Program, method, information processing device and system

Abstract

To address such a problem that it is not possible to output explanatory texts suitable for learning of users.SOLUTION: A program causing a computer including a processor and a storage unit to execute: an attribute acquisition step of acquiring attribute information regarding a first user; and an explanatory text acquisition step of acquiring an explanatory text related to the first user from a large-scale language model on the basis of the attribute information regarding the first user.SELECTED DRAWING: Figure 12

Description

Technical Field

[0001] The present disclosure relates to a program, a method, an information processing apparatus, and a system.

Background Art

[0002] Learning support technologies using information processing terminals are known. Patent Document 1 discloses a technology for evaluating the answer content of a learner and providing appropriate information to the learner or learning supporter. Patent Document 2 discloses a learning support technology capable of improving the learning motivation of registered users (students) and enhancing the learning effect.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0004] There is a problem that an explanatory text suitable for the user's learning cannot be output. Therefore, the present disclosure has been made to solve the above problems, and its object is to provide a technology for outputting an explanatory text suitable for the user's learning.

Means for Solving the Problems

[0005] A program for causing a computer including a processor and a storage unit to execute, wherein the processor executes an attribute acquisition step of acquiring attribute information regarding a first user, and an explanatory text acquisition step of acquiring an explanatory text related to the first user from a large language model based on the attribute information regarding the first user.

Effects of the Invention

[0006] According to the present disclosure, it is possible to output an explanatory text suitable for user learning.

Brief Description of the Drawings

[0007]

Figure 1

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Modes for Carrying Out the Invention

[0008] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In all the drawings for describing the embodiments, the same reference numerals are given to common components, and repeated descriptions are omitted. Note that the following embodiments do not unduly limit the content of the present disclosure described in the claims. Also, not all the components shown in the embodiments are essential components of the present disclosure. Further, each drawing is a schematic diagram and is not necessarily drawn precisely.

[0009] <Configuration of System 1> System 1 in the present disclosure is an information processing system that supports educational services provided by teachers who teach students in educational institutions such as schools and learning schools. System 1 includes an information processing device of server 10, first user terminal 20, second user terminal 30, and large language model 50, which are connected via network N. FIG. 1 is a block diagram showing the functional configuration of System 1. FIG. 2 is a block diagram showing the functional configuration of server 10. FIG. 3 is a block diagram showing the functional configuration of first user terminal 20. FIG. 4 is a block diagram showing the functional configuration of second user terminal 30.

[0010] Each information processing device is configured by a computer including an arithmetic device and a storage device. The basic hardware configuration of the computer and the basic functional configuration of the computer realized by the hardware configuration will be described later. For each of server 10, first user terminal 20, second user terminal 30, and large language model 50, descriptions overlapping with the basic hardware configuration of the computer and the basic functional configuration of the computer described later are omitted.

[0011] <Configuration of Server 10> Server 10 is an information processing device that supports educational services provided by teachers to students. Server 10 includes storage unit 101 and control unit 104.

[0012] <Configuration of the storage unit 101 of server 10> The storage unit 101 of server 10 includes an application program 1011, a user table 1012, a group table 1013, a homework table 1014, and a teaching material master 1021.

[0013] The application program 1011 is a program for causing the control unit 104 of server 10 to function as each functional unit. The application program 1011 includes applications such as a web browser application.

[0014] The user table 1012 is a table that stores and manages information of member users (hereinafter referred to as users) who use the service. By registering for use of the service, the information of the user is stored in a new record of the user table 1012. Thereby, the user can use the service according to the present disclosure. In the present disclosure, user information of users related to students (first users), teachers (second users), and administrators of the information processing service according to the present disclosure (administrator users) is stored. The user table 1012 is a table having columns of user ID, user name, attribute data, and group ID with the user ID as the primary key. FIG. 5 is a diagram showing the data structure of the user table 1012.

[0015] The user ID is an item that stores user identification information for identifying a user. The user identification information is an item for which a unique value is set for each user. The user name is an item that stores the name of the user. The user name may be set to an arbitrary string such as a nickname instead of the name. The attribute data includes the following information. In particular, the attribute data includes information regarding proficiency in learning content. · Personal information: name, date of birth, gender, nationality, ethnicity · Contact information: address, telephone number, email address · Answer information: grade and class, courses taken, proficiency level, learning progress, test scores and evaluations, attendance status · Health information: allergies, medical history, special health considerations · Psychological traits: learning style · Interests and hobbies: club activities, areas of interest and hobbies · Educational considerations: information on the presence or absence of learning disabilities, language disorders, intellectual disabilities, etc. Proficiency level is an indicator that shows how well a student understands and has mastered the learning content in a specific learning unit. In an online learning service, proficiency level is used to evaluate the learning progress of individual students and provide appropriate learning support. Proficiency level is an indicator calculated based on data (answer information such as correct / incorrect answers and answer times) obtained during the process of students solving problems or tasks within the unit, watching learning materials, or reading comprehension. Specifically, proficiency level includes answer information such as the correctness of answers and answer times when students solve each problem. Proficiency level may include a multi-level indicator / rank evaluated based on answer information, such as A (well understood), B (generally understood), C (not well understood), D (hardly understood). Group ID is an item that stores group identification information for identifying a group. Group identification information is an item with a unique value set for each group information.

[0016] Group table 1013 is a table for storing and managing information related to groups (group information). Group table 1013 is a table with columns for group ID, group name, feature quantity, and description text, with group ID as the primary key. Figure 6 is a diagram showing the data structure of group table 1013.

[0017] Group ID is an item that stores group identification information for identifying a group. Group identification information is an item with a unique value set for each group information. The group name is an item for storing the name of the group. The group name can be set to any string. The feature quantity is an item for storing statistical quantities and state quantities that characterize the group. Specifically, the feature quantity is calculated based on one or more attribute data of a plurality of users included in the group and combinations thereof. The feature quantity is calculated based on answer information such as the correctness and answer time of a plurality of users included in the group. The feature quantity may include the average of grades (correct answer rates), answer times, etc. for each learning unit of a plurality of users included in the group. The feature quantity may include the average of the ranks (A to D) of a plurality of users included in the group. In addition, the feature quantity may include information indicating the degree of proficiency of a plurality of users included in groups such as high proficiency, medium proficiency, and low proficiency. The explanatory text includes information on learning tasks and recommended questions for one or more users included in the group. Specifically, the learning task is set based on the learning subjects and learning content that the user is currently engaged in. It includes tasks to be achieved based on the strengths and weaknesses of the user, the ongoing curriculum, or specific evaluation criteria. The recommended questions correspond to these learning tasks and include learning materials for the user to deepen understanding and improve proficiency in learning. The explanatory text may include advice, feedback, learning guidance, learning progress, future learning plans, improvement measures for learning, recommendations for additional learning materials, etc. regarding the learning of one or more users included in the group.

[0018] The assignment table 1014 is a table for storing and managing information (assignment information) regarding assignments (learning materials) presented to students (first users) and the answer content for the assignments. The assignment table 1014 is a table having columns for assignment ID, questioner ID, student ID, teaching material ID, and answer data. Figure 7 is a diagram showing the data structure of the assignment table 1014.

[0019] The assignment ID is an item that stores assignment identification information for identifying assignments. The assignment identification information is an item for which a unique value is set for each piece of assignment information. The questioner ID is an item that stores the user identification information of the questioner (teacher, second user). The student ID is an item that stores the user identification information of the student (first user). The teaching material ID is an item that stores teaching material identification information for identifying learning teaching materials. The answer data is an item that stores the student's answer content for the learning teaching material. The answer data may include answer information such as the student's correct or incorrect answers and answer time for the learning teaching material.

[0020] The teaching material master 1021 is a table for storing and managing information (teaching material information) related to learning teaching materials. The teaching material master 1021 is a table having columns for the teaching material ID and teaching material data, with the teaching material ID as the primary key. Figure 8 is a diagram showing the data structure of the teaching material master 1021.

[0021] The teaching material ID is an item that stores teaching material identification information for identifying learning teaching materials. The teaching material identification information is an item for which a unique value is set for each piece of learning teaching material information. The teaching material data is an item that stores information about the learning teaching material. Specifically, the teaching material data includes the following information. · Textbook: A teaching material that describes the basic content of each subject · Workbook / Exercise book: A teaching material for deepening learning through problem exercises and practical practice

[0022] <Configuration of the control unit 104 of the server 10> The control unit 104 of the server 10 includes a user registration control unit 1041, a grouping unit 1042, an explanatory text creation unit 1043, and a question setting unit 1044. The control unit 104 realizes each functional unit by executing the application program 1011 stored in the storage unit 101.

[0023] The user registration control unit 1041 performs a process of storing information of a user who wishes to use the service according to the present disclosure in the user table 1012. The information stored in the user table 1012 is input by the user from an arbitrary information processing terminal to a web page or the like operated by the service provider, entered into a predetermined input form, and transmitted to the server 10. The user registration control unit 1041 stores the received information in a new record in the user table 1012, and the user registration is completed. As a result, the user stored in the user table 1012 can use the service. Prior to the registration of user information by the user registration control unit 1041 in the user table 1012, the service provider may perform a predetermined review to restrict the use of the service by the user. The user ID may be any character string or number that can identify the user, any character string or number desired by the user, or the user registration control unit 1041 may automatically set any character string or number.

[0024] The grouping unit 1042 executes a grouping process. Details will be described later.

[0025] The description creation unit 1043 executes a description creation process. Details will be described later.

[0026] The question presenting unit 1044 executes a question presenting process. Details will be described later.

[0027] <Configuration of the First User Terminal 20> The first user terminal 20 is an information processing device operated by a user who uses the service. The first user terminal 20 may be, for example, a mobile terminal such as a smartphone or a tablet, or a stationary PC (Personal Computer) or a laptop PC. It may also be a wearable terminal such as an HMD (Head Mount Display) or a wristwatch-type terminal. The first user terminal 20 includes a storage unit 201, a control unit 204, an input device 206, and an output device 208.

[0028] <Configuration of the storage unit 201 of the first user terminal 20> The storage unit 201 of the first user terminal 20 includes a first user ID 2011 and an application program 2012.

[0029] The first user ID 2011 is the account ID of the first user. The user transmits the first user ID 2011 from the first user terminal 20 to the server 10. The server 10 identifies the user based on the first user ID 2011 and provides the service according to the present disclosure to the user. Note that the first user ID 2011 includes information such as a session ID temporarily assigned by the server 10 when identifying the user using the first user terminal 20.

[0030] The application program 2012 may be stored in advance in the storage unit 201, or may be configured to be downloaded from a web server or the like operated by a service provider via a communication IF. The application program 2012 includes applications such as a web browser application. The application program 2012 includes an interpreter-type programming language such as JavaScript (registered trademark) that is executed on a web browser application stored in the first user terminal 20.

[0031] <Configuration of the control unit 204 of the first user terminal 20> The control unit 204 of the first user terminal 20 includes an input control unit 2041 and an output control unit 2042. The control unit 204 realizes each functional unit by executing the application program 2012 stored in the storage unit 201.

[0032] <Configuration of the input device 206 of the first user terminal 20> The input device 206 of the first user terminal 20 includes a camera 2061, a microphone 2062, a position information sensor 2063, a motion sensor 2064, and a touch device 2065.

[0033] <Configuration of the output device 208 of the first user terminal 20> The output device 208 of the first user terminal 20 includes a display 2081 and a speaker 2082.

[0034] <Configuration of the second user terminal 30> The second user terminal 30 is an information processing device operated by a user who uses the service. The second user terminal 30 may be, for example, a mobile terminal such as a smartphone or a tablet, or a stationary PC (Personal Computer) or a laptop PC. It may also be a wearable terminal such as an HMD (Head Mount Display) or a wristwatch-type terminal. The second user terminal 30 includes a storage unit 301, a control unit 304, an input device 306, and an output device 308.

[0035] <Configuration of the storage unit 301 of the second user terminal 30> The storage unit 301 of the second user terminal 30 includes a second user ID 3011 and an application program 3012.

[0036] The second user ID 3011 is the account ID of the second user. The user transmits the second user ID 3011 from the second user terminal 30 to the server 10. The server 10 identifies the user based on the second user ID 3011 and provides the service according to the present disclosure to the user. Note that the second user ID 3011 includes information such as a session ID temporarily assigned by the server 10 when identifying the user using the second user terminal 30.

[0037] The application program 3012 may be stored in advance in the storage unit 301, or may be configured to be downloaded from a web server or the like operated by a service provider via a communication IF. The application program 3012 includes an application such as a web browser application. The application program 3012 includes an interpreter-type programming language such as JavaScript (registered trademark) that is executed on a web browser application stored in the second user terminal 30.

[0038] <Configuration of the control unit 304 of the second user terminal 30> The control unit 304 of the second user terminal 30 includes an input control unit 3041 and an output control unit 3042. The control unit 304 realizes each functional unit by executing the application program 3012 stored in the storage unit 301.

[0039] <Configuration of the input device 306 of the second user terminal 30> The input device 306 of the second user terminal 30 includes a camera 3061, a microphone 3062, a position information sensor 3063, a motion sensor 3064, and a touch device 3065.

[0040] <Configuration of the output device 308 of the second user terminal 30> The output device 308 of the second user terminal 30 includes a display 3081 and a speaker 3082.

[0041] <Configuration of the large language model 50> A large language model 50 is an artificial intelligence system that learns from a wide range of text data and exhibits high performance in various language-related tasks such as natural language understanding and generation. The large language model 50 analyzes a large amount of document and conversation data and has capabilities such as context understanding, text generation, question answering, translation, and summary creation. The large language model 50 includes, for example, ChatGPT developed by OpenAI and Google Bard developed by Google.

[0042] <Operation of system 1> Hereinafter, each process of system 1 will be described. FIG. 9 is a flowchart showing the operation of the grouping process. FIG. 10 is a flowchart showing the operation of the explanatory text creation process. FIG. 11 is a flowchart showing the operation of the question presentation process. FIG. 12 is an example screen showing the operation of the explanatory text creation process. FIG. 13 is an example screen showing the operation of the question presentation process. FIG. 14 is an example screen showing the operation of the learning material presentation process.

[0043] <Grouping Process> The grouping process is a process of classifying a plurality of students (first users) into a plurality of groups according to the similarity of the student attribute data.

[0044] <Overview of the Grouping Process> The grouping process is a series of processes that acquire the attribute data of a plurality of students, execute a clustering process according to the similarity of the attribute data, classify the plurality of students into a plurality of groups, and calculate the feature amounts for each group.

[0045] The grouping process may be executed at the following timings. · The grouping unit 1042 of the server 10 may execute the grouping process after presenting a test such as an assignment or a problem to a student (first user) in the information processing service according to the present disclosure and confirming the learning effect within a specific range. Before and after the implementation of the test, after confirming the progress of the learning effect in daily classes, the first user is automatically associated with a plurality of groups. The first user can be grouped into a more suitable group according to the latest attribute information. By the question presentation process described later, learning materials and the like can be provided collectively for each of a plurality of first users having the same level of learning proficiency. · Execute according to the input operation of the user related to the administrator of the information processing service according to the present disclosure. It may be configured to execute according to an explicit process for executing the grouping process by the user related to the administrator. · The grouping unit 1042 of the server 10 may execute the grouping process every predetermined period (every hour, every day, every week, every month, etc.).

[0046] <Details of Grouping Process> The details of the grouping process are described below.

[0047] In step S101, the grouping unit 1042 of the server 10 executes an attribute acquisition step of acquiring attribute information including information regarding the proficiency level of the learning content of the learning materials for the first user. The attribute acquisition step acquires attribute information for a plurality of first users. Specifically, the grouping unit 1042 of the server 10 refers to the user table 1012 to acquire attribute data for each of a plurality of students. Note that the grouping unit 1042 of the server 10 may be configured to filter a plurality of students according to predetermined attribute data such as grade and class included in the attribute data, and acquire the attribute data of the student. That is, the grouping unit 1042 of the server 10 may perform grouping processing on some students belonging to a predetermined grade and a predetermined class.

[0048] In step S102, the grouping unit 1042 of the server 10 executes a group step of associating a plurality of first users with one or more groups based on the attribute information acquired in the attribute acquisition step. The group step associates a plurality of first users with one or more groups according to the similarity of the attribute information of the plurality of first users. Specifically, the grouping unit 1042 of the server 10 regards the attribute data as a vector having values for each of a plurality of elements included in the attribute data. The grouping unit 1042 of the server 10 calculates the distance between vectors based on the attribute data of each student by a method such as Euclidean distance, Manhattan distance, cosine similarity, Jaccard similarity, or the like. In particular, it is preferable for the grouping unit 1042 of the server 10 to calculate the similarity of vectors consisting of the similarity of answer information such as the proficiency level of the first user, the correctness of questions, and the answer time. The grouping unit 1042 of the server 10 classifies (clusters) a plurality of first users into a plurality of groups by the following method (one or more methods or a combination thereof) according to the similarity of the acquired attribute data of the plurality of first users. Note that the grouping unit 1042 of the server 10 may apply processing such as an arbitrary normalization method to vector components such as attribute data and proficiency. Even in that case, the processed vector is included in the student's attribute data.

[0049] · K-means method In this method, a plurality of students are classified into K clusters (groups). First, K cluster centers are randomly selected. Next, each student is assigned to the nearest cluster center, and the cluster center is updated. This process is repeated until there is no change in the cluster center. In this method, a plurality of first users can be classified by specifying a plurality of cluster numbers (group numbers). · Hierarchical clustering In this method, first, each student is regarded as an individual cluster (group), and gradually similar clusters are combined. The similarity between clusters is calculated based on criteria such as the shortest distance, the longest distance, and the average distance. This is suitable when the number of clusters is unknown in advance or when you want to understand the data structure in detail. · Density-based clustering (such as DBSCAN) In this method, clusters (groups) are formed based on density (the concentration of data points). An area with a specific density or higher is regarded as a cluster, and an area with a low density around it is treated as noise. This is suitable for data with irregular cluster shapes or data containing noise. · Spectral clustering In this method, dimensionality reduction is performed using the similarity matrix of the data, and then clustering is performed by a method such as K-means. The similarity matrix represents the similarity (or distance) between data points. This is suitable for data with a graph structure or non-linear structure data.

[0050] The grouping unit 1042 of the server 10 classifies the plurality of students obtained in step S102 into a plurality of groups. For example, the grouping unit 1042 of the server 10 classifies a plurality of students (student A, student B, student C, student D) into group A (student A, student C), group B (student B), group C (student D), etc.

[0051] In step S102, the group step executes a step of associating a plurality of first users with one or more groups after the plurality of first users confirm the learning effect in a specific range. Specifically, the grouping unit 1042 of the server 10 may give a test such as an assignment or a problem to a student (first user) in the information processing service according to the present disclosure, and after confirming the learning effect in a specific range, execute the clustering process according to step S102.

[0052] In step S103, the grouping unit 1042 of the server 10 calculates a feature amount for each cluster (group) classified in step S102. Specifically, the grouping unit 1042 of the server 10 aggregates the characteristics of the data points in the cluster (the attribute data of one or more students belonging to the cluster, the proficiency, and the vector based on the answer information), and calculates a feature amount (representative vector) representing the characteristics of the entire cluster.

[0053] For example, the grouping unit 1042 of the server 10 may include the feature amount calculated by the following method in the feature amount for each cluster. The grouping unit 1042 of the server 10 calculates a feature amount based on one or more vectors of the attribute data, proficiency, and answer information of one or more students belonging to the cluster. ·Average vector (average value vector, median vector, mode vector) Calculate the average (statistical values such as average value, median value, mode value) of the vectors of all students belonging to the cluster. The vector of each student includes the proficiency score in each learning unit of the student as an element. Each element of the average vector reflects the average proficiency of the students within that cluster. Note that instead of the average, any statistical value such as the maximum value or minimum value may be used. · Variance, standard deviation Calculate the variance and standard deviation of the attribute data, proficiency, answer information, and vectors within the cluster. Indicates how much the proficiency levels of the students within the cluster vary. · Range (maximum value - minimum value) Calculate the difference between the highest proficiency score and the lowest score within the cluster. Indicates the range of proficiency levels of the students within the cluster. · Feature quantities based on specific indicators For example, any parameters based on specific indicators such as the average correct answer rate or average answer time in a specific learning unit may be included in the feature quantities.

[0054] The grouping unit 1042 of the server 10 associates the classification created in step S102 with the feature quantities calculated in step S103 and stores them in the group name and feature quantity items of a new record in the group table 1013. As a result, group information for classifying students is stored in the group table 1013. The grouping unit 1042 of the server 10 associates and stores the group ID of the group to which the student is classified (the group ID of the newly created record in the group table 1013) in the group ID item of the record specified based on the user ID of the student classified in step S102 in the user table 1012. As a result, the association between the student and the group to which the student belongs is expressed. Also, it is specified which group the student is included in.

[0055] <Explanation text creation process> The explanation text creation process is a process of creating an explanation text for each group.

[0056] <Outline of the explanation text creation process> The description creation process is a series of processes that acquire feature amounts for each group, create a prompt (input text for the large language model for creating a description related to the group) that becomes the input text for the large language model based on the feature amounts, send the created prompt to the large language model, acquire a description from the large language model, and store the acquired description. The description creation unit 1043 of the server 10 executes a description creation process for each of the plurality of group information stored in the group table 1013, and stores the description in association with the group information in the description item of the group table 1013.

[0057] <Details of the description creation process> The details of the description creation process will be described below.

[0058] In step S301, the description creation unit 1043 of the server 10 executes a group information acquisition step of referring to the group table 1013 and acquiring group information including a group name and feature amounts.

[0059] In step S302, the description creation unit 1043 of the server 10 executes a prompt creation step of creating a prompt (input text including an instruction text and a command text for creating a description related to the group) that becomes the input text for the large language model based on the group information including the feature amounts acquired in step S301. The description creation unit 1043 of the server 10 inputs input data including the statistical amounts and the contents of the elements for each element included in the attribute information regarding one or a plurality of first users associated with a predetermined group into the large language model.

[0060] Specifically, the description creation unit 1043 of the server 10 creates the following prompt based on the feature amounts acquired in step S301. Note that the following prompt is an example, and the prompt is not limited to the prompt described below. The feature amounts include the statistical amounts and the contents of the elements for each element included in the attribute data regarding the students.

[0061] 〔Prompt〕 # Instruction Book: The following information is about the learning proficiency in a specific group classified according to the learning proficiency of multiple students. Based on the learning proficiency of the following groups, please output an explanatory text containing information about tasks and recommended questions. # Learning Proficiency of Group A: Question A: Average Correct Answer Rate ·% Average Answering Time · seconds Variance Standard Deviation Question B: Average Correct Answer Rate ·% Average Answering Time · seconds Variance Standard Deviation Question C: Average Correct Answer Rate ·% Average Answering Time · seconds Variance Standard Deviation Learning Unit A: Average Correct Answer Rate ·% Average Answering Time · seconds Variance Standard Deviation Learning Unit B: Average Correct Answer Rate ·% Average Answering Time · seconds Variance Standard Deviation Learning Unit C: Average Correct Answer Rate ·% Average Answering Time · seconds Variance Standard Deviation # Questions Difficult for Group A Content of Question A ··· Content of Question B ··· Content of Question C ··· # Basic Questions to Solve for Group A to Overcome Difficulties Content of Question A ··· Content of Question B ··· Content of Question C ··· # Other Related Questions Content of Question A ··· Content of Question B ··· Content of Question C ··· # Explanatory Text:

[0062] The prompt may include the attribute data of multiple students belonging to the group, rather than the learning proficiency of multiple students belonging to the group. The prompt may include tasks related to learning materials, questions, answering information for each unit, and information related to learning proficiency. Specifically, the prompt may include tasks related to learning proficiency and the content of questions for each group.

[0063] The description creation unit 1043 of the server 10 may not input the attribute information regarding one or more first users associated with a predetermined group into the large language model. Specifically, the description creation unit 1043 of the server 10 may include in the prompt the feature amounts calculated based on the attribute data of a plurality of students, but it is preferable to adopt a configuration that does not include the attribute data, proficiency levels, answer information, etc. of individual students. Thereby, the description creation unit 1043 of the server 10 can refrain from transmitting to the external large language model 50 the attribute data, proficiency levels, answer information, etc., which are the personal information of individual students. For example, it is possible not to transmit the personal information of students to the outside, and it is possible to reduce the risk of personal information leakage and the like.

[0064] In step S303, the description creation unit 1043 of the server 10 executes a prompt transmission step of transmitting the prompt created in the prompt creation step to the large language model 50. Specifically, the description creation unit 1043 of the server 10 transmits a request including the prompt created in step S302 to the endpoint (URL) that accepts the input of the prompt provided by the large language model 50. The description creation unit 1043 of the server 10 may include in the request hyperparameters for controlling the answer text from the large language model 50, such as the model name and temperature of the large language model 50, other than the prompt, for the endpoint.

[0065] In step S304, the description creation unit 1043 of the server 10 executes a description acquisition step of acquiring, based on the attribute information regarding the first user, the description related to the first user from the large language model. The description acquisition step acquires a description including information regarding the tasks and recommended questions of the first user. Further, the description acquisition step acquires a description including information regarding the tasks and recommended questions for each learning unit of the first user. Specifically, in response to the transmission of a request to the large language model 50 in step S303, the description creation unit 1043 of the server 10 receives and obtains a response including the description output by the large language model 50. The description to be obtained is the description output by the large language model 50 based on the student's attribute data, proficiency, answer information, etc. The description includes information about the assignment and recommended questions. The description may also include information about the assignment and recommended questions for each learning unit. The description is exemplified as follows.

[0066] 〔Description〕 #Description: #Assignment: The students in this group understand the degree of polynomials and monomials. However, their ability to represent coefficients, especially for positive integers and -1, is relatively low. Also, their ability to determine whether it is an n-degree expression is slightly low. #Recommended questions: The difficult questions for this group are questions D, E, L, etc. Specifically, this group lacks understanding of knowledge such as F, M, P. Recommended questions for acquiring those knowledge include Q, R, etc.

[0067] The description creation unit 1043 of the server 10 stores the description output in step S304 in the description item of the record of the group information of the group related to the prompt creation in the group table 1013. Thereby, the description is stored in association with each group information. The description creation unit 1043 of the server 10 may present the description obtained in the description acquisition step.

[0068] Specifically, the second user operates the input device 306 of the second user terminal 30, executes a browser application or the like, and opens the description presentation page D1 by inputting the URL of a web page (description presentation page) for executing the description presentation process. The control unit 304 of the second user terminal 30 transmits a request including the second user ID 3011 for opening the description presentation page to the server 10.

[0069] When the server 10 receives a request, it generates an explanatory text presentation page and sends it to the second user terminal 30. The control unit 304 of the second user terminal 30 displays the explanatory text presentation page on the display 3081 of the second user terminal 30 and presents it. FIG. 12 is an example of a screen of an explanatory text presentation screen in the explanatory text presentation process. An explanatory text presentation page D1 is displayed on the display 3081 of the second user terminal 30. The explanatory text presentation page D1 includes group information D11, D12, D13 ··· The group information D11 includes a group name D111, an explanatory text D112, the name of the student included in the group (the user name of the first user) D113, the number of students D114, and a question button D115. Similarly, for the group information D12 and D13, the group names D121, D131, the explanatory texts D122, D132, the name of the student included in the group (the user name of the first user) D123, D133, the number of students D124, D134, and the question buttons D125, D135 are included.

[0070] <Questioning Process> The questioning process is a process of collectively presenting learning materials to a plurality of students (the first user) included in a group.

[0071] <Overview of Questioning Process> The questioning process is a series of processes that accepts the selection of one or more groups from a teacher (the second user), accepts the selection of one or more learning materials from the teacher, assigns the selected one or more learning materials to one or more groups, and presents the assigned one or more learning materials to the students.

[0072] <Details of Questioning Process> The details of the questioning process will be described below.

[0073] In step S501, the questioning unit 1044 of the server 10 executes a teaching material reception step of accepting, from the second user, the selection of one or more learning materials corresponding to the explanatory text acquired in the explanatory text acquisition step for a predetermined group. Specifically, on the explanatory text presentation page D1, the teacher selects the question buttons D115, D125, D135 of the group for which question processing is desired from among the groups included in the group information D11, D12, D13 ···.

[0074] The question setting unit 1044 of the server 10 refers to the teaching material master 1021 to acquire teaching material information including the teaching material ID and teaching material data. Note that the question setting unit 1044 of the server 10 may be configured to filter a plurality of learning teaching materials according to predetermined attribute data such as the grade and class of the group related to the selected question buttons D115, D125, D135, acquire and specify the teaching material information related to the learning teaching material. That is, the teaching material information may be acquired and specified by excluding the teaching material information that has nothing to do with the grade and class of the group.

[0075] The question setting unit 1044 of the server 10 generates a question page based on the teaching material information related to the acquired learning teaching material and transmits it to the second user terminal 30. The control unit 304 of the second user terminal 30 displays and presents the question page on the display 3081 of the second user terminal 30. FIG. 13 is an example screen of a question screen in the question processing. On the display 3081 of the second user terminal 30, a question page D3 is displayed. The question page D3 includes questions D301, D302, D303 ··· for each unit. The questions D301, D302, D303 ··· each include a question name D3011, D3021, D3031 ···, a check box D3012, D3022, D3032 ···, and an assignment button D31. The question page D3 displays a list of questions (learning teaching materials) for each unit. Note that each of the questions D301, D302, D303 ··· is associated with the teaching material ID etc. of the teaching material information acquired from the teaching material master 1021.

[0076] Note that the control unit 304 of the second user terminal 30 may present the questions to the teacher with the check boxes D3012, D3022, D3032 ··· of the questions D301, D302, D303 ··· related to the recommended questions included in the explanatory texts D112, D122, D132 being in a selected state. As a result, the teacher can omit the complicated task of selecting recommended questions, reducing the input workload of the teacher.

[0077] In step S502, the question-issuing unit 1044 of the server 10 executes a teaching material reception step of receiving the selection of one or more teaching materials from the second user for a predetermined group. Specifically, the second user operates the input device 306 of the second user terminal 30 to select check boxes D3012, D3022, D3032, ···. As a result, the second user can select one or more teaching materials from the teaching materials presented in a list on the question-issuing page D3.

[0078] In step S503, the question-issuing unit 1044 of the server 10 executes a teaching material providing step of collectively providing the one or more teaching materials received in the teaching material reception step to one or more first users associated with a predetermined group. Specifically, the second user operates the input device 306 of the second user terminal 30 to select the assignment button D31. The control unit 304 of the second user terminal 30 sends a request to the server 10 for assigning teaching materials to a plurality of students for each group. The request includes the second user ID 3011, the first user IDs of one or more first users included in the group selected in step S501, and one or more teaching material IDs specified based on the check boxes D3012, D3022, D3032, ··· selected in step S502. The question-issuing unit 1044 of the server 10 stores the second user ID 3011, the plurality of first user IDs, and the one or more teaching material IDs included in the request in the items of the question issuer ID, student ID, and teaching material ID of a new record in the assignment table 1014. Specifically, the question-issuing unit 1044 of the server 10 stores a plurality of records in the assignment table 1014 according to the plurality of first user IDs and the plurality of teaching material IDs. As a result, a plurality of teaching materials can be collectively issued to one or more students belonging to the group selected by the teacher in step S501.

[0079] In step S504, the question presenting unit 1044 of the server 10 executes a learning material presenting process for presenting a learning material specified based on the teaching material ID stored in the assignment table 1014 to the first user. Specifically, the first user operates the input device 206 of the first user terminal 20, executes a browser application or the like, and opens a learning material presentation page D5 by inputting the URL or the like of a web page (learning material presentation page) for executing the learning material presenting process. The control unit 204 of the first user terminal 20 transmits a request including the first user ID 2011 for opening the learning material presentation page to the server 10.

[0080] When receiving the request, the question presenting unit 1044 of the server 10 searches the student ID item in the assignment table 1014 based on the first user ID 2011, obtains and specifies the assignment information. Note that the question presenting unit 1044 of the server 10 may obtain only the records in which nothing is stored (null value or blank, etc.) in the answer data item, and exclude the records in which information is stored (the student has already answered) in the answer data item to specify the assignment information. The question presenting unit 1044 of the server 10 searches the teaching material ID item in the teaching material master 1021 based on the obtained teaching material ID, and obtains the teaching material information including the teaching material data. The question presenting unit 1044 of the server 10 generates a learning material presentation page based on the obtained assignment information and teaching material information, and transmits it to the first user terminal 20. The control unit 204 of the first user terminal 20 displays and presents the learning material presentation page D5 on the display 2081 of the first user terminal 20. FIG. 14 is an example screen of a learning material presentation screen in the learning material presenting process. The learning material presentation page D5 is displayed on the display 2081 of the first user terminal 20. The learning material presentation page D5 includes learning materials D51, D52, D53, ···. The learning material D51 includes a question D511 and an answer input field D512. Note that the learning materials D51, D52, D53, ··· are drawn based on the teaching material data included in the teaching material information. The first user operates the input device 206 of the first user terminal 20 to input an answer to problem D511 into the answer input field D512. The control unit 204 of the first user terminal 20 transmits a request including the answer content input in the answer input field D512 and the assignment ID related to problem D511 to the server 10. The question issuing unit 1044 of the server 10 searches the assignment ID item in the assignment table 1014 based on the assignment ID included in the request received from the first user terminal 20, and stores the answer content input in the answer input field D512 in the answer data item of the identified record. Thereby, the answer content for each question issued to the student can be stored in association with each other.

[0081] <Basic Hardware Configuration of a Computer> FIG. 15 is a block diagram showing the basic hardware configuration of a computer 90. The computer 90 includes at least a processor 901, a main memory device 902, an auxiliary storage device 903, and a communication IF 991 (Interface). These are electrically connected to each other by a communication bus 921.

[0082] The processor 901 is hardware for executing an instruction set described in a program. The processor 901 is composed of an arithmetic unit, registers, peripheral circuits, and the like.

[0083] The main memory device 902 is for temporarily storing a program and data processed by the program and the like. For example, it is a volatile memory such as DRAM (Dynamic Random Access Memory).

[0084] The auxiliary storage device 903 is a storage device for storing data and programs. For example, it is a flash memory, HDD (Hard Disc Drive), magneto-optical disk, CD-ROM, DVD-ROM, semiconductor memory, or the like.

[0085] The communication IF991 is an interface for inputting and outputting signals for communicating with other computers via a network using wired or wireless communication standards. The network is composed of various mobile communication systems constructed by the Internet, LAN, wireless base stations, etc. For example, the network includes 3G, 4G, 5G mobile communication systems, LTE (Long Term Evolution), wireless networks (e.g., Wi-Fi (registered trademark)) that can be connected to the Internet by a predetermined access point, etc. When connecting wirelessly, communication protocols such as Z-Wave (registered trademark), ZigBee (registered trademark), Bluetooth (registered trademark), etc. are included. When connecting wired, the network also includes those directly connected by a USB (Universal Serial Bus) cable, etc.

[0086] Note that all or part of each hardware configuration can be provided in a distributed manner among a plurality of computers 90 and connected to each other via a network to virtually realize the computer 90. In this way, the computer 90 is a concept that includes not only a single housing and the computer 90 housed in a case but also a virtualized computer system.

[0087] <Basic Functional Configuration of Computer 90> The functional configuration of the computer realized by the basic hardware configuration (Figure 15) of the computer 90 will be described. The computer includes at least functional units of a control unit, a storage unit, and a communication unit.

[0088] Note that the functional units included in the computer 90 can also be realized by providing all or part of each functional unit in a distributed manner among a plurality of computers 90 connected to each other via a network. The computer 90 is a concept that includes not only a single computer 90 but also a virtualized computer system.

[0089] The control unit is realized by the processor 901 reading out various programs stored in the auxiliary storage device 903 and expanding them in the main storage device 902, and executing processing according to the programs. The control unit can realize functional units that perform various information processes according to the types of programs. As a result, the computer is realized as an information processing device that performs information processing.

[0090] The storage unit is realized by the main storage device 902 and the auxiliary storage device 903. The storage unit stores data, various programs, and various databases. Also, the processor 901 can secure a storage area corresponding to the storage unit in the main storage device 902 or the auxiliary storage device 903 according to the program. Further, the control unit can cause the processor 901 to execute addition, update, and deletion processing of the data stored in the storage unit according to various programs.

[0091] The database refers to a relational database and is for managing a table in a tabular format structurally defined by rows and columns, and a set of data called a master, in association with each other. In a database, a table is called a table, a master, a column of a table is called a column, and a row of a table is called a record. In a relational database, the relationship between tables and masters can be set and associated. Normally, a column serving as a primary key for uniquely identifying a record is set for each table and each master, but setting a primary key for a column is not essential. The control unit can cause the processor 901 to execute addition, deletion, and update of records in a specific table and master stored in the storage unit according to various programs. Also, by storing data, various programs, and various databases in the storage unit, the information processing device and information processing system according to the present disclosure can be regarded as being manufactured.

[0092] Note that the database and master in the present disclosure may include any data structure (such as a list, dictionary, associative array, object, etc.) in which information is structurally defined. The data structure shall also include data that can be regarded as a data structure by combining data with functions, classes, methods, etc. described in any programming language.

[0093] The communication unit is realized by the communication IF991. The communication unit realizes the function of communicating with other computers 90 via a network. The communication unit can receive information transmitted from other computers 90 and input it to the control unit. The control unit can cause the processor 901 to execute information processing on the received information according to various programs. Also, the communication unit can transmit the information output from the control unit to other computers 90.

[0094] <Supplementary Note> The matters described in each of the above embodiments are appended below.

[0095] (Supplementary Note 1) A program for causing a computer including a processor and a storage unit to execute, the program causing the processor to execute an attribute acquisition step (S101) of acquiring attribute information regarding a first user, and an explanatory text acquisition step (S304) of acquiring an explanatory text related to the first user from a large language model based on the attribute information regarding the first user. Thereby, an explanatory text suitable for the learning of the first user can be acquired according to the attribute information of the first user (student).

[0096] (Supplementary Note 2) The attribute acquisition step (S101) is the step of acquiring attribute information including information regarding the proficiency of the learning content of the learning material regarding the first user, for the program described in Supplementary Note 1. Thereby, an explanatory text suitable for the learning of the first user can be acquired according to the learning proficiency of the first user.

[0097] (Supplementary Note 3) The description acquisition step (S304) is a step of acquiring a description including information on the problems and recommended problems of the first user, as described in Appendix 1 of the program. Thereby, it is possible to acquire a description including problems and recommended problems (recommended questions) suitable for the learning of the first user according to the attribute information of the first user.

[0098] (Appendix 4) The description acquisition step (S304) is a step of acquiring a description including information on the problems and recommended problems for each learning unit of the first user, as described in Appendix 3 of the program. Thereby, it is possible to acquire a description including problems and recommended problems (recommended questions) for each learning unit suitable for the learning of the first user according to the attribute information of the first user.

[0099] (Appendix 5) The attribute acquisition step (S101) is a step of acquiring attribute information on a plurality of first users, and the processor executes a group step (S102) of associating the plurality of first users with one or more groups based on the attribute information acquired in the attribute acquisition step. The description acquisition step (S304) is a step of acquiring a description related to a predetermined group from a large language model based on the attribute information related to one or more first users associated with the predetermined group, as described in Appendix 1 of the program. Thereby, it is possible to group the first users based on the attribute information and acquire a description suitable for learning for each group.

[0100] (Appendix 6) The description acquisition step (S304) is a step of inputting input data including the statistical quantity and the content of each element included in the attribute information related to one or more first users associated with a predetermined group into a large language model, thereby acquiring a description related to the predetermined group, as described in Appendix 5 of the program. As a result, it is possible to obtain an explanatory text regarding a predetermined group by using, as input data, the statistical quantities (feature quantities) for each individual element included in the attribute information of an individual first user, the content (definition) of the elements, and the like. The explanatory text may include information regarding tasks and recommended problems for each learning unit.

[0101] (Appendix 7) The explanatory text acquisition step (S304) is a program described in Appendix 6, which is a step of not inputting the attribute information regarding one or more first users associated with a predetermined group into a large language model. As a result, it is possible to obtain an explanatory text regarding a predetermined group without inputting personal information such as the attribute information of an individual first user into the large language model. Without transmitting the attribute information of an individual first user or the like to an external large language model or the like, it is possible to obtain an appropriate explanatory text for each group according to the attribute information of each first user.

[0102] (Appendix 8) A program described in Appendix 7, in which a processor executes a learning material reception step (S502) of receiving, from a second user, a selection of one or more learning materials according to the explanatory text obtained in the explanatory text acquisition step for a predetermined group, and a learning material provision step (S503) of collectively providing the one or more learning materials received in the learning material reception step to one or more first users associated with the predetermined group. As a result, the second user (teacher) can select learning materials for each of the plurality of first users included in the group according to the obtained explanatory text, and can collectively provide the selected learning materials for each group.

[0103] (Appendix 9) The attribute acquisition step (S101) is a step of acquiring attribute information regarding a plurality of first users. Based on the attribute information acquired by the processor in the attribute acquisition step, a grouping step (S102) of associating the plurality of first users with one or more groups, and a teaching material providing step (S503) of collectively providing learning materials to one or more first users associated with a predetermined group are executed. The program described in Appendix 1. Accordingly, learning materials can be collectively provided for each of the plurality of first users included in the group based on the attribute information.

[0104] (Appendix 10) The processor executes a teaching material reception step (S501) of receiving a selection of one or more learning materials from a second user for a predetermined group. The teaching material providing step (S503) is a step of collectively providing the one or more learning materials received in the teaching material reception step to one or more first users associated with the predetermined group. The program described in Appendix 9. Accordingly, the second user (teacher) can select learning materials for each of the plurality of first users included in the group and collectively provide the selected learning materials for each group.

[0105] (Appendix 11) The grouping step (S102) is a step of associating a plurality of first users with one or more groups according to the similarity of the attribute information of the plurality of first users. The program described in Appendix 5 or Appendix 10. Accordingly, the first users can be grouped according to the similarity of their attribute information. For example, according to the similarity such as the learning proficiency of the first users, a plurality of first users having the same level of learning proficiency can be grouped into the same group. Also, learning materials and the like can be collectively provided for each of the plurality of first users having the same level of learning proficiency.

[0106] (Appendix 12) The group step (S102) is a step of associating a plurality of first users with one or more groups after the plurality of first users have confirmed the learning effect within a specific range, which is the program described in Appendix 5 or Appendix 10. As a result, after confirming the progress of the learning effect in daily classes before and after the implementation of the test, the first user is automatically associated with a plurality of groups. For example, a configuration for updating the attribute information (learning proficiency) of the first user during the test is suitable. In this case, the first user can be grouped into a more suitable group according to the latest attribute information. Learning materials and the like can be provided collectively for each of the plurality of first users having the same level of learning proficiency.

[0107] (Appendix 13) A method executed by a computer including a processor and a memory, wherein the processor executes all the steps executed in the invention according to any one of Appendices 1 to 10. As a result, an explanatory text suitable for the learning of the first user can be obtained according to the attribute information of the first user (student).

[0108] (Appendix 14) An information processing apparatus including a control unit and a storage unit, wherein the control unit executes all the steps executed in the invention according to any one of Appendices 1 to 10. As a result, an explanatory text suitable for the learning of the first user can be obtained according to the attribute information of the first user (student).

[0109] (Appendix 15) A system including means for executing all the steps executed in the invention according to any one of Appendices 1 to 10. As a result, an explanatory text suitable for the learning of the first user can be obtained according to the attribute information of the first user (student).

Explanation of Reference Signs

[0110] 1 System, 10 Server, 101 Memory Unit, 104 Control Unit, 106 Input Device, 108 Output Device, 20 First User Terminal, 201 Memory Unit, 204 Control Unit, 206 Input Device, 208 Output Device, 30 Second User Terminal, 301 Memory Unit, 304 Control Unit, 306 Input Device, 308 Output Device, 50 Large Language Model, 501 Memory Unit, 504 Control Unit, 506 Input Device, 508 Output Device

Claims

1. A program for causing a computer including a processor and a memory unit to execute, wherein the processor performs an attribute acquisition step of acquiring attribute information regarding a first user, and a description acquisition step of acquiring a description related to the first user from a large language model based on the attribute information regarding the first user, and executes the program.

2. The attribute acquisition step is a step of acquiring the attribute information including information regarding the proficiency level of the learning content of the learning materials regarding the first user. The program according to Claim 1.

3. The description acquisition step is a step of acquiring the description including information regarding the tasks and recommended problems of the first user. The program according to Claim 1.

4. The description acquisition step is a step of acquiring the description including information regarding the tasks and recommended problems for each learning unit of the first user. The program according to Claim 3.

5. The attribute acquisition step is a step of acquiring the attribute information regarding a plurality of the first users, wherein the processor performs a grouping step of associating the plurality of the first users with one or more groups based on the attribute information acquired in the attribute acquisition step, and executes, and the description acquisition step is a step of acquiring a description regarding the predetermined group from the large language model based on the attribute information regarding one or more of the first users associated with the predetermined group. The program according to Claim 1.

6. The description acquisition step is a step of inputting, into the large language model, input data including the statistical quantity for each element included in the attribute information regarding one or more of the first users associated with the predetermined group and the content of the element, to acquire the description regarding the predetermined group. The program according to Claim 5.

7. The description acquisition step is a step of not inputting the attribute information regarding one or more of the first users associated with the predetermined group into the large language model. The program according to Claim 6.

8. wherein the processor performs a learning material reception step of receiving, from a second user, a selection of one or more learning materials corresponding to the description acquired in the description acquisition step for the predetermined group. A teaching material providing step of collectively providing the one or more learning teaching materials received in the teaching material reception step to the one or more first users associated with the predetermined group; executing, The program according to claim 7.

9. The attribute acquisition step is a step of acquiring the attribute information regarding a plurality of the first users, The processor, A grouping step of associating a plurality of the first users with one or more groups based on the attribute information acquired in the attribute acquisition step; A teaching material providing step of collectively providing learning teaching materials to one or more of the first users associated with a predetermined group; executing, The program according to claim 1.

10. The processor, A teaching material reception step of receiving a selection of one or more learning teaching materials from a second user for the predetermined group; executing, The teaching material providing step is a step of collectively providing the one or more learning teaching materials received in the teaching material reception step to the one or more first users associated with a predetermined group. The program according to claim 9.

11. The grouping step is a step of associating a plurality of the first users with one or more groups according to the degree of similarity of the attribute information of the plurality of the first users. The program according to any one of claims 5 to 10.

12. The grouping step is a step of associating a plurality of the first users with one or more groups after the plurality of the first users have confirmed a learning effect within a specific range. The program according to any one of claims 5 to 10.

13. A method executed by a computer including a processor and a memory, wherein the processor executes all steps executed in the invention according to any one of claims 1 to 10.

14. An information processing apparatus including a control unit and a storage unit, wherein the control unit executes all steps executed in the invention according to any one of claims 1 to 10.

15. A system including means for executing all steps executed in the invention according to any one of claims 1 to 10.

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