displayed to the user. Specifically, the feedback is displayed on the screen using HTML and JavaScript.

[1282] Step 18:

[1283] The user enters exam information and clicks the submit button. For example, they enter "AWS Certified Solutions Architect." The input is the user's exam information, and the output is the data sent to the server. Specifically, the user enters text and clicks the "Submit" button.

[1284] Step 19:

[1285] The server retrieves the appropriate exam preparation content from the database based on the exam information. The input is the exam information data, and the output is the retrieved exam preparation content. Specifically, the server uses SQL queries to retrieve the relevant content.

[1286] Step 20:

[1287] The server delivers the acquired test preparation content to the user's device. The input is the test preparation content, and the output is the content delivered to the device. Specifically, the server sends the content as an HTTP response, and the device receives it.

[1288] Step 21:

[1289] The device displays the received test preparation content, which the user can use to prepare for the test. The input is the received content data, and the output is the content that is displayed to the user. Specifically, the content is rendered using HTML and JavaScript and displayed on the screen.

[1290] Step 22:

[1291] The server checks the user's communication line information and applies discounts to specific communication service users. The input is communication line information, and the output is the calculated discount price. Specifically, the server analyzes the IP address and determines whether the discount applies.

[1292] Step 23:

[1293] The server calculates the discount price and displays the price information on the terminal. The input is the discount price calculation data, and the output is the price information displayed on the terminal. Specifically, the server sends the calculation result in JSON format to the terminal, and the terminal displays it on the screen.

[1294] These are the specific processing steps of the online learning system of the present invention, which allows users to learn efficiently and easily, and also optimizes the learning experience through emotion recognition.

[1295] (Application example 2)

[1296] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1297] Online learning systems are required to not only suggest appropriate learning courses based on the user's learning content and progress and provide confirmation tests, but also to monitor the user's emotional state to optimize the learning experience. However, many current online learning systems lack the functionality to consider the user's emotional state and do not provide sufficient support to maximize learning efficiency. Furthermore, insufficient feedback and adjustment of the learning experience according to the user's emotional state leads to a decrease in users' motivation to learn and a decrease in learning effectiveness.

[1298] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a terminal for the user to input the content they want to learn, natural language processing means for receiving and analyzing the learning content input from the terminal, means for proposing an optimal learning course based on the analysis results, means for providing a confirmation test based on the user's learning progress, means for providing test preparation content to the user, means for applying discounts to specific communication service users based on communication line information, emotion recognition means for monitoring the user's emotional state and providing feedback, and means for adjusting the learning experience according to the emotional state. This makes it possible to grasp the user's emotional state in real time and provide an optimal learning experience according to that state.

[1299] "Terminal" means a device that allows a user to input what they want to learn and receive and display learning content.

[1300] A "server" is a computer system that receives, analyzes, and processes learning content sent by users.

[1301] "Natural language processing means" is a technology for analyzing text entered by a user and extracting key keywords and related information.

[1302] "Learning Course" means a series of educational content or lectures offered for User learning.

[1303] A "validation test" is a test provided to assess a user's learning progress and includes questions that measure the user's understanding.

[1304] "Exam Preparation Content" refers to study materials and practice questions that users need to pass a particular exam or certification.

[1305] "Communication line information" is data that indicates information about the Internet connection and mobile communications used by the user.

[1306] A "means for applying discounts" is a system that provides discounts on learning courses or service fees to users who meet certain conditions.

[1307] "Emotion recognition means" is a technology that detects and analyzes a user's emotional state from their facial expressions, voice, behavior, etc.

[1308] "Feedback" refers to guidance and advice provided based on a user's learning progress and emotional state.

[1309] "Means for adjusting the learning experience" refers to technology that dynamically changes the difficulty and content of a learning course depending on the user's emotional state.

[1310] This invention relates to an online learning system that inputs what a user wants to learn, suggests an optimal learning course based on that input, and monitors the user's emotional state to provide feedback.

[1311] The online learning system of the present invention consists of the following components: First, a user inputs the content they want to learn using a terminal. This terminal can be any device such as a PC, smartphone, smart glasses, or head-mounted display, and is connected to a server via a network.

[1312] The server receives the learning content sent by the user from the device and analyzes it using a natural language processing engine, which uses, for example, Google's NLU API or other common natural language analysis technologies, to extract the user's learning objectives and keywords.

[1313] The server then searches the database for the most suitable learning course based on the extracted keywords and suggests it to the user. At this stage, the server also monitors the user's learning progress and provides timely review tests and exam preparation content.

[1314] Furthermore, the system uses emotion recognition to monitor the user's emotional state in real time. This emotion recognition is achieved by analyzing the user's facial expressions, voice, typing speed, and other behavioral data. The server uses this data to determine the user's emotional state and adjust the learning experience accordingly. This technology can temporarily lower the difficulty of the learning course if the user is feeling stressed, thereby maintaining the user's motivation and efficiency in learning.

[1315] As a concrete example, consider a case where a user wants to learn "data science." In this case, the user enters the keyword "data science" into their device, and the server analyzes this keyword using a natural language processing engine. After analysis, the server suggests optimal learning courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science." When the user selects "Python for Data Science" and begins learning, the server monitors their emotional state in real time and adjusts the learning experience. It also provides confirmation tests at appropriate times according to the user's learning progress and provides feedback based on the results.

[1316] Examples of prompts to input to a generative AI model include:

[1317] "Enter what you want to learn. Include specific keywords, such as 'data science.'"

[1318] In this way, the online learning system of the present invention allows users to learn efficiently and easily, and optimizes the learning experience through emotion recognition, thereby maximizing learning effectiveness.

[1319] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1320] Step 1:

[1321] The user enters the content they wish to learn from a terminal. The user enters the text of what they want to learn into the input form on the terminal and clicks the send button. For example, they enter "data science." The entered content is sent from the terminal to the server. The input data is in text format. The output is the text data sent to the server.

[1322] Step 2:

[1323] The server receives the learning content sent from the device and analyzes it using a natural language processing engine. The input is the text data entered by the user, and the output is the extraction results of key keywords. In this process, the text data is analyzed and the keyword "data science" is extracted. Based on the analysis results, related learning courses are searched for in the database.

[1324] Step 3:

[1325] Based on the analysis results, the server generates a list of optimal learning courses and sends it to the device. The input is the extracted keywords and learning course information from the database, and the output is a list of learning courses. Specifically, it suggests courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science." The device displays the list.

[1326] Step 4:

[1327] The user selects the desired course from the suggested learning courses on the terminal and clicks the "Start" button for the selected course. The input is the learning course selection information, and the output is the selection information sent to the server. The server receives the user's selection and retrieves the learning materials for the selected course from the database.

[1328] Step 5:

[1329] The server retrieves the learning materials and videos corresponding to the learning course selected by the user and delivers them to the terminal in sequence. The input is the information about the selected learning course, and the output is the distribution data of the learning materials and videos. Specifically, the video lecture is played and the learning materials in PDF format can be downloaded.

[1330] Step 6:

[1331] The server uses emotion recognition means to monitor the user's emotional state and analyze it in real time. The input is behavioral data such as the user's facial expressions, voice, and typing speed, and the output is the analysis of the user's emotional state. The device sends this data to the server, which generates feedback based on the analysis results. For example, if the user is feeling stressed, the server will display feedback such as "Relax and continue studying."

[1332] Step 7:

[1333] The server tracks the user's learning progress and provides confirmation tests at appropriate times. The input is learning progress data, and the output is the confirmation test data. The user answers the confirmation test and sends it to the server. The server grades the test with an automatic evaluation system and returns the results to the device as feedback.

[1334] Step 8:

[1335] When a user inputs information about a specific exam or certification, the server provides the most appropriate exam preparation content based on that information. The input is the exam information, and the output is the distribution data of the exam preparation content. Specifically, preparation materials such as past exam questions and mock exams are provided.

[1336] Step 9:

[1337] The server checks the user's communication line information and applies discounts to specific communication service users. The input is communication line information, and the output is the discounted price information. The server calculates the discounted price and displays the discounted information on the terminal.

[1338] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1339] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1340] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1341] [Fourth embodiment]

[1342] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1343] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1344] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1345] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1346] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1347] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1348] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1349] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1350] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1351] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1352] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1353] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1354] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1355] ---

[1356] This invention relates to an online learning system using PCs and mobile devices. The system of the present invention has a terminal for inputting the content to be learned, a server that receives and analyzes the input content, a server function that proposes the optimal learning course, a server function that provides confirmation tests and test preparation content, and a server function that applies discounts based on communication line information. Each function is described in detail below.

[1357] ---

[1358] Enter what you want to learn

[1359] Users access the learning system's website from a web browser on their PC or mobile device. They enter what they want to learn into the input form on the website. For example, if they want to learn "data science," they enter that information into the form and click the submit button.

[1360] ---

[1361] Receiving and parsing input

[1362] The server receives the desired learning content sent from the device. After receiving it, it uses natural language processing to analyze the text of the input content and extracts key keywords. For example, if "data science" is input, the server analyzes this keyword and searches for related learning courses.

[1363] ---

[1364] Suggestion of the best course of study

[1365] The server searches the database for the most appropriate learning course based on the analysis results. To minimize latency, it is desirable to pre-index a large amount of learning data. It then suggests highly relevant learning courses to the user. For example, the server might display courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science" on the user's device.

[1366] ---

[1367] View and select study paths

[1368] The device receives the course information sent from the server and displays it to the user. The user selects the desired course from the displayed courses and clicks the "Start" button for the course. For example, if the user selects "Python for Data Science," they click on that course.

[1369] ---

[1370] Providing learning content

[1371] The server retrieves the learning materials, videos, and exercises corresponding to the user's selected course from the database and delivers them to the user's device. The device displays the delivered content and allows the user to progress with their studies. For example, video lectures can be played and PDF learning materials can be downloaded.

[1372] ---

[1373] Providing confirmation tests

[1374] The server provides confirmation tests at appropriate times according to the user's learning progress. The tests consist of multiple choice and written questions to verify the user's level of understanding. When the user answers the confirmation test and clicks the submit button, the server receives the answers and grades them using an automated evaluation system.

[1375] ---

[1376] Providing feedback

[1377] The server generates feedback for the user based on the results of the confirmation test and sends it to the device. The device displays this feedback, allowing the user to understand their level of understanding and weak points. For example, the feedback might be, "You got 80% correct. You need to practice more on loop syntax."

[1378] ---

[1379] Providing exam preparation content

[1380] Users can input information about specific qualification exams and certification tests. The server then retrieves the appropriate test preparation content from the database and delivers it to the device. The device then displays the received test preparation content, allowing the user to use it to prepare for the exam.

[1381] ---

[1382] Discounts applied

[1383] The server checks the user's communication line information and applies discounts to users of specific communication services. For example, if a user uses a specific communication service, the server calculates the discount price and displays the discounted fee information on the terminal.

[1384] ---

[1385] In this way, the online learning system of the present invention provides an environment in which users can learn efficiently and easily, maximizing the effectiveness of their learning.

[1386] The processing flow will be explained below.

[1387] Step 1:

[1388] The user accesses the learning system website using the browser on their PC or mobile device, enters the content they want to learn into the input form, and clicks the submit button.

[1389] Step 2:

[1390] The device sends the user's input to the server, where it is temporarily stored.

[1391] Step 3:

[1392] The server uses a natural language processing engine to analyze the user's input and extract key keywords. For example, if a user inputs that they want to learn "data science," the server will extract the keyword "data science."

[1393] Step 4:

[1394] The server searches the database for relevant learning courses based on the extracted keywords, creates a list of learning courses, and selects the most suitable course for the user.

[1395] Step 5:

[1396] The server sends the selected course list to the user's terminal, which displays the received course list on the screen and allows the user to select a course.

[1397] Step 6:

[1398] The user selects the desired course from the displayed learning courses and clicks the "Start" button for the selected course. The terminal sends the selection information to the server.

[1399] Step 7:

[1400] The server retrieves the learning materials, videos, and exercises corresponding to the user's selected course from a database and delivers them to the device in sequence. The device then displays the received content, allowing the user to proceed with their learning.

[1401] Step 8:

[1402] The server tracks the user's learning progress and provides a confirmation test to the user's device at the appropriate time, which then displays the test on the screen.

[1403] Step 9:

[1404] The user takes the test and enters their answers. The device sends the answers to a server, which then grades them with an automated scoring system and generates a result.

[1405] Step 10:

[1406] The server generates feedback based on the results of the verification test and sends it to the user's device, which then displays the feedback to the user.

[1407] Step 11:

[1408] The user enters information about the qualification exam or certification exam they wish to take. The device sends the entered information to the server. The server retrieves exam preparation content from the database and distributes it to the user's device.

[1409] Step 12:

[1410] The server checks the user's communication line information and applies a discount if a specific communication service is used. The server calculates the discount price and displays the discounted fee information on the terminal.

[1411] ---

[1412] Through the above processing steps, the user can proceed with efficient and effective learning.

[1413] Example 1

[1414] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1415] In recent years, demand for online learning systems has increased, but systems that can propose optimal learning courses for individual users and respond flexibly based on their learning progress are not yet fully developed. Additional features, such as discount application based on communication line information, are also lacking. Therefore, there is a need for a system that allows users to efficiently and effectively learn the content they want to learn.

[1416] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1417] In this invention, the server includes means using a generative AI model to analyze the user's text input, means for providing a validation test based on the user's learning progress, and means for receiving the user's validation test answers and scoring them using an automated assessment system, thereby enabling personalized learning course suggestions, progress management, and discount application.

[1418] A "terminal" is a device that allows a user to input information and check the display, and includes devices such as PCs and mobile terminals.

[1419] A "server" is a computer system that receives, analyzes, stores, and transmits information over a network.

[1420] "Natural language processing means" refers to means that use technologies and algorithms to analyze input text information and understand its meaning.

[1421] A "course" is a collection of study materials, lectures, and exercises designed for a user to study.

[1422] A "confirmation test" is a multiple-choice or written test to measure a user's level of understanding.

[1423] "Exam Preparation Content" refers to study materials and practice questions designed to help students pass a particular qualification or certification exam.

[1424] "Communication line information" refers to information about the provider and contract plan of the communication service used by the user.

[1425] A "generative AI model" is a machine learning algorithm or model for natural language processing and data analysis.

[1426] An "automated evaluation system" is a system that analyzes user responses and performs mechanical evaluations.

[1427] "Feedback" is advice or instruction provided to a user based on their learning progress or test results.

[1428] This invention relates to an online learning system using PCs and mobile devices. It includes a terminal for users to input the content they want to learn, a server that receives and analyzes the input, a server that proposes the optimal learning course based on the analysis results, a server that provides confirmation tests according to learning progress, a server that provides test preparation content, and a server that applies discounts based on communication line information. Each function is described in detail below.

[1429] First, users access the learning system's website from their PC or mobile device, enter the subject they want to learn (e.g., "data science") into the input form on the website, and click the submit button.

[1430] The server then receives the desired learning content sent from the device. After receiving it, the server uses a generative AI model (e.g., the BERT model) to analyze the text of the input and extract key keywords. For example, if "data science" is input, the server analyzes this keyword and searches a database for related learning courses. This database contains data indexed using, for example, Elasticsearch.

[1431] The server searches the indexed data for the most suitable learning courses and displays the most relevant courses on the user's device. For example, it might suggest courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science." The user can select the desired course from the displayed courses and click on it.

[1432] The learning materials, videos, and exercises corresponding to the selected course are delivered from the server. This includes learning materials stored in Amazon S3, for example. Users can view the delivered content on their devices and proceed with their studies. Specifically, video lectures are played and learning materials in PDF format can be downloaded.

[1433] Furthermore, the server provides confirmation tests according to the user's learning progress. These tests include multiple-choice and essay questions to check the user's level of understanding. When the user answers the confirmation test and submits the answers, the server receives the answers and scores them using an automated evaluation system (e.g., AutoML). The server then generates feedback based on the results of the confirmation test and sends it to the device. For example, the server may provide feedback such as, "You got 80% correct. You need to practice more on loop syntax."

[1434] Users can also enter information about specific qualification exams and certification tests. Based on this, the server retrieves appropriate test preparation content from the database and delivers it to the user's device. Users can use the received test preparation content to advance their exam preparation. For example, content such as "TOEIC Preparation Course" is provided.

[1435] Finally, the server checks the user's communication line information and applies discounts to users of specific communication services. For example, if the user is using a specific communication service, the server calculates the discount price and displays the discounted fee information on the terminal.

[1436] Prompt Sentence Examples

[1437] "What are the best online courses for Python for Data Science?"

[1438] In this way, the online learning system of the present invention provides an environment in which users can study efficiently and easily, maximizing the effectiveness of their learning.

[1439] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1440] Step 1:

[1441] Users access the learning system's website from a web browser on their PC or mobile device. They enter the subject they want to learn (e.g., "data science") into the input form and click the submit button. The input is text data of the subject they want to learn, and the output is data sent to the server as an HTTP POST request.

[1442] Step 2:

[1443] The server receives an HTTP POST request from the device for the content the user wants to learn. It uses a generative AI model (e.g., the BERT model) to analyze the input text and extract key keywords. Specifically, it tokenizes the text data and applies a natural language processing algorithm to identify important words and phrases. The input is the text data of the content the user wants to learn, and the output is the analysis results (key keywords).

[1444] Step 3:

[1445] The server uses the analyzed keywords to search the database for the most suitable learning courses. This search process uses a search engine (e.g., Elasticsearch) that utilizes indexed data. Specifically, the server scores the relevance of learning courses based on the keywords and lists the most suitable courses. The input is the main keywords, and the output is a list of the most suitable learning courses.

[1446] Step 4:

[1447] The terminal receives the list of optimal learning courses sent from the server and displays it to the user. The user selects the desired course (e.g., "Python for Data Science") from the displayed courses and clicks the select button. Here, the input is the list of learning courses, and the output is the specific course selected by the user.

[1448] Step 5:

[1449] The server retrieves the learning materials, videos, and exercises corresponding to the learning course selected by the user from a database. This database is stored, for example, using a cloud storage service (e.g., Amazon S3). The retrieved content is then delivered to the user's device. The input is the selected learning course, and the output is the learning materials, videos, and exercises (specific content).

[1450] Step 6:

[1451] The device receives the distributed learning content and displays it to the user. The user watches video lectures and downloads learning materials in PDF format to progress with their studies. Here, the input is the distributed learning content, and the output is the screen display for the user to study and the downloaded learning materials.

[1452] Step 7:

[1453] The server provides a confirmation test based on the user's learning progress. Specifically, it analyzes the user's access history and study time data to generate an appropriate test. The test includes multiple-choice and essay questions and is sent to the user. The input is the user's learning progress data, and the output is the generated confirmation test.

[1454] Step 8:

[1455] The terminal receives the confirmation test sent from the server and displays it to the user. The user answers the test and clicks the send button to send the answer data to the server. The input is the confirmation test and the output is the user's test answer.

[1456] Step 9:

[1457] The server receives the user's test answers and scores them using an automated evaluation system (e.g., AutoML). Feedback is generated based on the analysis results and sent to the user's device. The feedback includes the accuracy rate and areas for improvement in learning. The input is the user's test answers, and the output is the generated feedback.

[1458] Step 10:

[1459] The device receives the feedback sent from the server and displays it to the user. The user can understand their own level of understanding and weaknesses and can revise their study plan. The input is the feedback, and the output is the displayed feedback.

[1460] Step 11:

[1461] When a user inputs information about a specific qualification or certification exam, the server searches the database for appropriate exam preparation content and delivers it to the terminal. The input is the qualification or certification exam information, and the output is the exam preparation content.

[1462] Step 12:

[1463] The terminal receives the test preparation content sent from the server and displays it to the user, who can use it to prepare for the test. The input is the test preparation content, and the output is a display for the user to use in their studies.

[1464] Step 13:

[1465] The server checks the user's communication line information and applies discounts to specific communication service users. It verifies number portability information, calculates the discount, and sends it to the terminal. The input is communication line information, and the output is discount application information.

[1466] Step 14:

[1467] The terminal receives the discount application information sent from the server and displays it to the user. The user can check the discounted price information. The input is the discount application information, and the output is the discounted price displayed to the user.

[1468] Through these steps, the online learning system provides an environment that allows users to learn efficiently and easily, maximizing learning effectiveness.

[1469] (Application example 1)

[1470] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1471] Conventional online learning systems often limit the effectiveness of learning because they make it difficult for students to learn face-to-face or engage in real-time dialogue, and require students to manage their own progress independently. Furthermore, the process of efficiently inputting the content users want to learn and selecting the most appropriate course from a variety of courses is cumbersome. Furthermore, they are unable to fully accommodate the communication status and device environment of specific students, making it difficult to provide an individually optimized learning experience. New technological solutions are needed to solve these problems.

[1472] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1473] In this invention, the server includes a terminal for a user to input content they wish to learn, natural language processing means for receiving and analyzing the learning content input from the terminal, means for the server to suggest an optimal learning course based on the analysis results, means for the server to provide a confirmation test based on the user's learning progress, means for the server to provide test preparation content to the user, means for applying discounts to specific communication service users based on communication line information, means for the user to view and operate learning content in a virtual store using smart glasses, a head-mounted display, or other display device, means for the server to input content they wish to learn through voice recognition, and means for the server to visually display an appropriate learning course in a virtual reality environment. This solves the problem of users having difficulty in self-directed learning and provides a more immersive learning experience.

[1474] "What you want to learn" refers to the learning topics or themes that users select and enter based on their learning goals or interests.

[1475] A "terminal" is an electronic device used by a user to input data or view content, including smart glasses and head-mounted displays.

[1476] "Natural language processing means" refers to technology that analyzes text data entered by users and extracts meaning and important keywords.

[1477] A "server" is a central processing unit that receives input data from users, analyzes and processes it, and returns an appropriate response.

[1478] "Optimal learning course" refers to the educational program or content that best suits the user's learning needs.

[1479] "Study progress status" is information that indicates how much progress the user has made in the course of their studies.

[1480] A "review test" is a test provided to assess what a user has learned, and includes questions to check their understanding and memory.

[1481] "Exam Preparation Content" means study materials and practice questions provided to prepare for a particular qualification or certification exam.

[1482] "Communication line information" refers to information regarding the Internet connection and data communications used by the user.

[1483] A "means for applying discounts" is a mechanism for applying discounts and reducing fees to communication service users who meet certain conditions.

[1484] A "virtual store" is a virtual space that users can access via the Internet and purchase goods and services.

[1485] "Smart glasses" are glasses-type wearable devices equipped with a display function that can display and operate information.

[1486] A "head-mounted display" is a display device that the user wears on their head and can provide immersive images.

[1487] "Speech recognition" is a technology that converts a user's speech into text data in real time.

[1488] A "virtual reality environment" is a virtual space in which users are immersed in a computer-generated 3D space, providing a realistic experience.

[1489] The present invention aims to provide users with an immersive learning experience by incorporating a virtual reality environment into an online learning system. Specific embodiments of the present invention will be described below.

[1490] System Program

[1491] Hardware

[1492] Smart glasses: A wearable device in the form of glasses with a display function

[1493] Head-mounted display (HMD): A display device worn on the head.

[1494] Server: A central processing unit that receives, analyzes, and provides data

[1495] software

[1496] Natural Language Processing (NLP) systems: Analyze user input data and extract meaning and keywords (e.g., Google Cloud Natural Language API)

[1497] Virtual reality (VR) development platforms: Generate 3D spaces and provide interactive learning experiences (e.g., Unity 3D)

[1498] Learning Management System (LMS): Manages and delivers learning courses (e.g., Moodle)

[1499] Program processing description

[1500] 1. Enter what you want to learn

[1501] Users wear smart glasses or an HMD and voice-input what they want to learn in the virtual store.

[1502] Voice data is captured through the built-in microphone of smart glasses or HMDs and transmitted to a natural language processing system.

[1503] 2. Receiving and analyzing input

[1504] The server uses voice recognition to convert the user's voice input into text and uses a natural language processing system to extract keywords.

[1505] The server searches the learning management system for relevant learning courses based on the extracted keywords.

[1506] 3. Recommending the best course of study

[1507] The server searches for relevant learning courses and displays the results on the user's smart glasses or HMD.

[1508] Users can select the most appropriate course from the displayed list and begin learning.

[1509] 4. Offering study courses

[1510] The server sequentially delivers teaching materials and videos based on the course selected by the user.

[1511] Users can learn in a virtual reality environment through smart glasses or an HMD.

[1512] 5. Testing and Providing Feedback

[1513] The server provides confirmation tests according to learning progress and scores the user's answers with an automated evaluation system.

[1514] Feedback is generated based on the results and displayed on the user's device.

[1515] 6. Provision of exam preparation content

[1516] When a user inputs the content they need to prepare for a specific exam, the server searches for and provides the preparation content based on that information.

[1517] 7. Discount Application

[1518] The server checks the user's communication line information and applies discounts to users of specific communication services.

[1519] Specific examples

[1520] 1. User A puts on the smart glasses and says, "I want to learn Python."

[1521] 2. The server recognizes "Python" as a keyword and suggests the related courses "Python for Data Science" and "Advanced Python."

[1522] 3. User A selects "Python for Data Science" and watches the course materials and videos in a virtual reality environment.

[1523] 4. During the learning process, the server provides a confirmation test, and after completion, feedback such as "You got 80% correct. You need more practice on loop syntax" is displayed.

[1524] Prompt Sentence Examples

[1525] Simulate a system that suggests learning content to users through voice control in a virtual learning salon. If a user types "I want to learn Python," explain what courses would be suggested and what learning content would be provided. Also, describe the technical implementation of the system.

[1526] This allows users to study in a virtual reality environment, providing a greater sense of immersion and learning effectiveness than traditional online learning systems.

[1527] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1528] Step 1:

[1529] Users wear smart glasses or a head-mounted display (HMD) and voice-input what they want to learn in the virtual store.

[1530] Input: User speech (e.g., "I want to learn Python")

[1531] How it works: Audio data is captured through the smart gadget's built-in microphone.

[1532] Output: Audio data is generated.

[1533] Step 2:

[1534] The server uses voice recognition to convert the user's voice input into text data.

[1535] Input: Audio data

[1536] How it works: The server uses a speech recognition engine (e.g., Google Cloud Speech-to-Text) to convert the audio data into text.

[1537] Output: Text data (e.g., "I want to learn Python")

[1538] Step 3:

[1539] The server analyzes the text data using natural language processing (NLP) and extracts keywords.

[1540] Input: Text data

[1541] How it works: The server uses a natural language processing engine (e.g., Google Cloud Natural Language API) to analyze the input text. The analysis extracts key keywords.

[1542] Output: Extracted keywords (e.g. "Python")

[1543] Step 4:

[1544] The server searches for relevant learning courses from a learning management system (LMS) based on the extracted keywords.

[1545] Input: Extracted keywords

[1546] How it works: The server searches the LMS database for learning courses related to the extracted keywords.

[1547] Output: A list of related learning courses (e.g., "Python for Data Science," "Advanced Python")

[1548] Step 5:

[1549] The server displays the search results on the user's smart glasses or HMD.

[1550] Input: A list of related courses

[1551] How it works: The server uses a virtual reality (VR) development platform (e.g. Unity 3D) to visually display the results on the user's smart gadget.

[1552] Output: A list of displayed courses

[1553] Step 6:

[1554] The user selects from the displayed learning courses and begins learning.

[1555] Input: Select a course of study (e.g., "Python for Data Science")

[1556] Operation: The user selects the desired course using the operation interface of the smart gadget and sends the selection information to the server.

[1557] Output: Information about the course selected by the user

[1558] Step 7:

[1559] The server delivers teaching materials and videos sequentially based on the course selected by the user.

[1560] Input: Course information selected by the user

[1561] How it works: The server retrieves the learning materials and videos corresponding to the selected course from the LMS and sends them to the user's smart gadget.

[1562] Output: Delivered learning materials and videos

[1563] Step 8:

[1564] Users can view educational materials and videos and progress through their studies in a virtual reality environment.

[1565] Input: Delivered learning materials and videos

[1566] How it works: Users view and interact with learning content in a virtual reality environment through smart glasses or an HMD.

[1567] Output: Learning progress data

[1568] Step 9:

[1569] The server provides confirmation tests according to the learning progress, and the user's answers are scored by an automated evaluation system.

[1570] Input: Learning progress data

[1571] How it works: The server provides a prompt at the appropriate time and automatically scores the user's answers.

[1572] Output: Verification test results

[1573] Step 10:

[1574] The server generates feedback based on the results of the validation test and displays it on the user's smart gadget.

[1575] Input: Verification test result

[1576] How it works: The server generates feedback and displays it to the user, showing their progress and suggesting areas for improvement.

[1577] Output: Feedback information (e.g., "You got it 80% right. You need more practice with loop syntax.")

[1578] Step 11:

[1579] Users input the content they need to prepare for a specific exam, and the server searches for and provides the preparation content based on that information.

[1580] Input: Test preparation input (e.g., "Data Science Certification Exam")

[1581] How it works: The server retrieves relevant test preparation content from the LMS and delivers it to the user's smart gadget.

[1582] Output: Provided exam prep content

[1583] Step 12:

[1584] The server checks the user's communication line information and applies discounts to users of specific communication services.

[1585] Input: Communication line information

[1586] How it works: The server analyzes the line information, calculates the applicable discounts, and notifies the user.

[1587] Output: Discount information

[1588] Through the above steps, the present invention can provide users with an efficient and effective learning environment.

[1589] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1590] ---

[1591] This invention relates to an online learning system using PCs and mobile devices. The system of the present invention includes a terminal for inputting the content to be learned, a server that receives and analyzes the input content, a server function for proposing optimal learning courses, a server function for providing confirmation tests and exam preparation content, a server function for applying discounts based on communication line information, and an emotion engine that recognizes the user's emotions. Each function is described in detail below.

[1592] ---

[1593] Input and analyze what you want to learn

[1594] Users access the learning system's website from a web browser on their PC or mobile device. They enter what they want to learn into the input form on the website. For example, if they want to learn "data science," they enter that information into the form and click the submit button.

[1595] The server receives the desired learning content sent from the device and analyzes the text using a natural language processing engine. It extracts key keywords and searches the database for relevant learning courses based on those keywords. For example, if the keyword "data science" is entered, the server will pick up courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science."

[1596] ---

[1597] Course suggestions and selection

[1598] The server sends the selected course list to the user's device, which then displays the list on the screen. The user selects the desired course from the displayed courses and clicks the "Start" button for the selected course. For example, if the user selects "Python for Data Science," they click on that course.

[1599] ---

[1600] Providing learning content and an emotional engine

[1601] The server retrieves the learning materials, videos, and exercises corresponding to the user's selected course from the database and delivers them to the device. The device displays the received content, allowing the user to proceed with their learning. For example, a video lecture can be played and PDF learning materials can be downloaded.

[1602] At the same time, the device uses an emotion engine to monitor the user's state and provide feedback and content accordingly. The device collects the user's facial expressions, voice, typing speed, and other behavioral data and sends it to the server. The server uses this data to analyze the user's emotional state and makes adjustments such as temporarily lowering the difficulty of the learning course if the user is feeling stressed.

[1603] ---

[1604] Providing confirmation tests and feedback

[1605] The server tracks the user's learning progress and provides confirmation tests at appropriate times. The tests consist of multiple choice and written questions to verify the user's level of understanding. When the user answers the confirmation test and clicks the submit button, the server receives the answers and grades them using an automated evaluation system.

[1606] The server generates feedback for the user based on the results of the confirmation test and sends it to the device. The device displays this feedback, allowing the user to understand their level of understanding and weak points. For example, the feedback might be, "You got 80% right. You need more practice with loop syntax."

[1607] ---

[1608] Providing exam preparation content

[1609] Users can input information about specific qualification exams or certification tests. Based on the input exam information, the server retrieves appropriate exam preparation content from a database and delivers it to the device. The device then displays the received exam preparation content, allowing users to use it to prepare for the exam.

[1610] ---

[1611] Discounts applied

[1612] The server checks the user's communication line information and applies discounts to users of specific communication services. For example, if a user uses a specific communication service, the server calculates the discount price and displays the discounted fee information on the terminal.

[1613] ---

[1614] In this way, the online learning system of the present invention allows users to learn efficiently and easily, and optimizes the learning experience through emotion recognition, thereby providing an environment that maximizes learning effectiveness.

[1615] The processing flow will be explained below.

[1616] Step 1:

[1617] The user accesses the learning system website using the browser on their PC or mobile device, enters the content they want to learn into the input form, and clicks the submit button.

[1618] Step 2:

[1619] The device sends the user's input to the server, where it is temporarily stored.

[1620] Step 3:

[1621] The server uses a natural language processing engine to analyze the user's input and extract key keywords. For example, if a user inputs that they want to learn "data science," the server will extract the keyword "data science."

[1622] Step 4:

[1623] The server searches the database for relevant learning courses based on the extracted keywords, creates a list of learning courses, and selects the most suitable course for the user.

[1624] Step 5:

[1625] The server sends the selected course list to the user's terminal, which displays the received course list on the screen and allows the user to select a course.

[1626] Step 6:

[1627] The user selects the desired course from the displayed learning courses and clicks the "Start" button for the selected course. The terminal sends the selection information to the server.

[1628] Step 7:

[1629] The server retrieves the learning materials, videos, and exercises corresponding to the user's selected course from a database and delivers them to the device in sequence. The device then displays the received content, allowing the user to proceed with their learning.

[1630] Step 8:

[1631] The device uses an emotion engine to collect the user's facial expressions, voice, typing speed and other behavioral data, and then transmits the collected emotion data to the server.

[1632] Step 9:

[1633] The server analyzes the received emotional data and recognizes the user's learning state. If the user is feeling stressed, the difficulty level of the learning course and the presentation method will be adjusted.

[1634] Step 10:

[1635] The server tracks the user's learning progress and provides confirmation tests at appropriate times, which are then displayed on the device's screen.

[1636] Step 11:

[1637] The user takes the test and enters their answers. The device sends the answers to a server, which then grades them with an automated scoring system and generates a result.

[1638] Step 12:

[1639] The server generates feedback based on the results of the verification test and sends it to the user's device, which then displays the feedback to the user.

[1640] Step 13:

[1641] The user enters information about the qualification exam or certification exam they wish to take. The device sends the entered information to the server. The server retrieves exam preparation content from the database and distributes it to the user's device.

[1642] Step 14:

[1643] The server checks the user's communication line information and applies a discount if a specific communication service is used. The server calculates the discount price and displays the discounted fee information on the terminal.

[1644] Example 2

[1645] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1646] While conventional online learning systems offer basic functions such as providing optimal learning courses based on the content users input as they wish to learn, providing confirmation tests, and providing exam preparation content, they lack more advanced personalized learning support, such as optimizing the learning experience by taking into account the user's emotional state or applying discounts based on communication line information. This makes it difficult to maximize learning effectiveness and maintain motivation to learn.

[1647] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1648] In this invention, the server includes an information processing terminal for inputting content that the user wants to learn, natural language processing engine means for receiving and analyzing the learning content input from the terminal, means for the information processing device having a function of suggesting an optimal learning course based on the analysis results, means for the information processing device having a function of providing a confirmation test based on the user's learning progress, means for the information processing device having a function of providing test preparation content to the user, emotion recognition engine means for the information processing device having a function of monitoring the user's emotional state and optimizing the learning experience, and means for applying discounts to specific communication service users based on communication line information. This allows users to be provided with more highly personalized learning support, maximizing learning effectiveness and maintaining motivation to learn.

[1649] "User" refers to an individual or corporation that uses the online learning system to input what they want to learn and receive learning content.

[1650] "Information processing terminal" refers to a computer or mobile terminal that allows users to input study content and display study courses and content.

[1651] "Information processing device" refers to servers and cloud computing resources that handle all aspects of the learning system, such as receiving and analyzing the content to be learned, proposing learning courses, providing confirmation tests, and providing exam preparation content.

[1652] A "natural language processing engine" refers to a software engine that analyzes the text data of the learning content entered by the user and extracts important keywords.

[1653] "Study course suggestion function" refers to a function that suggests the most suitable study course to the user based on the results of analysis by the natural language processing engine.

[1654] "Confirmation test provision function" refers to a function for providing confirmation tests at appropriate times based on the user's learning progress.

[1655] "Exam preparation content provision function" refers to a function that provides users with appropriate exam preparation content based on the exam information entered by the user.

[1656] An "emotion recognition engine" is an engine that analyzes a user's facial expressions, voice, and behavioral data to recognize their emotional state and optimize the learning experience.

[1657] "Communication line information" refers to information about the internet line and communication services used by the user.

[1658] The "discount application function" refers to a function for applying a discount to a specific communication service user based on communication line information.

[1659] The present invention relates to an online learning system that includes an information processing terminal used by a user, an information processing device having a natural language processing engine, an emotion recognition engine, and a discount application function based on communication line information. The following describes an embodiment of the present invention in detail.

[1660] Input and analyze what you want to learn

[1661] Users access the online learning system using a web browser on an information processing device such as a PC or mobile device. They enter what they want to learn into the input form on the website and click the submit button. For example, they might enter "data science." The information processing device analyzes the input text using a natural language processing engine implemented in Python and extracts key keywords. The information processing device then searches for related learning courses in a MySQL database and suggests the most suitable course.

[1662] Course suggestions and selection

[1663] The information processing device sends a list of learning courses to be suggested to the user to the information processing terminal. The terminal uses JavaScript to display the list of learning courses on the screen. The user selects the desired course from the displayed course and clicks the start button. For example, the user selects "Python for Data Science."

[1664] Providing learning content and an emotional engine

[1665] The information processing device retrieves content related to the learning course selected by the user from a database and sequentially delivers it to the user's device. The device displays the received content in HTML format, allowing the user to proceed with their learning. For example, video lectures may be played and learning materials in PDF format may be available for download. The device also collects the user's emotional data from the webcam and microphone and transmits it to the server in real time. The information processing device analyzes the user's emotional state using an emotion recognition engine based on TensorFlow and provides feedback, such as adjusting the difficulty of the learning content, if the user is feeling stressed.

[1666] Providing confirmation tests and feedback

[1667] The information processing device tracks the user's learning progress and provides confirmation tests at appropriate times. The user answers the confirmation test and clicks the submit button. The information processing device receives the answers and scores them using an automated evaluation system implemented in Ruby. Feedback is generated based on the scoring results and sent to the device. The device displays the feedback on the screen, allowing the user to understand their level of understanding and areas for improvement.

[1668] Providing exam preparation content

[1669] Users can input specific exam information, for example, "AWS Certified Solutions Architect." The information processing device retrieves appropriate exam preparation content from a database based on that information and delivers it to the user's device. The device then displays the received content in HTML format, allowing the user to continue preparing for the exam.

[1670] Discounts applied

[1671] The information processing device checks the user's communication line information and applies a discount to users of a specific communication service. For example, if the user is a subscriber of a specific communication carrier, the information processing device calculates the discount price and sends the fee information to the terminal. The terminal displays the discount information on its screen.

[1672] Examples of concrete examples and prompts

[1673] Specific examples

[1674] Learning content: "Data Science"

[1675] Suggested courses: "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science."

[1676] Course selected: "Python for Data Science"

[1677] Learning content: video lectures, PDF materials

[1678] Test result: "80% correct. I need more practice with loop syntax."

[1679] Exam Information: "AWS Certified Solutions Architect"

[1680] Exam preparation content provided: "AWS exam question bank" and "AWS related materials"

[1681] Prompt Sentence Examples

[1682] 1. "I received the Python for Data Science course materials, what's next?"

[1683] 2. "If my learning progress is slow, how can I improve it?"

[1684] 3. "Please give me feedback on the questions I got wrong on the confirmation test."

[1685] 4. "Which test prep content is most effective?"

[1686] As described above, the online learning system of the present invention allows users to study efficiently and easily, and optimizes the learning experience through emotion recognition, thereby maximizing learning effectiveness.

[1687] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1688] Step 1:

[1689] A user accesses the learning system's website from a web browser. The user uses an information processing terminal to enter a specified URL and display the online learning system's home page. The input here is the user's action (URL input and access), and the output is the website's home page displayed on the terminal. Specifically, the web browser sends an HTTP request, and the server returns an HTTP response.

[1690] Step 2:

[1691] The user enters what they want to learn into the input form and clicks the submit button. For example, enter "data science" into the text box and submit. The input is what the user wants to learn (text data), and the output is that this data is sent to the server. Specifically, the user enters text on the keyboard and clicks the "Submit" button.

[1692] Step 3:

[1693] The server receives the learning content sent from the device and analyzes it using a natural language processing engine. The input is the text data sent by the user, and the main keywords are extracted as a result of the analysis. Specifically, the server uses an NLP engine implemented in Python to extract the keyword "data science" from the text. The output is a list of keywords.

[1694] Step 4:

[1695] The server searches the database for relevant learning courses based on the analyzed keywords. The input is the extracted keyword list, and the output is a list of learning courses retrieved from the database. The server uses SQL queries to search the MySQL database and retrieve courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science."

[1696] Step 5:

[1697] The server sends the selected course list to the user's device. The input is the list of courses, and the output is that this list is displayed on the device. Specifically, the server sends the course list in JSON format as an HTTP response, and the device receives it.

[1698] Step 6:

[1699] The device displays the received learning course list on the screen. The input is the course list received from the server, and the output is a list of learning courses that the user can view. Specifically, it uses JavaScript to generate HTML content and displays it to the user as a list.

[1700] Step 7:

[1701] The user selects the desired course and clicks the start button. For example, select "Python for Data Science." The input is the user's selection action, and the output is the ID of the selected course being sent to the server. Specifically, the user clicks on the course with the mouse and presses the "Start" button.

[1702] Step 8:

[1703] The server retrieves content corresponding to the user's selected learning course from the database. The input is the selected course ID, and the output is the corresponding learning material and video data. Specifically, the server retrieves the learning material and video data from the MySQL database using SQL queries.

[1704] Step 9:

[1705] The server sequentially distributes the acquired learning content to the user's device. The input is the acquired learning content, and the output is the teaching materials and videos distributed to the device. Specifically, the server sends the content as an HTTP response, and the device receives it.

[1706] Step 10:

[1707] The device displays the received learning content, allowing the user to progress through their studies. The input is the received content data, and the output is the learning materials and videos displayed to the user. Specifically, the device uses HTML and JavaScript to render the learning materials and videos and display them on the screen.

[1708] Step 11:

[1709] The device collects user emotional data from a webcam and microphone and sends it to a server. The input is the user's facial expression, voice, typing speed, etc., and the output is the transmission of the collected emotional data. Specifically, the device acquires sensor data in real time and sends it to the server via an API.

[1710] Step 12:

[1711] The server uses an emotion recognition engine to analyze the user's emotional data and provide feedback as needed. The input is the collected emotional data, and the output is feedback information. Specifically, it analyzes emotions using a TensorFlow model and adjusts the learning difficulty, such as lowering the learning difficulty, if the user is feeling stressed.

[1712] Step 13:

[1713] The server tracks the user's learning progress and provides confirmation tests at appropriate times. The input is the learning log data, and the output is the content of the confirmation test. Specifically, the server monitors the progress and generates a confirmation test when certain conditions are met.

[1714] Step 14:

[1715] The user answers the confirmation test and clicks the "Submit" button. The input is the user's test answer, and the output is the answer data sent to the server. Specifically, the user answers the questions on the screen and presses the "Submit" button.

[1716] Step 15:

[1717] The server receives the answers and grades them with an automated evaluation system. The input is the user's test answer data, and the output is the test score. Specifically, the evaluation system, implemented in Ruby, analyzes the answers and calculates the score.

[1718] Step 16:

[1719] The server generates feedback and sends it to the user's device. The input is the scoring result data, and the output is feedback information. Specifically, the server generates feedback including correct / incorrect answers and advice, and sends it to the device.

[1720] Step 17:

[1721] The device displays feedback, allowing the user to understand their level of understanding and areas for improvement. The input is feedback data, and the output is feedback that is displayed to the user. Specifically, the feedback is displayed on the screen using HTML and JavaScript.

[1722] Step 18:

[1723] The user enters exam information and clicks the submit button. For example, they enter "AWS Certified Solutions Architect." The input is the user's exam information, and the output is the data sent to the server. Specifically, the user enters text and clicks the "Submit" button.

[1724] Step 19:

[1725] The server retrieves the appropriate exam preparation content from the database based on the exam information. The input is the exam information data, and the output is the retrieved exam preparation content. Specifically, the server uses SQL queries to retrieve the relevant content.

[1726] Step 20:

[1727] The server delivers the acquired test preparation content to the user's device. The input is the test preparation content, and the output is the content delivered to the device. Specifically, the server sends the content as an HTTP response, and the device receives it.

[1728] Step 21:

[1729] The device displays the received test preparation content, which the user can use to prepare for the test. The input is the received content data, and the output is the content that is displayed to the user. Specifically, the content is rendered using HTML and JavaScript and displayed on the screen.

[1730] Step 22:

[1731] The server checks the user's communication line information and applies discounts to specific communication service users. The input is communication line information, and the output is the calculated discount price. Specifically, the server analyzes the IP address and determines whether the discount applies.

[1732] Step 23:

[1733] The server calculates the discount price and displays the price information on the terminal. The input is the discount price calculation data, and the output is the price information displayed on the terminal. Specifically, the server sends the calculation result in JSON format to the terminal, and the terminal displays it on the screen.

[1734] These are the specific processing steps of the online learning system of the present invention, which allows users to learn efficiently and easily, and also optimizes the learning experience through emotion recognition.

[1735] (Application example 2)

[1736] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1737] Online learning systems are required to not only suggest appropriate learning courses based on the user's learning content and progress and provide confirmation tests, but also to monitor the user's emotional state to optimize the learning experience. However, many current online learning systems lack the functionality to consider the user's emotional state and do not provide sufficient support to maximize learning efficiency. Furthermore, insufficient feedback and adjustment of the learning experience according to the user's emotional state leads to a decrease in users' motivation to learn and a decrease in learning effectiveness.

[1738] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a terminal for the user to input the content they want to learn, natural language processing means for receiving and analyzing the learning content input from the terminal, means for proposing an optimal learning course based on the analysis results, means for providing a confirmation test based on the user's learning progress, means for providing test preparation content to the user, means for applying discounts to specific communication service users based on communication line information, emotion recognition means for monitoring the user's emotional state and providing feedback, and means for adjusting the learning experience according to the emotional state. This makes it possible to grasp the user's emotional state in real time and provide an optimal learning experience according to that state.

[1739] "Terminal" means a device that allows a user to input what they want to learn and receive and display learning content.

[1740] A "server" is a computer system that receives, analyzes, and processes learning content sent by users.

[1741] "Natural language processing means" is a technology for analyzing text entered by a user and extracting key keywords and related information.

[1742] "Learning Course" means a series of educational content or lectures offered for User learning.

[1743] A "validation test" is a test provided to assess a user's learning progress and includes questions that measure the user's understanding.

[1744] "Exam Preparation Content" refers to study materials and practice questions that users need to pass a particular exam or certification.

[1745] "Communication line information" is data that indicates information about the Internet connection and mobile communications used by the user.

[1746] A "means for applying discounts" is a system that provides discounts on learning courses or service fees to users who meet certain conditions.

[1747] "Emotion recognition means" is a technology that detects and analyzes a user's emotional state from their facial expressions, voice, behavior, etc.

[1748] "Feedback" refers to guidance and advice provided based on a user's learning progress and emotional state.

[1749] "Means for adjusting the learning experience" refers to technology that dynamically changes the difficulty and content of a learning course depending on the user's emotional state.

[1750] This invention relates to an online learning system that inputs what a user wants to learn, suggests an optimal learning course based on that input, and monitors the user's emotional state to provide feedback.

[1751] The online learning system of the present invention consists of the following components: First, a user inputs the content they want to learn using a terminal. This terminal can be any device such as a PC, smartphone, smart glasses, or head-mounted display, and is connected to a server via a network.

[1752] The server receives the learning content sent by the user from the device and analyzes it using a natural language processing engine, which uses, for example, Google's NLU API or other common natural language analysis technologies, to extract the user's learning objectives and keywords.

[1753] The server then searches the database for the most suitable learning course based on the extracted keywords and suggests it to the user. At this stage, the server also monitors the user's learning progress and provides timely review tests and exam preparation content.

[1754] Furthermore, the system uses emotion recognition to monitor the user's emotional state in real time. This emotion recognition is achieved by analyzing the user's facial expressions, voice, typing speed, and other behavioral data. The server uses this data to determine the user's emotional state and adjust the learning experience accordingly. This technology can temporarily lower the difficulty of the learning course if the user is feeling stressed, thereby maintaining the user's motivation and efficiency in learning.

[1755] As a concrete example, consider a case where a user wants to learn "data science." In this case, the user enters the keyword "data science" into their device, and the server analyzes this keyword using a natural language processing engine. After analysis, the server suggests optimal learning courses such as "Python for Data Science," "Machine Learning Basics," and "Statistics for Data Science." When the user selects "Python for Data Science" and begins learning, the server monitors their emotional state in real time and adjusts the learning experience. It also provides confirmation tests at appropriate times according to the user's learning progress and provides feedback based on the results.

[1756] Examples of prompts t...

Claims

1. A terminal for users to input what they want to learn, a server having a natural language processing means for receiving and analyzing the learning content input from the terminal; means for the server to propose an optimal learning course based on the analysis results; a means for the server to provide a confirmation test based on the user's learning progress; means for the server to provide test preparation content to users; A means for applying a discount to a specific communication service user based on communication line information; A system including:

2. 2. The system according to claim 1, wherein the server comprises means for analyzing input learning content using a natural language processing engine and extracting keywords.

3. 2. The system of claim 1, wherein the terminal has means for displaying the results of the validation test as feedback to the user.

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