Learning support system and learning support method

Abstract

To provide a mechanism for reducing careless mistakes of answers to questions.SOLUTION: A learning support system includes: an answer reception section for receiving an answer to a question; an answer evaluation section for evaluating whether the answer is extrinsically wrong; and an output section for outputting a display which encourages the ascertainment of the answer when the answer is extrinsically wrong.SELECTED DRAWING: Figure 18

Description

[Technical field]

[0001] The present invention relates to a learning support system and a learning support method. [Background technology]

[0002] Background art of this technical field is JP 2021-107898 A (Patent Document 1). This publication states that "the learning support device 30 has an acquisition unit 301 that acquires editing history information in the process of creating a program by a learner and electroencephalogram information indicating the state of the learner's electroencephalogram, an analysis unit 36 ​​that uses the electroencephalogram information and the editing history information to analyze the type of errors in the program being created by the learner, and a question information transmission unit 35 that determines the difficulty level of a question to be posed based on the electroencephalogram information and the type of error, and outputs a question of the determined difficulty level" (see abstract). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-107898 Summary of the Invention [Problem to be solved by the invention]

[0004] According to the technology of Patent Document 1, it is described that when learning programming, problems of a difficulty level according to the learning situation can be provided. Patent Document 1 also describes that "when the time interval between the record to be analyzed and the record immediately before the record to be analyzed is shorter than a predetermined time, and the brain wave concentration level of the brain wave information at the same time as the record to be analyzed is low, the analysis unit 36 ​​identifies the error of the record to be analyzed as a careless mistake." However, Patent Document 1 does not disclose a configuration for prompting confirmation of the answer when the answer to the question is a non-essential wrong answer.

[0005] Therefore, the present invention provides a mechanism for prompting a user to confirm an answer when the answer to a question is a non-essential incorrect answer. [Means for solving the problem]

[0006] In order to solve the above problems, for example, the configurations described in the claims are adopted. The present application includes multiple means for solving the above-mentioned problems, and one example is a learning support system comprising an answer receiving unit that receives an answer to a question, an answer evaluation unit that evaluates whether the answer is a non-essentially incorrect answer, and an output unit that outputs a display prompting confirmation of the answer if the answer is a non-essentially incorrect answer. Effect of the Invention

[0007] According to the present invention, it is possible to provide a mechanism for prompting a user to confirm an answer when the answer to a question is a non-essential incorrect answer. Problems, configurations and effects other than those described above will become apparent from the following description of the embodiments. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is an example of an overall configuration diagram of a learning support system 100. As shown in FIG. [Diagram 2] FIG. 2 shows an example of the hardware configuration of the management server 101. [Diagram 3] FIG. 3 shows an example of the hardware configuration of the user terminal 102. [Figure 4] FIG. 4 shows an example of the hardware configuration of the instructor terminal 103. As shown in FIG. [Diagram 5] FIG. 5 is an example of user information 500. [Figure 6] FIG. 6 is an example of learning unit information 600. [Figure 7] FIG. 7 is an example of instructor information 700. [Figure 8] FIG. 8 is an example of learning history information 800. [Figure 9] FIG. 9 is an example of study content information 900. [Figure 10] FIG. 10 is an example of the incorrect answer pattern information 1000. [Figure 11] FIG. 11 is an example of a learning support flow 1100. [Figure 12] FIG. 12 shows an example of an evaluation content determination flow 1200. [Figure 13] FIG. 13 shows another example of the evaluation content determination flow 1300. [Figure 14] FIG. 14 is an example of an output flow 1400. [Figure 15] FIG. 15 is another example of an output flow 1500. [Figure 16] FIG. 16 is an example of a question output screen 1600. [Figure 17] FIG. 17 is a diagram for explaining a method for evaluating an answer. [Figure 18] FIG. 18 is an example of a reconfirmation prompting screen 1800. [Figure 19] FIG. 19 is another example of the reconfirmation prompting screen 1900. [Figure 20] FIG. 20 is an example of a display screen 2000 for displaying the review correction rate. [Figure 21] FIG. 21 is an example of a display screen 2100 showing the correction rate for each type of incorrect answer. [Figure 22] FIG. 22 is an example of a relationship diagram 2200 of a learning unit. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] A learning support system, a learning support method, and a program according to the present technology will be described below with reference to the drawings. The learning support system according to the present technology provides a mechanism for prompting a user to confirm an answer when the answer is a non-essential wrong answer.

[0010] [Learning Support System] FIG. 1 is a diagram showing an example of the configuration of an entire learning support system 100 according to an embodiment. The learning support system 100 includes one or more management servers 101, one or more user terminals 102, and one or more instructor terminals 103. Each of the one or more user terminals 102 and the one or more instructor terminals 103 is configured to be connectable to one or more management servers 101 via a network. The network may be wired or wireless, and each terminal can transmit and receive information to and from each other via the network. The user terminal 102 may be provided separately from the management server 101, or may be provided integrally with the management server 101.

[0011] The management server 101 and the user terminal 102 in the learning support system 100 (hereinafter, the management server 101 and the user terminal 102 may be simply referred to as "terminals") may be, for example, a portable terminal (mobile terminal) such as a smartphone, tablet, mobile phone, or personal digital assistant (PDA), or may be a wearable terminal such as glasses (including goggles), a wristwatch, or clothing. Each terminal may be a stationary or portable computer, or a server located on the cloud or a network. In terms of functionality, each terminal may be a VR (Virtual Reality) terminal, an AR (Augmented Reality) terminal, or an MR (Mixed Reality) terminal. Alternatively, each terminal may be a combination of a plurality of these terminals. For example, a combination of one smartphone and one wearable terminal may function logically as one terminal. Each terminal may also be an information processing terminal other than these.

[0012] Each terminal of the learning support system 100 may optionally include a processor that executes an operating system, applications, programs, etc., a main storage device such as a RAM (Random Access Memory), an auxiliary storage device such as an IC card, a hard disk drive, an SSD (Solid State Drive), a flash memory, etc., a communication control unit such as a network card, a wireless communication module, a mobile communication module, etc., an input device that detects motion by capturing images of a touch panel, a keyboard, a mouse, a voice input device, a motion controller, a camera unit, etc., and an output device such as a monitor, a display, a printer, a voice output device, an oscillator, etc. The input device may include a sensor such as a GPS, a gyro sensor, an acceleration sensor, etc. The output device may be a device or a terminal that transmits information to be output to an external monitor, a display, a printer, a device, etc.

[0013] The main memory stores various programs and applications (software modules), and the processor executes these programs and applications to realize each functional element of the overall system. Each module may be implemented by one or more programs or applications. Each module may be implemented by an independent program or application, or may be implemented as a subprogram or function within an integrated program or application. Each module may be implemented as hardware by integrating circuits or employing a microcomputer (hardware module).

[0014] Furthermore, each module may be realized by a single processor or by multiple processors. Also, each module may be provided in a single terminal (including a management server) or may be provided separately in two or more terminals (including a management server) connected to each other via a network. Also, each module may be provided in each or any one or more of two or more terminals (including a management server) connected to each other via a network. Cases in which some modules are realized in a different country from the other modules are also considered.

[0015] In this specification, each module is described as an entity (subject) that performs processing, but in reality, processing is performed by a processor executing various programs, applications, and the like.

[0016] The auxiliary storage device stores various databases (DB). A "database" is a set of data that is organized and collected so as to be compatible with any data operation (e.g., extraction, addition, deletion, overwriting, etc.) from the processor or an external computer. The auxiliary storage device is a functional element (storage unit) that stores one or more sets of data. There are no limitations on the method of implementing the database, and it may be, for example, a database management system, spreadsheet software, or text files such as XML and JSON. Some or all of this information may be stored in a relational database or a non-relational database. The database may be provided independently in a state that is connectable to the processor, etc.

[0017] The learning contents for which the learning support system 100 provides learning support are not particularly limited, and may be, for example, learning contents such as Japanese language (including classics, modern Japanese, etc.), arithmetic (including mathematics, etc.), science (including chemistry, physics, biology, etc.), social studies (including world history, Japanese history, geography, civics, etc.), foreign language (including English, German, etc.), music, calligraphy, etc., which are learned at various schools, etc. In addition, the learning contents for which the learning support system 100 provides learning support may be learning of specialized academic subjects such as information engineering, fashion business, physical / occupational therapy, learning of exercises such as gymnastics and e-sports, learning of academic hobbies, learning for various qualification examinations, and various other types of learning. In the following, the present technology will be described taking as an example a case in which the main learning support target of the learning support system 100 is learning English at a cram school.

[0018] [Management Server] FIG. 2 illustrates an example of the hardware configuration of the management server 101. The management server 101 is an element that manages this learning support system 100. The management server 101 is typically a terminal used by an administrator who manages and operates this learning support system 100. The management server 101 is configured, for example, by a computer server or the like that is placed on a cloud.

[0019] The management server 101 includes a main storage device 201 and an auxiliary storage device 202. The management server 101 also includes a processor 203, an input device 204, an output device 205, and a communication control unit 206 as described above. The main memory device 201 stores programs and applications such as a user terminal management module 211, a content output module 212, an answer reception module 213, an answer evaluation module 214, an output module 215, an analysis display module 216, and a teacher terminal management module 217. Each functional element of the management server 101 is realized by the processor 203 executing these programs and applications stored in the main memory device 201.

[0020] The auxiliary storage device 202 stores information necessary for the operation of the learning support system 100. The auxiliary storage device 202 stores, for example, user information 500, learning unit information 600, instructor information 700, learning history information 800, learning content information 900, and incorrect answer pattern information 1000. Details of this information will be described later. Note that the implementation method of each piece of information stored in the auxiliary storage device 202 is not limited to the present embodiment, and each piece of information may be realized in a form in which it is distributed across multiple database servers or cloud applications.

[0021] Each functional element of the management server 101 will now be briefly described. The user terminal management module 211 manages the operation of the user terminal 102. The user terminal management module 211 cooperates with a user learning management module 311 of the user terminal 102 to control basic operations for supporting learning executed in the user terminal 102 using the learning support system 100.

[0022] For example, the user terminal management module 211 cooperates with the user learning management module 311 to output (display) a login screen, a user information management screen, and the like used for learning management executed by the management server 101 on an output device 305 such as a display of the user terminal 102. The user terminal management module 211 also cooperates with the user learning management module 311 of the user terminal 102 to acquire input information input from the user terminal 102 via these display screens. The user terminal management module 211 operates based on the acquired information (various information, instructions, and the like) and outputs (records) the acquired information to the auxiliary storage device 202 as user information 500, and the like.

[0023] The content output module 212 outputs learning content to the user terminal 102. The content output module 212, for example, manages the output of learning content, connects to learning unit information 600, learning history information 800, learning content information 900, etc. according to the user's learning content, and outputs learning content to the user terminal 102. The content output module 212 cooperates with the user learning execution module 312 of the user terminal 102, and outputs learning content to an output device 305 such as a display of the user terminal 102, for example, based on an input (e.g., an instruction) from the user terminal 102.

[0024] Answer receiving module 213 acquires the answers entered for the output study content from user terminal 102. Answer receiving module 213 outputs (records) the acquired answers to, for example, auxiliary storage device 202.

[0025] The answer evaluation module 214 evaluates whether the received answer is a non-essential wrong answer. The answer evaluation module 214 also evaluates whether the user's answer is correct. The answer evaluation module 214 also evaluates, for example, whether the answer corresponds to the non-essential error classification in the wrong answer pattern information. For example, the answer evaluation module 214 evaluates the answer as a non-essential wrong answer when the answer corresponds to the non-essential error classification, and evaluates the answer as an essential wrong answer when the answer does not correspond to the non-essential error classification. The answer reception module 213, for example, outputs (records) the evaluation result of the answer to the auxiliary storage device 202. The method of evaluating the answer will be described later.

[0026] The output module 215 displays information according to the evaluation result of the answer. For example, when the evaluation result of the answer is correct, the output module 215 outputs to the user terminal 102 a display indicating that the answer is correct. For example, when the evaluation result of the answer is a non-essentially incorrect answer, the output module 215 outputs to the user terminal 102 a display prompting the user to confirm the answer. For example, when the evaluation result of the answer is a non-essentially incorrect answer, the output module 215 outputs to the user terminal 102 a display indicating that the answer is a non-essentially incorrect answer.

[0027] The analysis display module 216 analyzes the user's answer from various viewpoints. For example, the analysis display module 216 analyzes the user's answer based on the evaluation result of the answer by the answer evaluation module 214. The analysis display module 216 outputs the analysis result. The output destination may be any of the management server 101, the user terminal 102, and the instructor terminal 103. The analysis of the answer by the analysis display module 216 will be described in detail later.

[0028] The instructor terminal management module 217 manages the operation of the instructor terminal 103. The instructor terminal management module 217 cooperates with the instructor learning management module 411 of the instructor terminal 103 to control basic operations for managing the learning performed by the user using the learning support system 100 in the instructor terminal 103. For example, the instructor terminal management module 217 cooperates with the instructor learning management module 411 to output (display) the login page, instructor information management page, various user learning management pages, etc. of the learning support system 100 to the instructor terminal 103. The instructor terminal management module 217 also cooperates with the instructor learning management module 411 of the instructor terminal 103 to acquire input information input from the instructor terminal 103. The instructor terminal management module 217 operates based on the acquired information (various information, instructions, etc.) and outputs (records) the acquired information to the auxiliary storage device 202 as instructor information 700, etc.

[0029] [User device] FIG. 3 shows an example of the hardware configuration of the user terminal 102. The user terminal 102 is a terminal used by a user (a learner, for example, a student, etc.) who uses the learning support system 100. The user terminal 102 is configured, for example, by a terminal such as a mobile information terminal, a notebook PC, or a desktop PC, etc.

[0030] The user terminal 102 includes a main memory device 301 and an auxiliary memory device 302. The user terminal 102 also includes a processor 303, an input device 304, an output device 305, a camera 306, and a communication control unit 307 as described above. The main memory device 301 stores programs and applications such as a user learning management module 311 and a user learning execution module 312, and each functional element of the user terminal 102 is realized by the processor 303 executing these programs and applications.

[0031] The user learning management module 311 controls the basic operations of the user terminal 102. The user learning management module 311 cooperates with, for example, the user terminal management module 211 of the management server 101 to control the basic operations for managing learning performed using the learning support system 100.

[0032] The user learning execution module 312 controls the output of learning content for executing learning by the learning support system 100 in the user terminal 102. The user learning execution module 312 cooperates with the user terminal management module 211 of the management server 101, for example, to output (display) various learning contents on the user terminal 102 and transmit user input to the management server 101.

[0033] The auxiliary storage device 302 stores information necessary for the operation of the user terminal 102. For example, the auxiliary storage device 302 stores user information 500, learning unit information 600, learning history information 800, learning content information 900, etc. This information may be some or all of the information related to the user's learning among the user information 500, learning unit information 600, learning history information 800, learning content information 900, etc. stored in the management server 101.

[0034] [Teacher's terminal] FIG. 4 shows an example of the hardware configuration of the instructor terminal 103. As shown in FIG. The instructor terminal 103 is an example of a terminal used by a person other than the user (the learner), and in this embodiment, it is illustrated as a "instructor terminal" used by an instructor. The terminal used by a person other than the user may be, for example, a terminal operated by an instructor, a classroom manager, a guardian, etc. In addition, in this learning support system 100, the instructor terminal 103 is an additional element and does not necessarily have to be provided. Furthermore, the instructor terminal 103 may be provided separately from the management server 101, or may be provided integrally with the management server 101.

[0035] The instructor terminal 103 is configured as a terminal such as a smartphone, a tablet, a notebook PC, or a desktop PC. The main memory device 401 stores programs and applications such as an instructor learning management module 411, and the processor 403 executes these programs and applications to realize each functional element of the instructor terminal 103.

[0036] The instructor learning management module 411 controls basic operations of the instructor terminal 103. For example, in cooperation with the instructor terminal management module 217 of the management server 101, the instructor learning management module 411 controls basic operations for managing learning performed by a user using the learning support system 100. For example, in cooperation with the instructor terminal management module 217, the instructor learning management module 411 outputs various user learning management pages and the like to the instructor terminal 103 and transmits input from the instructor to the management server 101.

[0037] The auxiliary storage device 402 stores information necessary for the operation of the instructor terminal 103. The auxiliary storage device 402 stores, for example, user information 500, learning unit information 600, instructor information 700, learning history information 800, learning content information 900, and incorrect answer pattern information 1000. This information may be a part or all of the information related to the instructor's learning support among the user information 500, learning unit information 600, instructor information 700, learning history information 800, learning content information 900, and incorrect answer pattern information 1000 stored in the management server 101.

[0038] 5 to 9 show various types of information stored in the management server 101. Although not limited to this, it is assumed that some or all of this information is stored in a JSON format file. Some or all of this information may be configured to be stored in a relational database or a non-relational database.

[0039] FIG. 5 is an example of user information 500. User information 500 is information about a user (e.g., a student) who studies using the learning support system 100. User information 500 includes, for example, a user ID, a user display ID, a name, a school, a grade, a school of choice, an address, a course ID, a course taken, and other information, and values ​​such as those shown as sample values ​​520 are input for each field name (item name) 510. The contents indicated by sample values ​​520 are written in a summary 530 column.

[0040] The user ID is a symbol given to each user to identify the user, and information about each user is basically linked by this user ID. The user ID is a primary key referenced from other information. The user display ID is a display ID for the user displayed on the screen of the management server 101, the user terminal 102, etc., and can be set arbitrarily. The user display ID can be set arbitrarily by the user using a predetermined symbol within a range of predetermined conditions (for example, 10 characters or less). The name is the user's name information. The school and grade are information indicating the name of the school (educational institution) to which the user currently belongs and the grade to which the user belongs. For example, "JH2" indicates the second year of junior high school. The school of choice is the name of the school to which the user wishes to advance, for example, the name of a junior high school, high school, university, etc. for which the user plans to take an entrance exam. The school of choice may include information such as faculty and department.

[0041] The address is information indicating the address or residence of the user, or the address or residence of the user's guardian. The course ID indicates an identification ID of a course the user is taking among the learning courses provided by the learning support system 100. The course ID stores the course ID of the learning unit information 600, and is linked to the contents of the learning unit information 600 by this course ID. The course to be taken indicates a course the user is taking among the learning courses provided by the learning support system 100. The user information 500 may also include information on the user's guardian, various procedural information, user registration information, etc.

[0042] This information may be acquired in units of a learning unit, learning content (e.g., explanation content, question content, video content), questions, etc. A "learning unit" is a unit of learning set for each group of coherent learning elements. In this embodiment, a "learning unit" may or may not match a unit specified in a textbook or the like (i.e., a unit following the curriculum guidelines). A learning subject includes learning in multiple fields, and each field includes multiple learning units. In this learning support system, for example, one or more sets of learning contents are prepared for the study of each learning unit. A set of learning contents may include one or more explanation contents, question contents, video contents, etc.

[0043] FIG. 6 is an example of learning unit information 600. The learning unit information 600 is information on a learning course provided by the learning support system 100, and the learning course is prepared for each subject, grade, and textbook used, for example. The learning course may be further divided based on, for example, the learning progress, or may be prepared from other viewpoints. The learning unit information 600 includes information such as the course name, course ID, field, field ID, unit, unit ID, data URL, backward unit ID, difficulty level, and estimated learning time, and values ​​such as those shown as sample values ​​620 are input for each field name 610.

[0044] The course name and course ID are a name and an ID for identifying a course to be studied. In this embodiment, the course name may be the same as the name of a course to be studied, for example. The field and field ID are the name and ID of a category when each course (which may be a subject) is classified according to its content. The unit and unit ID are the name and ID of a category when each field is further classified according to its content. The data URL is information indicating the storage location of the data of the learning content used in the study of each unit. The data URL is, for example, the URL of a storage folder that stores various data that make up the learning content for each unit.

[0045] The backward unit ID is an ID for identifying data indicating the relationship between a certain learning unit and its backward unit, which is provided for each learning unit. A backward unit is a learning unit in which prerequisite knowledge for understanding a certain learning unit is provided. FIG. 22 is an example of a unit relation diagram showing the connection between a certain learning unit and its backward unit. Here, the unit relation diagram of "unit 1" is shown. In the unit relation diagram, the arrows connecting the learning units are oriented so that the learning unit to be understood is the end point and the backward unit for the learning unit to be understood is the starting point. Therefore, if a certain learning unit cannot be understood, the understanding of the learning unit can be improved by going back to the learning unit (backward unit) that is the starting point of the arrow according to the unit relation diagram. Although there are three backward units for unit 1 in FIG. 22, there may be one, two, or more backward units for one learning unit. In addition, a learning unit may be a learning unit that is a different learning unit from the learning unit. In addition, a learning unit may be a learning unit that is a different learning unit. The learning units may be learning units in different learning fields (e.g., different subjects, learning fields in different grades, etc.).

[0046] The difficulty level is information indicating the difficulty level of mastering each unit, and can be determined, for example, based on the percentage of correct answers in past and / or current tests for that unit. The standard learning time is information that is an estimate of the time required to master the learning content of each unit, and can be determined, for example, based on the time required by any past and / or current student to master the learning content of that unit. As an example, the learning time can be calculated based on a standard learning time (for example, average learning time) calculated based on big data based on past learning history. Whether or not the learning content has been mastered can be determined, for example, by obtaining a passing score once or multiple times in a confirmation test for that unit.

[0047] FIG. 7 is an example of instructor information 700. The instructor information 700 is information about an instructor who supports learning using the learning support system 100. The instructor information 700 includes, for example, an instructor ID, an instructor display ID, an affiliation ID, a course ID in charge, and a user ID in charge, and values ​​such as those shown as sample values ​​720 are input for each field name 710. The contents indicated by the sample values ​​720 are written in the summary 730 column.

[0048] The instructor ID is an ID given to each instructor to identify the instructor. The instructor display ID is an instructor display ID displayed on the screen of the management server 101, the instructor terminal 103, etc. The affiliation ID indicates, for example, information on the group or school to which the instructor belongs. The course ID indicates the course that the instructor is in charge of among the learning courses provided by the learning support system 100. The user ID is set, for example, for each course that the administrator is in charge of, and indicates the ID of the user (student) that the instructor is in charge of in that course. The instructor information 700 is linked to the learning history information 800, for example, via the user ID and the course ID.

[0049] FIG. 8 is an example of learning history information 800. The learning history information 800 is information on the progress of learning using the learning support system 100, and is provided for each user and unit, for example. The learning history information 800 includes information such as a user ID, unit ID, start date and time, end date and time, completion date and time, number of times the unit has been studied, question ID, correct answer ID, correct answer rate, score, score rate, retention rate (which may be the degree of learning), and the like, and values ​​such as those exemplified by sample value 820 are input for each field name 810. The contents indicated by sample value 820 are described in the summary 830 column.

[0050] The start date and time, end date and time, completion date and time, and number of times of unit study indicate information on the start date and time of study using the learning content of the unit, the end date and time, the completion date and time of study, and the number of times the study was completed, respectively. Note that completion means, for example, that the study using the learning content has been completed, and completion means, for example, that the study using the learning content has been completed (finished) by satisfying a predetermined completion criterion. Therefore, in order to "complete" the study using one learning content, the study using the learning content may be completed (conducted) multiple times. The completion criterion may be determined, for example, based on the correct answer rate, score rate, retention rate, etc. described later (for example, correct answer rate of 80% or more, score rate of 90% or more, retention rate of 95% or more, etc.). The number of times of unit study completion indicates the number of times the study of the unit has been completed for a unit that can be studied multiple times, and may be information such as 0 times (not completed), 1 time, 2 times or more, etc.

[0051] The score rate is the percentage of the user's score out of the total score allocated for the content. The retention rate is an index showing the degree of mastery of the learning content of the unit, and can be determined, for example, based on the correct answer rate, score rate, number of times of implementation, etc., when learning is performed using the learning content of the unit. The retention rate can be determined, for example, so that 0% is set for no learning, and the higher the correct answer rate, score rate, and number of times of implementation, the higher the retention rate (approaching 100%).

[0052] The question ID and correct answer ID are respectively an identification ID of a question asked in the learning content of the unit and an identification ID of the correct answer. Based on the question ID and correct answer ID, information regarding, for example, the number of correct answers and the correct answer rate (e.g., the ratio of the number of correct answers to the total number of questions) can be calculated from the user's answers to the questions asked in the unit. Information regarding the allocation of points is linked to the question ID. Therefore, the score and the score rate (e.g., the ratio of the total score to the total allocated points) can be calculated based on the question ID and correct answer ID.

[0053] The learning history information 800 may include various other information for each learning content, for example. The learning history information 800 may include information on the time required for answering, the content of incorrect answers, the rate of incorrect answers, and the like. The learning history information 800 may include, as reference information, learning results related to the unit, which are obtained without using the learning support system 100 (for example, mock test score information, etc.), and learning target values ​​related to the unit that the student should aim for. The learning history information 800 is linked to the user information 500, for example, via a user ID. The learning history information 800 is also linked to the learning unit information 600, for example, via a course ID.

[0054] FIG. 9 is an example of study content information 900. Learning content information 900 is information related to the exam that the user will take. Learning content information 900 includes information such as exam name, exam ID, exam date, field, field ID, score allocation, and question frequency, and values ​​such as those shown in sample value 920 are entered for each field name 910. The content indicated by sample value 920 is written in summary 930.

[0055] The test name and test ID are a name and an ID given to identify the test. The test may be, for example, an official test such as a common test conducted by a public institution, a mock test that imitates the official test, or an entrance test for a school. The test may also be, for example, a midterm test, a final test, or an end-of-year test conducted at a school. The test date is information indicating the date and time when the test is conducted. The field and field ID are the field and ID of the learning content that the test targets. The score allocation indicates the score allocation for each field of each question in the test. For example, for official tests, entrance tests, tests conducted at each school, etc., the score allocation may be an expected score allocation set based on the actual score allocation in the past test questions. For mock tests, the score allocation may be an expected score allocation that predicts the score allocation of the test being imitated.

[0056] The question frequency is information determined based on past questions of the target exam, and may be information expressed by a numerical value (e.g., -1 to +1 or 0 to 5) that increases as the question frequency increases. The question frequency may be input as 100% for learning content that is always asked in the target exam, or 40% for learning content that has a 40% probability of being asked. In this case, the average question frequency (e.g., 60%) of each learning content may also be recorded. The expected score allocation and question frequency can be determined in advance by analyzing statistical data of similar past exams, machine learning, or the like. The learning content information 900 is linked to the learning unit information 600, for example, through a field ID or the like.

[0057] FIG. 10 is an example of the incorrect answer pattern information 1000. The incorrect answer pattern information 1000 is information showing the relationship between the contents of incorrect answers and their classification. FIG. 10 is an example of the incorrect answer pattern information 1000 showing the contents of incorrect answers in an English fill-in-the-blank question and their classification. The incorrect answer pattern information 1000 includes, for example, an incorrect answer ID 1010, an incorrect answer content 1020, a careless mistake group (G) 1030, an essential mistake G1040, a spelling mistake G1050, and a grammatical mistake G1060. In this example, a "careless mistake" represents a non-essential error. The incorrect answer ID 1010 is an ID for identifying the contents of an incorrect answer. In this example, Error001 to Error000x are exemplified. The incorrect answer content 1020 indicates the contents of an incorrect answer corresponding to each incorrect answer ID 1010. In the column of the incorrect answer content 1020, contents considered to be careless mistakes and contents considered to be other incorrect answers are written for each subject and type of question. In this example, various possible incorrect answers to English fill-in-the-blank questions are listed.

[0058] Careless mistake G1030, essential mistake G1040, spelling mistake G1050, and grammar mistake G1060 are category names for classifying the contents of incorrect answers according to their characteristics. For each incorrect answer ID 1010, a mark "X" is attached to the category of incorrect answers to which the incorrect answer corresponding to the ID belongs. Each incorrect answer ID 1010 is classified to belong to either careless mistake G or essential mistake G. In the case of this example, for example, an incorrect answer corresponding to Error001 is classified as careless mistake G, an incorrect answer corresponding to Error002 is classified as careless mistake G and spelling mistake G, and an incorrect answer corresponding to Error007 is classified as essential mistake G. In addition, in the case of this example, the incorrect answer IDs classified as careless mistake G are arranged so that their ID numbers are smaller than those of the incorrect answer IDs classified as essential mistake G. The contents of the incorrect answers, the category names, the number of categories, and the correspondence between them may vary depending on the learning contents, the format of the questions, and the like.

[0059] [Learning support methods] The learning support method according to the present technology will be described based on an operation example of the learning support system 100. FIG. 11 is an example of a learning support flow 1100. The learning support method according to the present technology typically includes outputting a question (step 1110), accepting an answer (step 1120), evaluating whether the answer is a non-essential wrong answer (step 1130), and outputting a display prompting confirmation of the answer if the answer is a non-essential wrong answer (step 1140). Each step of the learning support method will be described below along with the learning support flow 1100. In the following description, a step in the flow chart will be indicated as, for example, "S1110".

[0060] First, the user terminal management module 211 cooperates with the user learning management module 311 of the user terminal 102 and receives, for example, information specifying the learning unit and learning content that the user is to study. The content output module 212 cooperates with the user learning execution module 312 of the user terminal 102, and outputs (displays) the designated learning content on a display or the like of the user terminal 102 based on the received information (S1110).

[0061] The content output module 212 outputs, for example, a question output screen 1600 shown in Fig. 16 to the user terminal 102. The content output module 212 outputs a question column 1610 at the top of the question output screen 1600 and an answer input column 1620 at the bottom. In this example, the Japanese sentence "This song is very difficult to sing" is displayed in the question column 1610 as an English translation question. The content output module 212 also outputs a hint display button 1630 marked "I don't know" and an answer button 1640 (send button) marked "Answer" below the answer input column 1620.

[0062] In the user terminal 102, the user learning execution module 312 accepts, for example, an answer entered by the user in the answer input field 1620 of the question output screen 1600. Then, upon accepting selection of the answer button 1640 by the user, the user learning execution module 312 transmits the answer by the user to the management server 101.

[0063] The answer receiving module 213 receives the user's answer sent from the user terminal 102 (S1120). In this example, for example, an answer such as "this song is too dificult to sing" is acquired as the user's answer to the above question (see FIG. 17(I) described later). The answer receiving module 213 stores the received user's answer in, for example, the auxiliary storage device 202.

[0064] Here, when the user learning execution module 312 accepts the user's selection of the hint display button 1630 and sends information indicating a request for a hint to the management server 101, the answer receiving module 213 displays (sends) to the user terminal 102 a pre-prepared hint for the question.

[0065] <Evaluation Example 1> The answer evaluation module 214 evaluates whether the received answer is a non-essential incorrect answer (S1130). Fig. 12 shows an example of an evaluation content determination flow 1200 for evaluating whether an answer is a non-essential wrong answer. Fig. 17 is a diagram for explaining a method for determining the evaluation content.

[0066] The answer evaluation module 214 obtains the correct answer to the question (S1210). The answer evaluation module 214 also obtains the incorrect answer pattern information 1000 (S1220). The answer evaluation module 214 can obtain the correct answer and incorrect answer pattern information corresponding to the question of the output learning content based on the learning content information 900. Here, as the correct answer, for example, as shown in FIG. 17(II), the English sentence "This song is too difficult to sing." is obtained. Note that S1210 and S1220 are in no particular order, and either may be performed first, or they may be performed simultaneously. Also, S1220 may be obtained at any timing before S1250, which will be described later, is performed.

[0067] The answer evaluation module 214 compares the answer with the correct answer (S1230). In this example, as shown in FIG. 17(III), the word "this" in the answer has the same alphabetic initial letter "t" as the "T" in the correct answer, but is lowercase instead of uppercase (difference 1). Also, the word "dificult" in the answer differs from the correct answer in that it is missing one "f" (difference 2).

[0068] The answer evaluation module 214 judges whether the answer is the same as the correct answer (S1240). If the answer is the same as the correct answer (Yes in S1240), the answer evaluation module 214 evaluates the answer as correct (S1260). On the other hand, if the answer is not the same as the correct answer (No in S1240), the answer evaluation module 214 judges whether the answer falls under a non-essential incorrect answer pattern (S1250).

[0069] In this example, the answer and the correct answer differ in the above two points (differences 1 and 2). Therefore, the answer evaluation module 214 determines whether the answer corresponds to a non-essential incorrect answer pattern (i.e., careless mistake G).

[0070] Specifically, the answer evaluation module 214 judges, for example, in the order of the wrong answer ID, which of the wrong answer contents 1020 in the acquired wrong answer pattern information 1000 the difference 1 regarding the answer corresponds to. The answer evaluation module 214 judges that the difference 1 corresponds to the wrong answer content of Error001. In this case, the answer evaluation module 214 attaches a tag corresponding to careless mistake G1030 to the answer, for example, based on the wrong answer pattern information 1000. By attaching a tag corresponding to careless mistake G to the answer, the answer evaluation module 214 judges that the answer corresponds to a non-essential wrong answer pattern (Yes in S1250). As a result, the answer evaluation module 214 evaluates that the answer tagged with the tag corresponding to careless mistake G contains a non-essential error (S1270).

[0071] On the other hand, the answer evaluation module 214 judges that the difference does not correspond to the erroneous answer contents of Errors 001 to 006 belonging to careless mistake G and Errors 007 to 008 belonging to essential mistake G, but corresponds to Error 009. In this case, the answer evaluation module 214 attaches a tag corresponding to essential mistake G 1040 to the answer, for example. By attaching a tag corresponding to essential mistake G to the answer, the answer evaluation module 214 judges that the answer does not correspond to a non-essential error pattern (No in S1250). As a result, the answer evaluation module 214 evaluates that the answer tagged with the essential mistake G is an essential error (S1280).

[0072] The answer evaluation module 214 may be configured to determine whether the difference corresponds to the content of the wrong answer indicated by each wrong answer ID by, for example, comparing it with a wrong answer pattern of each wrong answer ID prepared in advance. The wrong answer pattern of Error001 may be, for example, combination information of uppercase and lowercase alphabetical characters such as "A"-"a" and "B"-"b" (for example, 26 combinations) regarding the first character of a word. If the difference between the correct answer and the answer corresponds to any of the wrong answer patterns of Error001 (that is, if the first character of a word differs between the correct answer and the answer in whether it is an uppercase or lowercase alphabetical character), the answer evaluation module 214 determines that the answer corresponds to the content of the wrong answer of Error002. In addition, the wrong answer pattern of Error002 is, for example, linked to the word "difficult" that is prone to spelling mistakes, with wrong answer patterns "dificult", "defficult", "difficalt", etc. If an answer different from the correct answer falls into any of the error patterns of Error002, the answer evaluation module 214 determines that the answer falls into the error content of Error002.

[0073] Alternatively, the answer evaluation module 214 may be configured to determine whether the difference corresponds to the wrong answer content indicated by each wrong answer ID by using a learning device. The learning device may be, for example, a learning device that is trained to estimate whether the answer includes the wrong answer content indicated by each wrong answer ID by inputting the correct answer and the answer. The learning device may be prepared for each wrong answer ID, such as a capital / lower case error detector, a spelling error detector, a verb transformation error detector, etc. Also, the learning device may be, for example, a learning device that is trained to estimate whether the answer includes the wrong answer content indicated by which wrong answer ID by inputting the correct answer and the answer. These learning devices may be rule-based learning devices or machine learning learning devices.

[0074] In this manner, the answer evaluation module 214 determines, for example, one of the following three evaluation results for all answers (S1290). Rating (A) The answer is correct. Rating (B): The answer is fundamentally wrong. Rating (C) The answer contains a non-essential error.

[0075] <Evaluation example 2> The method of evaluating the answer by the answer evaluation module 214 is not limited to the above example. For example, if the answer is not correct (No in S1240), the answer evaluation module 214 judges which of the error contents 1020 in the acquired error pattern information 1000 corresponds to all the differences related to the answer, for example, in the order of the error ID. The answer evaluation module 214 judges that the difference 1 corresponds to the error content of Error001. In this case, the answer evaluation module 214 attaches a tag corresponding to the careless mistake G1030 to the answer, for example. Next, the answer evaluation module 214 next judges that the difference 2 does not correspond to the error content of Error001, but corresponds to the error content of Error002. In this case, the answer evaluation module 214 attaches a tag corresponding to the careless mistake G1030 and a tag corresponding to the spelling mistake G1050 to the answer, for example.

[0076] The answer evaluation module 214 associates all differences between the answer and the correct answers with one of the incorrect answer IDs, thereby attaching one or more tags corresponding to the incorrect answer group. The answer evaluation module 214 judges the answer to be in a non-essential incorrect answer pattern by attaching at least one tag corresponding to the careless mistake G to the answer (Yes in S1250). As a result, the answer evaluation module 214 evaluates that the answer tagged with the careless mistake G contains a non-essential error (S1270).

[0077] The answer evaluation module 214 judges the answer not to be a non-essential incorrect answer pattern by not attaching any tag corresponding to careless mistake G to the answer and attaching only the tag corresponding to essential mistake G (No in S1250). As a result, the answer evaluation module 214 evaluates the answer with only the tag corresponding to essential mistake G as an essential error (S1280). In this manner, the answer evaluation module 214 determines, for example, one of the following evaluation results (A) to (C) for all answers (S1290). Rating (A) The answer is correct. Rating (B): The answer is fundamentally wrong. Rating (C) The answer contains a non-essential error.

[0078] FIG. 14 is an example of an output flow 1400. The output module 215 acquires the evaluation result by the answer evaluation module 214 (S1410). Then, the output module 215 executes an output process according to the evaluation result (S1420).

[0079] Specifically, when the answer is evaluated as (A), the output module 215 outputs (displays) a correct answer screen indicating that the answer is correct, for example, to the user terminal 102 (S1430). That is, the answer evaluation module 214 acquires the correct answer to the question, and when the answer is the same as the correct answer, it evaluates that the answer is not an unsubstantial incorrect answer but a correct answer, and the output module 215 outputs a display indicating that the answer is correct.

[0080] Also, if the answer is evaluated as (B), the output module 215 outputs (displays) an incorrect answer screen indicating that the answer is an incorrect answer, for example, to the user terminal 102 (S1450). That is, if the answer is not the same as the correct answer and acquires incorrect answer pattern information indicating the classification of the error, and if the answer does not correspond to the classification of non-essential errors in the incorrect answer pattern information, the answer is evaluated as an essential incorrect answer, and the output module 215 outputs a display indicating that the answer is an essential incorrect answer.

[0081] If the answer is not the same as the correct answer, the answer evaluation module 214 obtains error pattern information indicating the classification of the error, and if the answer does not correspond to the classification of non-essential errors in the error pattern information, it evaluates the answer as an essential error, and the output module 215 does not output a display prompting confirmation of the answer.

[0082] If the answer is graded (C), the output module 215 outputs (displays), for example, a reconfirmation prompting screen to prompt the user to confirm the answer on the user terminal 102 (S1440). That is, if the answer is not the same as the correct answer and the answer evaluation module 214 acquires wrong answer pattern information indicating the classification of the error, and if the answer corresponds to the classification of a non-essential error in the wrong answer pattern information, the answer is evaluated as a non-essential wrong answer, and the output module 215 outputs a display prompting the user to confirm the answer. For example, the output module 215 outputs information regarding the classification of a non-essential error as a display prompting the user to confirm the answer.

[0083] FIG. 18 is an example of a reconfirmation prompting screen 1800. For example, the output module 215 displays a reconfirmation prompting screen on the user terminal 102, superimposed on the question output screen 1600 in a state where the user has input the answer, to prompt the user to confirm the answer. The output module 215 displays the contents (types) of common careless mistakes, examples of careless mistakes, and examples of correct answers on the reconfirmation prompting screen 1800, together with a reconfirmation prompting message saying "Please review whether your answer is correct." The output module 215 displays a send button 1810 displaying "Answer as is" and a back button 1820 displaying "Review" at the bottom right of the reconfirmation prompting screen 1800.

[0084] (If you don't want to recheck your answers) In the user terminal 102, when the user learning execution module 312 accepts, for example, the selection of the send button 1810 by the user, it transmits information indicating that the answer will not be rechecked to the management server 101. By acquiring the information indicating that the answer will not be rechecked, the answer receiving module 213 accepts the previously received answer as the final answer. Then, the answer evaluation module 214 evaluates the answer as incorrect based on the fact that the answer is different from the correct answer. As a result, the output module 215 displays, for example, an incorrect answer screen on the user terminal 102 indicating that the answer is incorrect.

[0085] (If you want to double check your answers) In the user terminal 102, when the user learning execution module 312 accepts, for example, the selection of the back button 1820 by the user, it transmits information indicating to return to the question output screen 1600 to reconfirm the answer to the management server 101. Then, the output module 215 outputs, for example, information to the user terminal 102 instructing not to display the reconfirmation prompting screen 1800. Then, the question output screen 1600 in the state in which the user has input the answer is displayed on the user terminal 102. This allows the user to continue inputting the answer. For example, if the user finds that his / her answer contains a careless mistake such as that displayed on the reconfirmation prompting screen 1800, he / she can re-input the correct answer.

[0086] Then, when the user learning execution module 312 accepts the selection of the answer button 1640 by the user, it transmits the user's answer to the management server 101. The answer receiving module 213 accepts the user's answer sent from the user terminal 102 (S1120). The answer receiving module 213 stores the accepted answer in, for example, the auxiliary storage device 202. This returns to S1130, and the answer evaluation module 214 can again evaluate whether the accepted answer is a non-essential incorrect answer.

[0087] For an answer received after the reconfirmation prompt screen 1800 is displayed, the answer receiving module 213 may evaluate whether or not the answer is correct without returning to S1130.

[0088] According to the above configuration, the user's understanding of the question can be more appropriately evaluated. For example, the user's answer may correctly answer the question, but may include non-essential errors such as careless mistakes. In such a case, even if the user's understanding of the question is sufficient, if the user's answer is evaluated as an incorrect answer due to a small mistake different from the question, it may lead to an incorrect evaluation of the user's understanding of the question. According to the present technology, it is possible to avoid evaluating an answer including a non-essential error by the user as an incorrect answer, and, for example, it is possible to more appropriately evaluate the user's understanding of the question.

[0089] FIG. 19 is another example of the reconfirmation prompting screen 1900. The reconfirmation guidance screen is not limited to the example shown in Fig. 18. The output module 215 may display, for example, a reconfirmation guidance screen 1900. The output module 215 displays the contents (types) of common careless mistakes and a check box 1930 side by side along with a reconfirmation guidance message "Please review your answer to see if it is correct!" on the reconfirmation guidance screen 1900. The output module 215 displays a send button 1910 displaying "Answer as is" and a back button 1920 displaying "Review" at the bottom right of the reconfirmation guidance screen 1900. The send button 1910 and the back button 1920 operate in the same way as in Fig. 18, and therefore a detailed description thereof will be omitted.

[0090] By displaying the check boxes 1930, the output module 215 can make the user aware that it is desirable to recheck each of the contents (types) of common careless mistakes displayed on the reconfirmation guidance screen 1900 before answering. Although not limited to this, the output module 215 may display the check boxes 1930 so that the user can enter a check. In this case, the output module 215 may activate the send button 1910 (make it possible to accept selection of the send button 1910) when it has accepted the entry of checks for all the check boxes 1930 corresponding to the displayed common careless mistakes.

[0091] (Analysis based on evaluation results) The analysis display module 216 analyzes the evaluation results related to the answer. The analysis display module 216 outputs the obtained analysis results to, for example, at least one of the user terminal 102 and the instructor terminal 103. The analysis display module 216 is configured to be able to output (display) the obtained analysis results to at least one of the user terminal 102 and the instructor terminal 103, for example, in the form of a graph (for example, a pie chart, a histogram, a line graph, etc.). The analysis display module 216 may be configured to be able to display the obtained analysis results, for example, as numerical values. Examples of the analysis results generated by the analysis display module 216 include the following.

[0092] The analysis display module 216 calculates, for example, a careless mistake rate. The careless mistake rate is, for example, the ratio of non-essential incorrect answers (i.e., careless mistakes) to the total number of answers that are not correct. The analysis display module 216 calculates the careless mistake rate for each user's answers, making it possible to grasp, for example, the frequency of careless mistakes made by each user. Furthermore, the analysis display module 216 calculates the careless mistake rates for multiple users for each question, making it possible to grasp questions that are prone to careless mistakes.

[0093] The analysis display module 216 calculates a review correction rate. The review correction rate is, for example, the rate at which the answer receiving module 213 acquires a corrected answer after the output module 215 displays the reconfirmation guidance screen 1800 or 1900. 20 is an example of a review correction rate display screen 2000 output by the analysis display module 216 to at least one of the user terminal 102 and the instructor terminal 103. By the analysis display module 216 displaying the review correction rate on the user terminal 102 and / or the instructor terminal 103, it can be confirmed that about 70% (67.1%) of users who viewed the reconfirmation guidance screens 1800 and 1900 were able to review and correct their answers at least once.

[0094] A review and correction rate higher than 0% can be considered to make users aware of the need to recheck their answers. Also, the higher the review and correction rate, the lower the rate at which users make careless mistakes, and the more accurately the user's level of understanding of the question can be evaluated. Furthermore, for users who did not recheck their answers, additional measures (for example, follow-up guidance) can be taken depending on the cause or tendency of not being able to make corrections.

[0095] The analysis display module 216 calculates the review correction rate for each type of incorrect answer. The review correction rate for each type of incorrect answer is, for example, a review correction rate calculated for each type of incorrect answer (i.e., for each incorrect answer ID). The analysis display module 216 can calculate the review correction rate for each type of incorrect answer for each user and / or for each question. FIG. 21 is an example of a display screen 2100 showing the correction rate for each type of incorrect answer. The analysis and display module 216 calculates the review and correction rate for each type of incorrect answer, making it possible to grasp the types of incorrect answers that are more likely to result in careless mistakes.

[0096] The analysis display module 216 calculates the correction correct rate. The correction correct rate is, for example, the rate at which the corrected answers acquired by the answer receiving module 213 are evaluated as correct by the answer evaluation module 214. By calculating the correction correct rate, the analysis display module 216 can grasp the rate at which users who have a degree of understanding of the question make careless mistakes. In addition, the higher the correction correct rate, the more careless mistakes are reduced, and it can be confirmed that the user's degree of understanding of the question can be more accurately evaluated.

[0097] The analysis display module 216 performs the analysis of the above evaluation results over time, for example, at predetermined intervals. For example, the analysis display module 216 calculates the careless mistake rate at the end of each predetermined period, thereby making it possible to grasp the change in the frequency of careless mistakes made by the user.

[0098] (Looking back) The content output module 212 may be configured to output questions related to the backward unit to the user terminal 102 in the case of evaluation (B), and not output questions related to the backward unit in the case of evaluation (C). That is, when the answer is evaluated to be an essential wrong answer, the content output module 212 presents other questions related to the backward unit of the learning unit to which the incorrect question belongs, and when the answer is evaluated to be a non-essential wrong answer, it does not present other questions related to the backward unit of the learning unit to which the incorrect question belongs.

[0099] For example, when the output module 215 displays a screen containing an incorrect answer, a button labeled "Ask questions related to the backward unit" or the like may be displayed on the incorrect answer screen, and when the content output module 212 receives a user's selection of the button, it may be configured to output questions related to the backward unit to the user terminal 102. Alternatively, the output module 215 may be configured to output a question related to the retroactive unit when the user has finished studying the currently studying study content. With this configuration, it is possible to prevent the user from moving on to the next learning content without essentially understanding the learning content.

[0100] (Action according to the content of the careless mistake) The content output module 212 may change the content of the study content to be output next depending on the type of incorrect answer (eg, depending on the incorrect answer ID). For example, the content output module 212 may be configured to, when the user answers a question incorrectly, extract and output, as the next question, a question (a similar question) that is likely to lead to a similar answer incorrectly.

[0101] The timing of outputting the type of incorrect answer may be on a question-by-question basis (for example, as the immediately next question, or as the question 2-3 questions later) or on a learning unit basis (for example, the immediately next learning unit or learning content).

[0102] Furthermore, for example, when a user gives a wrong answer to a certain question, the content output module 212 subsequently outputs an explanation for the wrong answer corresponding to each type of wrong answer when the type of the wrong answer given by the user (which may be, for example, an incorrect answer ID) is, for example, "third person singular s," "past tense," "singular / plural," etc. The content output module 212 may be configured to output the similar questions immediately after outputting the explanation for the wrong answer, or at a predetermined timing.

[0103] The content output module 212 may be configured to output an explanation and / or a similar question for such an incorrect answer when the user's learning proficiency is equal to or higher than a predetermined threshold, for example. The content output module 212 may also be configured not to output an explanation and / or a similar question for such an incorrect answer when the user's learning proficiency is lower than a predetermined threshold, for example. In addition, the content output module 212 may, for example, when a user gives an incorrect answer to a question for which there are no similar questions (for example, a mistake in the contraction of an English word), provide only an explanation so that no similar questions are given.

[0104] The content output module 212 may be configured to output or not output an explanation and / or a similar question for such a wrong answer depending on the timing of the user's wrong answer, for example. For example, the content output module 212 may be configured to output an explanation for the wrong answer of the same type if a predetermined time has passed since the previous output of an explanation for the same type of wrong answer or if it is the first time, and not output an explanation for the wrong answer of the same type if the predetermined time has not passed. In this case, the content output module 212 may also be configured to output the similar question if a predetermined time has passed or if it is the first time, and not output it if the predetermined time has not passed. On the other hand, the content output module 212 may be configured to output the similar question every time separately from the explanation, or may be configured to output or not output based on a reference time different from the explanation.

[0105] The types of incorrect answers (e.g., incorrect answer IDs) may be classified into those for which valid similar questions can be prepared and those for which valid similar questions cannot be prepared. If the incorrect answer given by the user to a question is one for which no valid similar questions can be prepared (e.g., an abbreviation mistake), the content output module 212 may only provide an explanation and not give a similar question. With this configuration, it is possible to provide more appropriate information to the user.

[0106] (Using incorrect answers) The answer evaluation module 214 may be configured to store English words that are misspelled (misspelled) among the incorrect answers given by the user. For example, the answer evaluation module 214 classifies the type of incorrect answer for differences between the answers and the correct answers. For example, in the above example of <Evaluation Example 2>, the answer evaluation module 214 classifies the type of incorrect answer for all differences. The answer evaluation module 214 stores, for example, the correct answer for the English word misspelled by the user, by attaching a tag corresponding to the spelling mistake G1050, for example. Although not essential, the answer evaluation module 214 may store the English word misspelled by the user (incorrect answer) in association with the correct answer.

[0107] The answer evaluation module 214 may record the English words (correct answers and / or incorrect answers) that the user misspelled as an English vocabulary book. In this case, the answer evaluation module 214 may record all words tagged with the spelling mistake G1050 as a vocabulary book. Alternatively, the answer evaluation module 214 may record the English words (correct answers and / or incorrect answers) that the user specified among the English words (correct answers and / or incorrect answers) that the user specified as an English vocabulary book. The user's instruction may be, for example, configured such that the output module 215 displays the misspelled word, a message "Would you like to save this in your vocabulary book?", a Yes button, and a No button on the correct answer screen, the incorrect answer screen, and the reconfirmation guidance screen, and when the answer evaluation module 214 receives the selection of the Yes button by the user, the answer evaluation module 214 stores the misspelled English word as a vocabulary book. This allows the user to relearn the misspelled English word, and the English word can be efficiently fixed in memory.

[0108] <Variation 1> The method of determining and outputting the evaluation content according to the present technology is not limited to the above example. For example, the answer evaluation module 214 may determine the evaluation content by taking into account the user's proficiency in the learning unit. Other points may be the same as the above example, and the description of the common configuration and effects will be omitted.

[0109] 13 is another example of evaluation content determination flow 1300. Evaluation content determination flow 1300 differs from evaluation content determination flow 1200 in that, among all steps S1305 to S1355, S1315 and S1335 related to proficiency are added. S1305, S1310, S1320, S1325, S1330, S1340, S1345, S1350, and S1355 in evaluation content determination flow 1300 can be implemented in the same manner as S1210, and S1220 to S1290 in evaluation content determination flow 1200, respectively.

[0110] The answer evaluation module 214 acquires the correct answer to the question and the incorrect answer pattern information 1000 (S1305, S1310). The answer evaluation module 214 also acquires the degree of proficiency (S1315).

[0111] The proficiency level is an index representing the user's proficiency (for example, the level of understanding) for this learning unit. The answer evaluation module 214 can calculate the proficiency level by evaluating, for example, how much knowledge the user has about the learning unit, how much the user understands about the learning unit, and how long the user has studied the learning unit. Specifically, the answer evaluation module 214 calculates the proficiency level based on, for example, the score, the correct answer rate, the correct answer rate in the evaluation test, the learning content completion level, the learning progress level, the learning time, and the like, for the learning unit. The answer evaluation module 214 can calculate this information based on, for example, information recorded as learning history information, and the like. Note that the answer evaluation module 214 only needs to acquire the proficiency level before the subsequent step S1335, and there is no particular restriction on the timing of acquisition from other perspectives.

[0112] The answer evaluation module 214 compares the answer with the correct answer (S1320), judges whether the answer is the same as the correct answer (S1325), and judges whether the answer corresponds to a non-essential incorrect answer pattern (S1330). If it is judged that the answer is the same as the correct answer (Yes in S1325), the answer evaluation module 214 evaluates the answer as correct.

[0113] On the other hand, if the answer corresponds to a non-essential incorrect answer pattern (Yes in S1330), the answer evaluation module 214 judges whether the proficiency is higher than a predetermined level (S1335). The predetermined level may be, for example, a level at which it is judged that the user fully understands the learning contents of the learning unit. The predetermined level may be, for example, a pass level, such as a proficiency level based on the correct answer rate of 70% or more.

[0114] If the proficiency is not determined to be higher than the predetermined level (No in S1335), the answer evaluation module 214 evaluates the answer as including a substantial error (S1345). If the proficiency level is determined to be higher than the predetermined level (Yes in S1335), the answer evaluation module 214 evaluates the answer as being essentially incorrect (S1350).

[0115] In this manner, the answer evaluation module 214 determines, for example, one of the following three evaluation results for all answers (S1355). Rating (A) The answer is correct. Rating (B): The answer is fundamentally wrong. Rating (C) The answer contains a non-essential error.

[0116] The output module 215 outputs the evaluation result according to the output flow 1400, as in the above embodiment. With this configuration, if the user does not have sufficient proficiency in the unit, careless mistakes are likely to occur, so the user's understanding of the unit can be evaluated by considering whether or not a wrong answer is caused by a careless mistake (non-essential wrong answer). On the other hand, if the user has a high level of proficiency in the unit, careless mistakes can also be determined to be wrong answers, and the user can be prompted to be careful of careless mistakes themselves in addition to solving the problems.

[0117] If the answer is a non-essential wrong answer, it is also possible to consider whether the wrong answer is due to a careless mistake (non-essential wrong answer) only by internal processing without outputting a display prompting the user to confirm the answer. However, by the output module 215 outputting a display prompting the user to confirm the answer, it is possible to more reliably make the user aware of the action of rechecking whether there is a careless mistake.

[0118] <Variation 2> The method of outputting a display prompting confirmation of the answer while taking into account the user's proficiency is not limited to the above example. For example, the output module 215 may determine whether to output a display prompting confirmation of the answer while taking into account the user's proficiency with respect to the learning unit. Other points may be the same as those described above, and a description of the common configuration and effects will be omitted.

[0119] 15 is another example of the output flow 1500. The output flow 1500 differs from the output flow 1400 in that, among all steps S1510 to S1570, steps S1520 and S1540 relating to proficiency are added. S1510, S1530, and S1550 to 1570 in the output flow 1500 can be implemented in the same manner as S1410 to S1450 in the output flow 1400, respectively.

[0120] The output module 215 acquires the evaluation result by the answer evaluation module 214 (S1510). The output module 215 also acquires the user's proficiency with respect to the unit (S1520). There are no particular limitations on the timing of S1520, so long as it is performed before the subsequent process S1540. The output module 215 then executes output processing according to the evaluation result (S1530).

[0121] Here, when the answer is evaluation (A), the output module 215 outputs (displays) a correct answer screen indicating that the answer is correct on the user terminal 102 (S1550), for example, similar to the output flow 1400. Also, when the answer is evaluation (B), the output module 215 outputs (displays) an incorrect answer screen indicating that the answer is incorrect on the user terminal 102 (S1570), for example, similar to the output flow 1400.

[0122] If the answer is graded (C), the output module 215 judges whether the proficiency level is higher than a predetermined level (S1540). The predetermined level of proficiency is the same as described above. If the proficiency level is not judged to be higher than the predetermined level (No in S1540), the output module 215 outputs (displays) a reconfirmation prompting screen (S1560) to the user terminal 102, for example, as in S1440. That is, the output module 215 acquires proficiency information about the learning unit to which the question belongs, and outputs a display prompting confirmation of the answer if the proficiency level is lower than a predetermined threshold.

[0123] On the other hand, if the proficiency level is determined to be higher than the predetermined level (Yes in S1540), the output module 215 outputs (displays) an incorrect answer screen indicating that the answer is incorrect, for example, to the user terminal 102, as in the case where the evaluation result is (B) (S1570). That is, the output module 215 acquires proficiency information about the learning unit to which the question belongs, and does not output a display prompting confirmation of the answer if the proficiency level is equal to or higher than a predetermined threshold. If the proficiency level is lower than the predetermined threshold, it outputs a display prompting confirmation of the answer.

[0124] According to such a configuration, when a careless mistake is made and the evaluation is graded (C), the output module 215 can determine whether or not to output a reconfirmation prompting screen. Therefore, it is possible to avoid the cumbersome process of giving the evaluation result an evaluation of (B) even though the evaluation result includes a careless mistake, as in the case of the modification 1. The output module 215 can determine whether or not to output a reconfirmation prompting screen based on any index, and may be, for example, another index of proficiency.

[0125] The present invention is not limited to the above-described embodiment, but includes various modified examples. For example, the above-described embodiment has been described in detail to clearly explain the present invention, and is not necessarily limited to those including all of the configurations described. It is also possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. It is also possible to add, delete, or replace a part of the configuration of each embodiment with another configuration.

[0126] In the above embodiment, in order to facilitate understanding, the present technology has been described based on the case where the learning subject is learning English and the learning content includes fill-in-the-blank questions. Those skilled in the art can understand that the learning subject and learning content of the present technology are not limited to the above example. For example, non-essential incorrect answers may be incorrect units in mathematics, missing punctuation in Japanese, incorrect kanji, wording, person names, place names, etc. in Japanese. In addition, the learning content is not limited to the learning of a single subject, but can be applied to learning subjects and learning content that combine multiple subjects.

[0127] In the above embodiment, for example, the answer evaluation module 214 stores the words that the user misspelled. However, the operation and function of each module are not limited, and other modules may be configured to realize similar operations and functions.

[0128] In addition, the above-mentioned configurations, functions, processing units, processing means, etc. may be realized in part or in whole by hardware, for example, by designing them as integrated circuits. In addition, the above-mentioned configurations, functions, etc. may be realized in software by a processor interpreting and executing a program that realizes each function. Information such as the program, table, file, etc. that realizes each function can be stored in a memory, a recording device such as a hard disk or SSD (Solid State Drive), or a recording medium such as an IC card, SD card, or DVD.

[0129] In addition, the control lines and information lines shown are those that are considered necessary for the explanation, and not all control lines and information lines in the product are necessarily shown. In reality, it can be considered that almost all components are connected to each other. The above-described embodiment discloses at least the configurations described in the claims. [Explanation of symbols]

[0130] 100... learning support system, 101... management server, 102... user terminal, 103... instructor terminal, 211... user terminal management module, 212... content output module, 213... answer reception module, 214... answer evaluation module, 215... output module, 216... analysis display module, 217... instructor terminal management module, 311... user learning management module, 312... user learning execution module

Claims

1. an answer acceptance unit that accepts answers to questions; an answer evaluation unit that evaluates whether the answer is a non-essential incorrect answer; an output unit that outputs a display prompting the user to confirm the answer if the answer is a non-essential incorrect answer; A learning support system equipped with:

2. The answer evaluation unit obtains a correct answer to the question, and when the answer is the same as the correct answer, evaluates the answer as being a correct answer rather than an unessential incorrect answer; The learning support system according to claim 1 , wherein the output unit outputs a display indicating that the answer is a correct answer.

3. 3. The learning support system according to claim 2, wherein the answer evaluation unit acquires error pattern information indicating a classification of an error, and evaluates the answer to be a non-essential error if the answer corresponds to a classification of a non-essential error in the error pattern information.

4. The answer evaluation unit acquires error pattern information indicating a classification of an error, and evaluates the answer as an non-essential error when the answer corresponds to a classification of a non-essential error in the error pattern information; The learning support system according to claim 2 , wherein the output unit acquires information regarding the level of proficiency for the learning unit to which the question belongs, and outputs a display prompting the user to confirm the answer if the level of proficiency is lower than a predetermined threshold.

5. The answer evaluation unit acquires error pattern information indicating a classification of an error, and evaluates the answer as an non-essential error when the answer corresponds to a classification of a non-essential error in the error pattern information; The learning support system of claim 2 , wherein the output unit acquires information regarding the level of proficiency for the learning unit to which the question belongs, and if the level of proficiency is equal to or above a predetermined threshold, does not output a display prompting confirmation of the answer.

6. The answer evaluation unit acquires error pattern information indicating a classification of an error, and evaluates the answer as an essential error if the answer does not correspond to a classification of a non-essential error in the error pattern information; The learning support system according to claim 2 , wherein the output unit does not output a display prompting the user to confirm the answer.

7. The answer evaluation unit acquires error pattern information indicating a classification of an error, and evaluates the answer as an essential error if the answer does not correspond to a classification of a non-essential error in the error pattern information; The learning support system according to claim 2 , wherein the output unit outputs a display indicating that the answer is essentially an incorrect answer.

8. The learning support system according to claim 1 , wherein the output unit outputs information regarding classification of non-essential errors as a display for prompting confirmation of the answer.

9. It has a question setting department that sets questions, The question setting unit is If the answer is evaluated as being essentially incorrect, another question related to the learning unit to which the incorrect answer belongs is presented; 8. The learning support system according to claim 6, wherein if the answer is evaluated to be a non-essential incorrect answer, other questions related to a learning unit that is a retroactive unit to which the incorrectly answered question belongs are not presented.

10. An analysis and display unit that analyzes and displays the evaluation result of the answer, The learning support system according to claim 1 , wherein the analysis and display unit displays a percentage of the non-essential incorrect answers in a total number of the answers that are not correct.

11. An analysis and display unit that analyzes and displays the evaluation result of the answer, The learning support system according to claim 1 , wherein the analysis and display unit displays information on a change over time in a proportion of the non-essential incorrect answers to a total number of the answers that are not correct.

12. An analysis and display unit that analyzes and displays the evaluation result of the answer, The learning support system according to claim 1 , wherein the analysis and display unit displays a percentage of incorrect answers for each error category in a total number of the answers that are not correct.

13. A method for assisting learning by a computer, comprising the steps of: Accept the answer to the question, Evaluate whether the answer is a non-essential error; A learning support method that outputs a display prompting a user to confirm the answer if the answer is a non-essential incorrect answer.

14. A program for causing a computer to execute each step of the method according to claim 13.

Images