Information processing device, information processing method and information processing program

Abstract

To support effective review of questions.SOLUTION: An information processing device includes a communication part for outputting a question to a terminal, an acquisition part for acquiring a user's degree of understanding of the question based on an answer to the question input via the terminal and additional information of the question, and a setting part for setting questioning intervals of the question to the user based on the user's degree of understanding.SELECTED DRAWING: Figure 6

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device, an information processing method, and an information processing program that support learning. [Background technology]

[0002] Reviewing the same problem is known to be an effective learning method for solidifying understanding of that problem. This is because even if you have memorized something once, you may forget it over time. By repeating something you have forgotten several times, you become less likely to forget it, and the rate of forgetting per unit of time decreases. In other words, the memory moves from short-term memory to long-term memory and is solidified.

[0003] Learning is done for a variety of purposes. It can be for exams such as qualifications, for academic purposes, or for self-improvement such as learning a language. Whatever the purpose of learning, it is important to study efficiently.

[0004] Patent Document 1 describes that after a learner completes the answering process, the learner selects a new level of understanding relative to the previous level of understanding, and sets an optimal number of days between reviews based on the level of understanding. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Laid-Open No. 2008-203817 Summary of the Invention [Problem to be solved by the invention]

[0006] However, the level of understanding disclosed in Patent Document 1 is selected by the learner, and may therefore deviate from the learner's actual level of understanding. If the level of understanding selected by the learner deviates from the learner's actual level of understanding, the number of days between reviews set based on the level of understanding cannot be said to be optimal for the learner.

[0007] Therefore, the present invention aims to provide a technique for supporting effective review of questions. [Means for solving the problem]

[0008] The information processing device according to the present disclosure comprises a communication unit that outputs questions to a terminal, an acquisition unit that acquires a user's level of understanding of the questions based on the answers to the questions and additional information about the questions input via the terminal, and a setting unit that sets the interval at which questions are presented to the user based on the user's level of understanding.

[0009] The information processing device according to the present disclosure includes a communication unit that outputs questions to a terminal, an acquisition unit that acquires a user's level of understanding of the questions based on answers to the questions input via the terminal, and a setting unit that sets the interval between questions being presented to the user based on the relationship between the level of understanding and the question interval according to multiple answer histories for one or more questions and the user's level of understanding. [Effects of the Invention]

[0010] Embodiments according to the present disclosure support effective review of questions. [Brief explanation of the drawings]

[0011] [Figure 1] FIG. 1 is a block diagram showing an example of the configuration of a server according to the first embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of setting values ​​according to the first embodiment. [Figure 3] FIG. 3 is a graph showing relationship data according to the accuracy rate according to the first embodiment. [Figure 4] FIG. 4 is a table showing an example of relationship data according to accuracy rates according to the first embodiment. [Figure 5] FIG. 5 is a flowchart showing an example of a question setting process executed by the server according to the first embodiment. [Figure 6] FIG. 6 is a diagram showing an example of timing of setting a question according to the first embodiment. [Figure 7] FIG. 7 is a flowchart showing an example of the relationship data generation process executed by the server according to the first embodiment. [Figure 8] FIG. 8 is a diagram illustrating an example of setting values ​​according to the second embodiment. [Figure 9] FIG. 9 is a diagram showing an example of displaying a plurality of second options according to the second embodiment. [Figure 10] FIG. 10 is a flowchart showing an example of a question setting process executed by the server according to the second embodiment. [Figure 11] FIG. 11 is a diagram illustrating an example of setting values ​​according to the third embodiment. [Figure 12] FIG. 12 is a diagram showing an example of displaying a plurality of second options according to the third embodiment. [Figure 13] FIG. 13 is a flowchart showing an example of a question setting process executed by the server according to the third embodiment. [Figure 14] FIG. 14 is a block diagram showing an example of the configuration of a server according to the fourth embodiment. [Figure 15] FIG. 15 is a flowchart showing an example of a question setting process executed by the server according to the fourth embodiment. [Figure 16] FIG. 16 is a flowchart showing an example of the process of generating an additional information prediction model executed by the server according to the fourth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, several embodiments will be described with reference to the drawings.

[0013] [First embodiment] (Configuration example) FIG. 1 is a block diagram showing an example of the configuration of the server 1. As shown in FIG. The server 1 is an electronic device that distributes content to each user's terminal via a network NW and supports each user's learning. Here, an example will be described in which the server 1 supports studying for an exam such as a qualification exam. In this example, each user is a user who has registered to take various exam courses. The server 1 can support various types of learning, such as studying for academics and self-improvement in language learning, in addition to studying for an exam such as a qualification exam. The server 1 is an example of an information processing device. The network NW includes at least one network selected from the Internet, a mobile network, and a LAN (Local Area Network). Here, a user who owns a terminal 2 will be used as an example for description. The user who owns the terminal 2 is also referred to as a target user. The target user is an example of a user. The user includes the intention of a student or learner.

[0014] The exam may be an exam in which the final result is pass / fail or an exam in which the final result is a score, and is not limited to this. For example, an exam in which the final result is pass / fail is an exam related to the granting of a qualification. An exam related to the granting of a qualification may be an exam related to the granting of a national qualification or an exam related to the granting of a private qualification. For example, an exam in which the final result is a score is an exam related to a language. The exam may be an entrance exam. Exams include tests, certifications, etc.

[0015] For example, each exam course is made up of multiple units for each subject that makes up the exam. A unit is a group of content based on a theme or the like. Here, an example will be described in which the lessons related to each unit include input lessons and output lessons. However, the lessons related to each unit may be made up of output lessons without including input lessons.

[0016] An input lesson is a lesson for a user to acquire knowledge. For example, an input lesson is taken on a terminal. An input lesson may be taken by watching a video or listening to audio on a terminal. An input lesson may be taken by using an electronic text on a terminal. An input lesson may be taken by combining watching a video or listening to audio and using an electronic text. The server 1 can obtain the time a user has spent taking an input lesson, etc., from the user's attendance log.

[0017] An output lesson is a lesson in which a user confirms the retention of knowledge by solving problems. An output lesson includes one or more questions. For example, an output lesson is taken by answering each question on a terminal. In this example, the server 1 can obtain the time the user spent taking the output lesson and whether each question was correct or incorrect from the user's attendance log.

[0018] An example of the configuration of the server 1 will be described. The server 1 includes a processor 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, a storage device 14, and a communication interface 15. The processor 11, the ROM 12, the RAM 13, the storage device 14, and the communication interface 15 are connected to one another via a data bus or the like. In Fig. 1, the communication interface is described as "communication I / F."

[0019] The processor 11 corresponds to the central part of the server 1. The processor 11 is an element that constitutes the computer of the server 1. The processor 11 is a CPU (Central Processing Unit), but is not limited to this. The processor 11 may be configured with a circuit including a field programmable gate array or the like. The processor 11 loads a program stored in the ROM 12 or the storage device 14 into the RAM 13. The processor 11 executes the program loaded into the RAM 13 to realize each unit described below and perform various functions.

[0020] The ROM 12 corresponds to the main storage portion of the server 1. The ROM 12 is a non-volatile memory that stores control programs, control data, etc. in advance. The ROM 12 is an element that constitutes the computer of the server 1.

[0021] The RAM 13 corresponds to the main storage portion of the server 1. The RAM 13 is a volatile memory that temporarily stores data and the like being processed by the processor 11. The RAM 13 is a component that constitutes the computer of the server 1.

[0022] The storage device 14 corresponds to an auxiliary storage portion of the server 1. The storage device 14 is a device configured with a non-volatile memory that stores data, programs, etc. The storage device 14 is configured with an HDD (Hard Disk Drive) or an SSD (Solid State Drive), etc., but is not limited to these. The storage device 14 is an example of a storage unit. The storage device 14 includes a lesson data storage area 141. The lesson data storage area 141 stores content data of input lessons related to each unit for each test course. The lesson data storage area 141 stores content data of output lessons related to each unit for each test course.

[0023] The content data of the output lesson includes data for each question. Hereinafter, the question data may be referred to as a "question." A question includes a question statement and multiple first choices for answering the question. A question is asked as a new question and then repeatedly asked as a review question. A new question means an unanswered question that is asked for the first time. A review question means a question that has been answered at least once. An answer refers to the user's answer.

[0024] The content data of the output lesson includes data on the correct answers to each question. Hereinafter, the data on the correct answers to the questions may be referred to as "correct answers to the questions." The correct answers to the questions include the correct answers and explanations of the questions.

[0025] The storage device 14 includes a user data storage area 142. The user data storage area 142 stores user data for each user. The user data includes the user's level of understanding associated with each question. The level of understanding is a value indicating the user's level of understanding of the question. The value indicating the level of understanding indicates how certain the user currently is of the correct answer to the question. As the level of understanding increases, the user is more likely to be certain of the correct answer to the question. When the level of understanding is at the minimum, the user is assumed to have no memory of the correct answer to the question. Here, an example in which the minimum level of understanding is "0%" is described, but this is not limited to this example. When the level of understanding is at the maximum, the user is assumed to have certain of the correct answer to the question. The maximum level is the level of understanding at which the question is completed. If the level of understanding of a question is equal to or greater than the maximum level, the question will not be presented again as a review question. If the level of understanding of a question is below the maximum level, the question will be presented again as a review question. The maximum level may be a fixed value set for all users. The maximum level may be a value selected by the user from within a predetermined range via the terminal. Here, an example in which the maximum level of understanding is "100%" is described, but this is not limited to this example. The level of understanding is updated for each answer to a question. The level of understanding is a parameter used to set the interval between questions so that the same question is repeatedly presented as a review question. The interval between questions will be described later. The user data includes, for each question that has been answered at least once, the value of the level of understanding after the acquisition process of the acquisition unit 113, which will be described later. The user data includes, for each unanswered question, an initial value as the level of understanding. The initial value may be "0%" or a value greater than "0%". The initial value can be set as appropriate. Here, the explanation will be given assuming that the initial value is "0%".

[0026] The user data includes a question presentation interval associated with each question that has been answered at least once. The question presentation interval is the interval at which the same question is repeatedly presented as a review question. The question presentation interval included in the user data is a value after the setting process for the question presentation interval by the setting unit 114, which will be described later. The question presentation interval is the interval from the previous question presentation timing to the new question presentation timing. The previous question presentation timing is the question presentation timing at the time of the setting process for the question presentation timing by the setting unit 114, which will be described later. The new question presentation timing is the question presentation timing after the setting process for the question presentation timing by the setting unit 114. The question presentation interval is set based on the level of understanding after the acquisition process for the level of understanding by the acquisition unit 113.

[0027] The user data includes the question presentation timing associated with each question for each question that has been answered at least once. For example, the question presentation timing is the scheduled question presentation date. The question presentation timing is the timing at which the same question is repeatedly presented as a review question. The question presentation timing is set based on the question presentation interval after the setting unit 114 has performed the setting process for the question presentation interval. The question presentation timing included in the user data is the question presentation timing after the setting unit 114 has performed the setting process for the question presentation timing.

[0028] For each question, the user's level of understanding, the question presentation interval, and the question presentation timing are associated with each other. The question presentation interval and the question presentation timing are updated based on updates to the user's level of understanding.

[0029] The user data includes one or more answer histories associated with each question for each question that has been answered at least once. The answer history includes the question interval, the level of understanding at the time of question presentation, and whether the answer was correct or incorrect. The question interval included in the answer history is the interval between questions presented that are associated with questions presented based on the question presentation time. The level of understanding at the time of question presentation included in the answer history is the user's level of understanding of questions that are associated with questions presented based on the question presentation time. The correctness of the answer included in the answer history is the correctness of the answer to the question presented based on the question presentation time. The correctness of the answer includes whether the answer is correct or incorrect. A correct answer is when the answer matches the correct answer. An incorrect answer is when the answer does not match the correct answer.

[0030] The user data includes a set accuracy rate. The accuracy rate is a value related to the likelihood of correctly answering a question. The accuracy rate is a value where "100%" is the time when the user correctly answers the question. The accuracy rate decreases from "100%" as time passes from the time when the user correctly answers the question. For example, the time is days. The curve showing the tendency of the accuracy rate to decrease over time varies depending on the level of comprehension. The curve showing the tendency of the accuracy rate to decrease over time is also called a forgetting curve. The time it takes for the accuracy rate to decrease from "100%" to the set accuracy rate increases as the level of comprehension increases. This is because the higher the level of comprehension, the less likely it is to forget the correct answer to a question. The set accuracy rate is used to calculate the relationship data to be applied to the user, as described below. The set accuracy rate may be a fixed value, such as "90%," set commonly to all users. The set accuracy rate may also be a value selected by the user from within a predetermined range via a terminal. Selection is an example of input.

[0031] The user data includes an upper limit of the understanding level.

[0032] The storage device 14 includes a relationship data storage area 143. The relationship data storage area 143 stores relationship data for at least one accuracy rate. The relationship data storage area 143 may store relationship data for each accuracy rate for multiple accuracy rates. Hereinafter, the relationship data may be referred to as a "relationship."

[0033] The relationship data shows the relationship between the level of understanding and the question interval. The question interval is the time it takes for the correct answer rate to drop from "100%" to the correct answer rate associated with the relationship data. The time it takes for the correct answer rate to drop from "100%" to the correct answer rate associated with the relationship data increases as the level of understanding increases, so the question interval also increases as the level of understanding increases. The relationship between the level of understanding and the question interval can be said to mimic the trend that the time it takes for the correct answer rate to drop from "100%" to the correct answer rate associated with the relationship data increases as the level of understanding increases.

[0034] For example, the relationship data is data corresponding to a plurality of answer histories to one or more questions. In this example, the relationship data is generated by machine learning based on a plurality of answer histories to one or more questions. The term "generated" includes not only new creation but also updating. The relationship data may be generated commonly for a plurality of questions for a plurality of users. In this example, the plurality of answer histories to one or more questions may be a plurality of answer histories to a plurality of questions by a plurality of users. The relationship data may be generated for each question. In this example, the plurality of answer histories to one or more questions may be a plurality of answer histories to a single question by a plurality of users. The plurality of answer histories to one or more questions may be a plurality of answer histories to a single question by a single user. The relationship data may be generated for each user. In this example, the plurality of answer histories to one or more questions may be a plurality of answer histories to a plurality of questions by a single user. The plurality of answer histories to one or more questions may be a plurality of answer histories to a single question by a single user.

[0035] For example, the relationship data is curved data that shows the relationship between the level of understanding and the question interval. The relationship data is a non-linear relationship. The relationship data is a relationship in which the question interval becomes longer as the level of understanding increases. This is because, as mentioned above, the time it takes for the correct answer rate to decrease from "100%" to the correct answer rate associated with the relationship data becomes longer as the level of understanding increases. The relationship data is a relationship based on the correct answer rate. The relationship data differs depending on the correct answer rate. As the correct answer rate increases, the question interval for the same level of understanding becomes shorter. This is because the question interval is the time it takes for the correct answer rate to decrease from "100%" to the correct answer rate associated with the relationship data, and the time of decrease becomes shorter as the correct answer rate increases.

[0036] The communication interface 15 includes various interfaces that communicatively connect the server 1 to other electronic devices using a communication protocol defined by the network NW.

[0037] The hardware configuration of the server 1 is not limited to the above configuration, and the server 1 allows the omission or modification of the above components and the addition of new components as appropriate.

[0038] Each unit realized by the processor 11 will be described below. The processor 11 realizes a communication unit 111, a response processing unit 112, an acquisition unit 113, a setting unit 114, and a relationship data processing unit 115. Each unit realized by the processor 11 can also be referred to as each function. Each unit realized by the processor 11 can also be referred to as being realized by a control unit including the processor 11, ROM 12, and RAM 13.

[0039] The communication unit 111 communicates with the terminal 2 via the network NW. The communication unit 111 outputs content data of an input lesson to the terminal 2 via the network NW. The communication unit 111 outputs content data of an output lesson to the terminal 2 via the network NW. The communication unit 111 outputs questions to the terminal 2 via the network NW. Outputting questions to the terminal 2 is an example of presenting a question to the user. In one example, the communication unit 111 outputs a question related to a unit to the terminal 2 as a new question based on a request for an outlet lesson related to the unit. In another example, the communication unit 111 outputs a question to the terminal 2 as a review question based on a request for a review question. In this example, the communication unit 111 outputs a question related to a question timing on the same day as the review question request to the terminal 2 as a review question. If a question related to a question timing on a day before the review question request has not been output to the terminal 2 as a review question, the communication unit 111 outputs this question to the terminal 2 as a review question. The communication unit 111 outputs the correct answer to the question via the network NW to the terminal 2. The communication unit 111 acquires the answer to the question input via the terminal 2 via the network NW.

[0040] The answer processing unit 112 determines whether an answer to a question input via the terminal 2 is correct or incorrect. Determining whether an answer is correct or incorrect includes determining whether the answer is correct or incorrect.

[0041] The acquisition unit 113 acquires the target user's level of understanding of the question. For example, the acquisition unit 113 acquires the target user's level of understanding of the question based on the answer to the question input via the terminal 2. In this example, the acquisition unit 113 acquires the target user's level of understanding of the question depending on whether the answer to the question is correct or incorrect. The acquisition unit 113 increases the target user's level of understanding of the question when the answer to the question is correct. The acquisition unit 113 decreases the target user's level of understanding of the question when the answer to the question is incorrect. Acquiring the user's level of understanding of the question is an example of an understanding level acquisition process by the acquisition unit 113. Acquiring the user's level of understanding of the question includes updating the user's level of understanding of the question. The understanding level acquisition process includes an understanding level update process.

[0042] The acquisition unit 113 may acquire the target user's level of understanding for the question based on a set value. The set value is a value corresponding to whether the answer to the question is correct or incorrect. The set value is a value set to update the level of understanding at the time of the understanding acquisition process. The time of the understanding acquisition process includes a time before the understanding acquisition process. For example, the set value is a value to be added to the level of understanding at the time of the understanding acquisition process.

[0043] If the setting value is a positive value, the setting value is a value that increases the level of understanding. If the setting value is a negative value, the setting value is a value that decreases the level of understanding. If the answer is correct, the setting value is a positive value. This is because if the answer is correct, the user tends to remember the correct answer to the question. If the answer is incorrect, the setting value is a negative value. This is because if the answer is incorrect, the user tends not to remember the correct answer to the question. The setting value may be set commonly for multiple questions for multiple users. The setting value may be set for each user. The setting value may be set for each question. The setting value may be set according to the course, subject, unit, etc. The setting value can be set as appropriate.

[0044] If the answer to the question is correct, the acquisition unit 113 may increase the level of understanding after the update process by adding a positive set value to the level of understanding at the time of the update process of the level of understanding.If the answer to the question is incorrect, the acquisition unit 113 may decrease the level of understanding after the update process by adding a negative set value to the level of understanding at the time of the update process of the level of understanding.

[0045] The setting unit 114 sets the question presentation interval based on the target user's level of understanding of the questions acquired by the acquisition unit 113. For example, the setting unit 114 sets the question presentation interval based on the relationship data and the target user's level of understanding of the questions. Setting the question presentation interval is an example of a process for setting the question presentation interval by the setting unit 114. Setting the question presentation interval includes updating the question presentation interval. The process for setting the question presentation interval includes a process for updating the question presentation interval. The time point of the process for setting the question presentation interval includes a time point before the process for setting the question presentation interval.

[0046] The setting unit 114 sets the timing of question presentation based on the set question presentation interval. Setting the timing of question presentation is an example of a setting process of the timing of question presentation by the setting unit 114. Setting the timing of question presentation includes updating the timing of question presentation. The process of setting the timing of question presentation includes a process of updating the timing of question presentation. The time of the process of setting the timing of question presentation includes a time before the process of setting the timing of question presentation.

[0047] The relationship data processing unit 115 generates relationship data by machine learning based on a plurality of answer histories to one or more questions.

[0048] Terminal 2 will now be described. The terminal 2 is an electronic device used by the target user to take the course. For example, the terminal 2 is a personal computer (PC), but may also be, but is not limited to, a smartphone or a tablet. The terminal 2 may display content based on content data using a web browser, or may display content based on content data using an app.

[0049] The terminal 2 includes a processor 21, a ROM 22, a RAM 23, a storage device 24, a communication interface 25, an input device 26, a display device 27, and an image capturing device 28. The processor 21, the ROM 22, the RAM 23, the storage device 24, the communication interface 25, the input device 26, the display device 27, and the image capturing device 28 are connected to each other via a data bus or the like.

[0050] The processor 21 corresponds to the central part of the terminal 2. The processor 21 is configured with the same hardware as the processor 11 described above. The ROM 22 is configured with the same hardware as the ROM 12 described above. The RAM 23 is configured with the same hardware as the RAM 13 described above. The storage device 24 is configured with the same hardware as the storage device 14 described above. The communication interface 25 is configured with the same hardware as the communication interface 15 described above.

[0051] The input device 26 is a device that receives instructions based on operations by the target user, and is, but not limited to, a keyboard, a touchpad, a mouse, or the like.

[0052] The display device 27 is a device that displays images. The display device 27 is a liquid crystal display, but is not limited to this.

[0053] The photographing device 28 is a device that acquires image data of still images or videos based on photography. The image data includes photographic data of the target user based on photography of the target user by the photographing device 28. For example, the photographic data of the target user is data including images of the target user's body, such as the face and hands. For example, the photographing device 28 is a camera. Photographing the target user is an example of sensing the target user. The photographic data of the target user is an example of sensing data of the target user. The photographing device 28 is an example of a sensing device that acquires sensing data of the target user.

[0054] The hardware configuration of the terminal 2 is not limited to the above configuration, and the terminal 2 may appropriately omit or change the above components and add new components.

[0055] Examples of setting values ​​will be described below. FIG. 2 is a diagram illustrating an example of setting values. If the answer is correct, the set value is "+20%." If the answer is incorrect, the set value is "-50%." Note that these values ​​are examples, and the values ​​are not limited to these.

[0056] Explain relationship data. FIG. 3 is a graph showing the relationship data according to the accuracy rate. The horizontal axis represents the question interval. The vertical axis represents the level of understanding. The graph plots multiple answer histories. Points corresponding to each of the multiple answer histories are plotted at positions indicated by the question interval and level of understanding at the time of question presentation included in the answer history. A "circle" shown at the position where a point corresponding to the answer history is plotted indicates that the answer included in the answer history is correct. A "cross" shown at the position where a point corresponding to the answer history is plotted indicates that the answer included in the answer history is incorrect. An example will be explained where the answer history has a question interval of 3 days, a level of understanding at the time of question presentation of "50%", and a correct answer as the answer's accuracy. Points corresponding to the answer history are plotted at positions indicated by a question interval of 3 days and a level of understanding of "50%". A "circle" is shown at the position where a point corresponding to the answer history is plotted.

[0057] 3 shows a curve of the relationship data when the accuracy rate is "80%," a curve of the relationship data when the accuracy rate is "90%," and a curve of the relationship data when the accuracy rate is "95%." Note that these accuracy rates are examples, and the accuracy rates are not limited to these.

[0058] FIG. 4 is a table showing an example of relationship data according to accuracy rate. FIG. 4 shows, in table form, the relationship data when the accuracy rate is "80%" as indicated by the curve in FIG. 3, the relationship data when the accuracy rate is "90%, and the relationship data when the accuracy rate is "95%".

[0059] If the question interval is 0 days, the communication unit 111 outputs the question again to the terminal 2 on the same day as a review question. If the question interval is 1 day, the communication unit 111 outputs the question to the terminal 2 on the following day as a review question. If the question interval is complete, the communication unit 111 does not output the question to the terminal 2 as a review question.

[0060] Let's take an example where the comprehension level is 40%. In the relationship data where the correct answer rate is 80%, the question interval is 11 days. In the relationship data where the correct answer rate is 90%, the question interval is 8 days. In the relationship data where the correct answer rate is 95%, the question interval is 6 days. In this way, the relationship data differs depending on the correct answer rate. As the correct answer rate increases, the question interval for the same comprehension level becomes shorter.

[0061] Let's take the example of relationship data where the accuracy rate is "80%." When the level of understanding is "10%," the question interval is two days. When the level of understanding is "20%," the question interval is four days. When the level of understanding is "30%," the question interval is seven days. When the level of understanding is "40%," the question interval is 11 days. In this way, the relationship data shows a relationship in which the question interval becomes longer as the level of understanding increases. In this way, the amount of change in the question interval for each "10%" increase in comprehension is not constant, but gradually increases. Therefore, the relationship data shows a non-linear relationship.

[0062] (Example of operation) Next, an example of the operation of the server 1 configured as above will be described. The processing procedures described below are merely examples, and each process may be modified as much as possible. Furthermore, steps may be omitted, replaced, or added as appropriate depending on the embodiment.

[0063] Fig. 5 is a flowchart showing an example of a question setting process executed by the server 1. The server 1 executes the question setting process illustrated in Fig. 5 every time it outputs a question to the terminal 2 via the network NW. The question may be a new question or a review question. Hereinafter, a question that is the target of the question setting process is also referred to as a target question. A target question is an example of a question.

[0064] The communication unit 111 outputs the target question to the terminal 2 via the network NW (step S1). Based on the acquisition of the target question output from the server 1, the terminal 2 displays the target question on the display device 27. For example, the terminal 2 displays a question statement and a plurality of first options on the display device 27.

[0065] The communication unit 111 acquires, via the network NW, from the terminal 2 an answer to the target question input via the terminal 2 (step S2). For example, the answer to the target question includes one option selected by the target user from a plurality of first options via the input device 26 of the terminal 2.

[0066] The answer processing unit 112 determines whether the answer to the target question input via the terminal 2 is correct or incorrect (step S3). In step S3, for example, the answer processing unit 112 generates an answer history for the target question based on the determination of whether the answer to the target question is correct or incorrect. The answer processing unit 112 obtains the question presentation interval of the target question associated with the target question from the user data storage area 142, and sets the question presentation interval of the target question as the question presentation interval in the answer history. The answer processing unit 112 obtains the target user's level of understanding of the target question associated with the target question from the user data storage area 142, and sets the target user's level of understanding of the target question at the time of question presentation in the answer history. The answer processing unit 112 sets the correctness of the determined answer to the target question as the correctness of the answer in the answer history. The answer processing unit 112 associates the answer history related to the target question with the target user and saves it in the user data storage area 142.

[0067] The communication unit 111 outputs the correct answer to the target question to the terminal 2 via the network NW (step S4). Based on the acquisition of the correct answer to the target question output from the server 1, the terminal 2 displays the correct answer to the target question on the display device 27. For example, the terminal 2 displays the correct answer option from among the multiple first options and an explanation of the target question on the display device 27.

[0068] The acquisition unit 113 acquires the target user's level of understanding of the target question based on the answer to the target question input via the terminal 2 (step S5). In step S5, for example, the acquisition unit 113 acquires the target user's level of understanding of the target question based on whether the answer to the target question is correct or incorrect. The acquisition unit 113 may acquire the target user's level of understanding of the target question based on a set value according to whether the answer to the target question is correct or incorrect. The acquisition unit 113 stores the acquired level of understanding of the target user for the target question in the user data storage area 142 in association with the target question.

[0069] The setting unit 114 sets the question interval for the target question based on the target user's level of understanding of the target question acquired by the acquisition unit 113 (step S6). In step S6, for example, the setting unit 114 sets the question interval for the target question based on the relationship data and the target user's level of understanding of the target question. The setting unit 114 acquires the question interval corresponding to the target user's level of understanding of the target question from the relationship data. The setting unit 114 updates the question interval for the target question from the question interval for the target question at the time of the setting process for the question interval for the target question to the question interval acquired from the relationship data. The question interval acquired from the relationship data corresponds to the question interval for the target question after the setting process for the question interval for the target question. The setting unit 114 stores the question interval for the target question after the setting process for the question interval for the target question in the user data storage area 142 in association with the target question.

[0070] The setting unit 114 may compare the target user's level of understanding of the target question acquired by the acquisition unit 113 with the upper limit value. In this example, the setting unit 114 acquires the upper limit value associated with the target user from the user data storage area 142. The setting unit 114 compares the target user's level of understanding of the target question with the acquired upper limit value. The setting unit 114 determines whether or not to set an interval between the presentation of the target question to the target user based on the comparison result between the target user's level of understanding of the target question and the upper limit value. If the target user's level of understanding of the target question is less than the upper limit value, the setting unit 114 sets the interval between the presentation of the target question as described above. The target question is presented again as a review question. If the target user's level of understanding of the target question is equal to or greater than the upper limit value, the setting unit 114 does not set an interval between the presentation of the target question. The target question is not presented again as a review question.

[0071] The setting unit 114 sets the timing for presenting the target question based on the set question interval (step S7). In step S7, for example, the setting unit 114 sets a new question presentation timing by adding the set question presentation interval of the target question to the question presentation timing at the time of the setting process for the question presentation timing of the target question. The setting unit 114 associates the new question presentation timing with the target question and stores it in the user data storage area 142. Note that if the setting unit 114 does not set a question presentation interval for the target question in step S6, the setting unit 114 omits the processing of step S7.

[0072] The timing of the questions will be explained below. FIG. 6 is a diagram showing an example of timing of setting questions. FIG. 6 shows the timing at which a question is presented multiple times. "O" indicates that the answer is correct. "X" indicates that the answer is incorrect. FIG. 6 shows a graph in which the horizontal axis represents the number of days that have passed and the vertical axis represents the target user's understanding of the question. FIG. 6 shows a graph in which the horizontal axis represents the number of days that have passed and the vertical axis represents the correct answer rate. The set correct answer rate is referred to as the correct answer rate P.

[0073] The question presentation timing A1 will be described. At the question presentation timing A1, the communication unit 111 outputs a question to the terminal 2 as a new question. The answer is assumed to be incorrect. The acquisition unit 113 acquires a new level of understanding of "0%" by adding a negative setting value of "-50%" to the initial value of "0%," which is the level of understanding at the time of the understanding level acquisition process. The setting unit 114 sets a question presentation interval of "0 days" based on the level of understanding of "0%" after the understanding level acquisition process. The setting unit 114 sets the question presentation timing B1 based on the set question presentation interval of "0 days." The question presentation timing B1 is 0 days after the question presentation timing A1, which is set by adding the set question presentation interval of "0 days" to the question presentation timing A1 at the time of the setting process for the question presentation timing B1. From the question presentation timing A1 to the question presentation timing B1, the target user's level of understanding for the question is 0%. From the question presentation timing A1 to the question presentation timing B1, the correct answer rate is "0%."

[0074] The question presentation timing B1 will be described. At the question presentation timing B1, the communication unit 111 outputs the question to the terminal 2 as a review question. It is assumed that the answer is correct. The acquisition unit 113 acquires a new level of understanding of "20%" by adding a positive setting value of "+20%" to the level of understanding of "0%" at the time of the understanding level acquisition process. The setting unit 114 sets the question presentation interval of "1 day" based on the level of understanding of "20%" after the understanding level acquisition process. The setting unit 114 sets the question presentation timing C1 based on the set question presentation interval of "1 day". The question presentation timing C1 is one day after the question presentation timing B1, which is set by adding the set question presentation interval of "1 day" to the question presentation timing B1 at the time of the setting process of the question presentation timing C1. From the question presentation timing B1 to the question presentation timing C1, the target user's level of understanding of the question is "20%". At question presentation timing B1, the correct answer rate rises to 100% because the answer is correct. Between question presentation timing B1 and question presentation timing C1, the correct answer rate drops from 100% to the correct answer rate P over time.

[0075] The question presentation timing C1 will be described. The communication unit 111 outputs a question to the terminal 2 as a review question at the question presentation timing C1. It is assumed that the answer is correct. The acquisition unit 113 acquires a new level of understanding of "40%" by adding a positive setting value "+20%" to the level of understanding of "20%" at the time of the understanding level acquisition process. The setting unit 114 sets a question presentation interval of "4 days" based on the level of understanding of "40%" after the understanding level acquisition process. The setting unit 114 sets the question presentation timing D1 based on the set question presentation interval of "4 days". The question presentation timing D1 is four days after the question presentation timing C1, which is set by adding the set question presentation interval of "4 days" to the question presentation timing C1 at the time of the setting process for the question presentation timing D1. Between the question presentation timing C1 and the question presentation timing D1, the target user's level of understanding of the question is "40%". At question presentation timing C1, the correct answer rate rises to 100% because the answer is correct. Between question presentation timing C1 and question presentation timing D1, the correct answer rate drops from 100% to the correct answer rate P over time.

[0076] The question presentation timing D1 will be described. The communication unit 111 outputs a question to the terminal 2 as a review question at the question presentation timing D1. It is assumed that the answer is correct. The acquisition unit 113 acquires a new level of understanding of "60%" by adding a positive setting value of "+20%" to the level of understanding of "40%" at the time of the understanding level acquisition process. The setting unit 114 sets the question presentation interval of "8 days" based on the level of understanding of "60%" after the understanding level acquisition process. The setting unit 114 sets the question presentation timing E1 based on the set question presentation interval of "8 days." The question presentation timing E1 is 8 days after the question presentation timing D1, which is set by adding the set question presentation interval of "8 days" to the question presentation timing D1 at the time of the setting process for the question presentation timing E1. From the question presentation timing D1 to the question presentation timing E1, the target user's level of understanding of the question is "60%." At question presentation timing D1, the correct answer rate rises to 100% because the answer is correct. Between question presentation timing D1 and question presentation timing E1, the correct answer rate drops from 100% to the correct answer rate P over time.

[0077] The question presentation timing E1 will be described. The communication unit 111 outputs a question to the terminal 2 as a review question at the question presentation timing E1. It is assumed that the answer is correct. The acquisition unit 113 acquires a new level of understanding of "80%" by adding a positive setting value of "+20%" to the level of understanding of "60%" at the time of the understanding level acquisition process. The setting unit 114 sets a question presentation interval of "16 days" based on the level of understanding of "80%" after the understanding level acquisition process. The setting unit 114 sets the question presentation timing F1 based on the set question presentation interval of "16 days." The question presentation timing F1 is 16 days after the question presentation timing E1, which is set by adding the set question presentation interval of "16 days" to the question presentation timing E1 at the time of the setting process for the question presentation timing F1. From the question presentation timing E1 to the question presentation timing F1, the target user's level of understanding of the question is "80%." At question presentation timing E1, the correct answer rate rises to 100% because the answer is correct. Between question presentation timing E1 and question presentation timing F1, the correct answer rate drops from 100% to the correct answer rate P over time.

[0078] The question setting timing F1 will be explained. At the question setting timing F1, the communication unit 111 outputs a question to the terminal 2 as a review question. It is assumed that the answer is correct. The acquisition unit 113 acquires a new level of understanding of "100%" by adding a positive setting value of "+20%" to the level of understanding of "80%" at the time of the understanding level acquisition process. Since the level of understanding of "100%" after the understanding level acquisition process is equal to or greater than the upper limit value of "100%," the setting unit 114 does not set the question setting interval for the target question. After the question setting timing F1, the target user's level of understanding for the question is "100%". At the question setting timing F1, the correct answer rate rises to "100%" because the answer is correct. After the question setting timing F1, the correct answer rate remains at "100%".

[0079] As shown in Figure 6, the curve showing the trend of the decline in the accuracy rate over time is determined by the level of comprehension and differs depending on the level of comprehension. The curve showing the trend of the decline in the accuracy rate over time becomes flatter as the level of comprehension increases. It can be seen that the timing for review questions to be asked is when the accuracy rate drops from "100%" and falls below accuracy rate P. Since the time it takes for the accuracy rate to drop from "100%" to accuracy rate P increases as the level of comprehension increases, it can be seen that the interval between questions also increases as the level of comprehension increases. Setting the interval between questions based on the level of comprehension can be said to mimic the process of determining the time it takes for the accuracy rate to drop from "100%" to accuracy rate P based on the curve showing the trend of the decline in the accuracy rate over time, which is determined by the level of comprehension.

[0080] FIG. 7 is a flowchart showing an example of the relationship data generation process executed by the server 1.

[0081] The relationship data processing unit 115 may generate relationship data for each accuracy rate. The relationship data processing unit 115 may start the relationship data generation process at any timing and create new relationship data. The relationship data processing unit 115 may start the relationship data generation process at any timing and update the relationship data. Here, an example of the relationship data generation process for an accuracy rate P will be described.

[0082] The relationship data processing unit 115 acquires multiple answer histories for one or more questions (step S11). In step S11, for example, the relationship data processing unit 115 acquires multiple answer histories for one or more questions from the user data storage area 142.

[0083] The relationship data processing unit 115 generates relationship data by machine learning based on multiple answer histories for one or more questions (step S12). In step S12, for example, the relationship data processing unit 115 generates relationship data by machine learning based on the distribution of multiple answer histories as shown in FIG. 3. The relationship data processing unit 115 estimates the relationship between the level of understanding and the question interval corresponding to the correct answer rate P for each level of understanding based on the distribution of correct answers according to the question interval at each level of understanding. As shown in FIG. 3, the distribution of answer histories with correct answers tends to spread toward longer question intervals as the level of understanding increases. Therefore, the question interval corresponding to the correct answer rate P becomes longer as the level of understanding increases. This relationship between the level of understanding and the question interval corresponding to the correct answer rate P can be said to mimic the tendency that the time it takes for the correct answer rate to decrease from "100%" to the correct answer rate P becomes longer as the level of understanding increases. The relationship data processing unit 115 generates relationship data based on the estimation. The machine learning may be, but is not limited to, a neural network.

[0084] The relationship data processing unit 115 stores the generated relationship data in the relationship data storage area 143 (step S13).

[0085] (effect) The information processing device includes a communication unit that outputs questions to a terminal, an acquisition unit that acquires a user's level of understanding of questions based on answers to the questions input via the terminal, and a setting unit that sets the question presentation interval for the user based on the relationship between the level of understanding and the question presentation interval according to a plurality of answer histories for one or more questions, and the user's level of understanding. Since the forgetting curve differs depending on the user's level of understanding, the information processing device can set the question interval for the user based on the user's level of understanding, thereby setting the question interval so that review questions are presented at a timing that is effective for solidifying memory, just before forgetting. In this way, the information processing device can support effective review of questions by presenting review questions at effective timing and avoiding presenting more questions than necessary as review questions. By generating the relationship between the level of understanding and the question interval based on multiple answer histories for one or more questions, the information processing device can use the relationship between the level of understanding and the question interval to set the question interval so that review questions are asked at effective times.

[0086] In the information processing device, the acquisition unit updates the user's level of understanding depending on whether the answer is correct or incorrect. Since the user's level of understanding changes depending on whether the answer is correct or incorrect, and the forgetting curve differs depending on the user's level of understanding, the information processing device can set a question interval to present review questions at an effective timing depending on the updated level of understanding.

[0087] In the information processing device, the relationship is such that the interval between questions becomes longer as the level of understanding increases. This allows the information processing device to set the question interval using a relationship that reflects the characteristic that the higher the level of understanding, the less likely one is to forget. Therefore, the information processing device initially sets the interval between review questions to be short, and then sets the interval between review questions to be long as the user has memorized, so it is possible to set the question interval so that review questions are presented at effective times.

[0088] In the information processing device, the relationship is a relationship based on the accuracy rate regarding the possibility of correctly answering a question. This allows the user to change the relationship between the level of understanding and the question interval by setting the correct answer rate, and therefore the information processing device can set the question interval using the relationship according to the correct answer rate.

[0089] In the information processing device, the higher the correct answer rate for the relationship, the shorter the interval between questions at the same level of understanding. This allows the user to set a high correct answer rate if they want to study in a short period of time by shortening the question interval as much as possible.The user can set a low correct answer rate if they want to reduce the number of review questions per day by lengthening the question interval as much as possible.As a result, the information processing device can set the question interval so that review questions are presented at effective times while matching the user's study style.

[0090] In the information processing device, the answer histories include question intervals, levels of understanding at the time of question presentation, and correctness of answers. The relationships are generated by machine learning based on the answer histories. This allows the information processing device to improve the accuracy of the relationship between the level of understanding and the question interval, which enables setting the question interval so that review questions are presented at effective times. As a result, the information processing device can improve the accuracy of setting the question interval.

[0091] In the information processing device, a setting unit compares the user's understanding level with an upper limit value, and determines whether or not to set an interval between questions for the user based on the comparison result between the user's understanding level and the upper limit value. This makes it possible for the information processing device to prevent the same question from being repeatedly presented as a review question even after the level of understanding has reached or exceeded the upper limit.

[0092] [Second embodiment] The second embodiment is an embodiment in which a user's understanding of a question is acquired based on an answer to the question and first input additional information included in the first additional information for the question. In the second embodiment, the same components as those in the first embodiment are denoted by the same reference numerals, and their description will be omitted. In the second embodiment, the differences from the first embodiment will be mainly described.

[0093] (Configuration example) The configuration of the server 1 is the same as the configuration example described in the first embodiment using FIG. 1. The storage device 14 includes a lesson data storage area 141. As in the first embodiment, the lesson data storage area 141 stores content data of input lessons related to each unit for each exam course. As in the first embodiment, the lesson data storage area 141 stores content data of output lessons related to each unit for each exam course. In addition to the data described in the first embodiment, the content data of the output lessons includes data of multiple second options for inputting the first additional information described below. Hereinafter, the data of multiple second options may also be referred to as "multiple second options."

[0094] The additional information is information different from the answer to the question and is additional information to the question. The additional information is information that indicates the user's level of understanding of the question. As understanding of the question improves, the likelihood that the answer to the question is correct tends to increase. Therefore, the user's level of understanding of the question includes the likelihood that the user's answer to the question is correct. The additional information includes first additional information input via terminal 2. Since the first additional information is input via terminal 2, it is self-reported information based on the user's subjective opinion. The level of understanding indicated by the first additional information is one or more levels of understanding selected by the user from multiple levels of understanding via the terminal. Here, an example will be described in which the level of understanding is one level of understanding selected by the user from multiple levels of understanding via the terminal.

[0095] The first additional information includes first input additional information input before the display of the correct answer to the question on the terminal. The first input additional information includes information indicating the user's confidence in their answer to the question as information indicating the user's level of understanding of the question. The confidence in an answer is a subjective level of confidence in the answer based on the user's opinion. Confidence in the answer to the question tends to increase as the user's understanding of the question increases. Therefore, the confidence in the answer is an example of a level of understanding. The confidence in the answer is the confidence in one answer selected by the user via the terminal from multiple levels of confidence in the answer. Here, an example will be described in which the multiple levels of confidence in the answer are three levels: "not confident," "average," and "confident," but the multiple levels may be two levels or four or more levels. The confidence in the answer increases in the order of "not confident," "average," and "confident."

[0096] The plurality of second options includes a plurality of options indicating a plurality of levels of understanding. The plurality of second options includes a plurality of options indicating a plurality of levels of confidence in an answer as a plurality of options indicating a plurality of levels of understanding.

[0097] The storage device 14 includes a user data storage area 142. The user data storage area 142 stores user data for each user, similar to the first embodiment. The storage device 14 includes a relationship data storage area 143. As in the first embodiment, the relationship data storage area 143 stores relationship data for at least one accuracy rate.

[0098] The communication unit 111 communicates with the terminal 2 via the network NW, as in the first embodiment. In addition to the communication processing described in the first embodiment, the communication unit 111 outputs a plurality of second options to the terminal 2 via the network NW. The communication unit 111 acquires first additional information input via the terminal 2 from the terminal 2 via the network NW.

[0099] The answer processing unit 112 judges whether the answer to the question input via the terminal 2 is correct or incorrect, as in the first embodiment.

[0100] The acquisition unit 113 acquires the target user's level of understanding of the question. For example, the acquisition unit 113 acquires the target user's level of understanding of the question based on the answer to the question and the first additional information input via the terminal 2. In this example, the acquisition unit 113 acquires the target user's level of understanding of the question according to a combination of the correctness or incorrectness of the answer to the question and the first additional information.

[0101] The target user's level of understanding of the question acquired by the acquisition unit 113 varies depending on whether the answer to the question is correct or incorrect, regardless of the first additional information. Therefore, acquiring the target user's level of understanding of the question depending on a combination of the correctness of the answer to the question and the first additional information includes acquiring the target user's level of understanding of the question depending on whether the answer to the question is correct or incorrect. The acquisition unit 113 increases the target user's level of understanding of the question when the answer to the question is correct. The acquisition unit 113 decreases the target user's level of understanding of the question when the answer to the question is incorrect.

[0102] The target user's level of understanding of the question acquired by the acquisition unit 113 varies depending on the first additional information when the answer to the question is correct. The target user's level of understanding of the question acquired by the acquisition unit 113 may vary depending on the first additional information when the answer to the question is incorrect. Therefore, acquiring the target user's level of understanding of the question depending on a combination of the correctness of the answer to the question and the first additional information includes acquiring the target user's level of understanding of the question depending on the first additional information. The acquisition unit 113 acquires the target user's level of understanding of the target question depending on the first additional information, based on the answer to the question being correct. The acquisition unit 113 may change the amount of increase in the target user's level of understanding of the question depending on the first additional information, based on the answer to the question being correct. The acquisition unit 113 may significantly increase the target user's level of understanding of the question as the level of understanding indicated by the first additional information increases, based on the answer to the question being correct. This is because the user's actual understanding of the question tends to increase as the level of understanding indicated by the first additional information increases. The acquiring unit 113 may change the amount of decrease in the target user's level of understanding of the question according to the first additional information, based on whether the answer to the question is incorrect.

[0103] Acquiring the user's level of understanding for the question is an example of an understanding level acquisition process by the acquisition unit 113. Acquiring the user's level of understanding for the question includes updating the user's level of understanding for the question. The understanding level acquisition process includes understanding level update processing.

[0104] The acquisition unit 113 may acquire the target user's level of understanding of the question based on a set value. The set value is a value corresponding to a combination of the correctness of the answer and the first additional information. The value corresponding to the combination of the correctness of the answer and the first additional information can also be said to be a value corresponding to a combination of the correctness of the answer and the degree of understanding indicated by the first additional information. The set value is a value set to update the level of understanding at the time of the understanding acquisition process. The time of the understanding acquisition process includes before the understanding acquisition process. For example, the set value is a value to be added to the level of understanding at the time of the understanding acquisition process.

[0105] When the set value is a positive value, the set value is a value that increases the level of understanding. When the set value is a negative value, the set value is a value that decreases the level of understanding. When the answer is correct, the set value is a positive value. This is because when the answer is correct, the user remembers the correct answer to the question and the user's actual understanding of the question tends to be high. Typically, when the answer is correct, the set value is a different positive value depending on the first additional information. The positive set value becomes larger as the level of understanding indicated by the first additional information increases. This is because the user's actual understanding of the question tends to increase as the level of understanding indicated by the first additional information increases.

[0106] If the answer is incorrect, the set value is a negative value. This is because if the answer is incorrect, the user does not remember the correct answer to the question and the user's actual understanding of the question tends to be low. If the answer is incorrect, the set value may be the same negative value regardless of the level of understanding indicated in the first additional information. If the answer is incorrect, the set value may be the same negative value regardless of the level of understanding indicated in the first additional information. If the answer is incorrect, the set value may be a different negative value depending on the level of understanding indicated in the first additional information.

[0107] The setting value may be set commonly for multiple questions for multiple users. The setting value may be set for each user. The setting value may be set for each question. The setting value may be set according to a course, subject, unit, etc. The setting value can be set as appropriate.

[0108] If the answer to the question is correct, the acquisition unit 113 may increase the level of understanding after the update process by adding a positive setting value corresponding to the first additional information to the level of understanding at the time of the update process of the level of understanding.If the answer to the question is incorrect, the acquisition unit 113 may decrease the level of understanding after the update process by adding the same negative setting value regardless of the first additional information to the level of understanding at the time of the update process of the level of understanding.If the answer to the question is incorrect, the acquisition unit 113 may decrease the level of understanding after the update process by adding a negative setting value corresponding to the first additional information to the level of understanding at the time of the update process of the level of understanding.

[0109] As in the first embodiment, the setting unit 114 sets the question presentation interval based on the target user's level of understanding of the questions acquired by the acquisition unit 113. As in the first embodiment, the setting unit 114 sets the question presentation timing based on the set question presentation interval.

[0110] As in the first embodiment, the relationship data processing unit 115 generates relationship data by machine learning based on a plurality of answer histories to one or more questions.

[0111] In addition, since the first additional information includes the first input additional information, the expressions "first additional information" and "degree of understanding" in the description of the configuration example of the communication unit 111 and the description of the configuration example of the acquisition unit 113 may be read as "first input additional information" and "degree of confidence in the answer," respectively.

[0112] Examples of setting values ​​will be described below. FIG. 8 is a diagram illustrating an example of setting values. If the answer is correct, the set value is a positive value, and increases as the confidence level of the answer indicated in the first additional input information increases. If the answer is correct and the confidence level of the answer indicated in the first additional input information is "not confident," the set value is "+5%." If the answer is correct and the confidence level of the answer indicated in the first additional input information is "average," the set value is "+20%." If the answer is correct and the confidence level of the answer indicated in the first additional input information is "confident," the set value is "+40%." If the answer is incorrect, the set value is a negative value, and remains the same "-50%" regardless of the confidence level of the answer indicated in the first additional input information. Note that these values ​​are merely examples, and the values ​​are not limited to these.

[0113] An example of displaying a plurality of second options on terminal 2 will be described. FIG. 9 is a diagram showing an example of displaying a plurality of second options. Terminal 2 displays a plurality of second options on display device 27 along with a question statement and a plurality of first options. Terminal 2 displays a plurality of second options on display device 27 before displaying the correct answer to the question on display device 27. The plurality of first options are input keys such as buttons that can select one option. The plurality of second options are input keys such as buttons that can select one option.

[0114] (Example of operation) Next, an example of the operation of the server 1 configured as above will be described. The processing procedures described below are merely examples, and each process may be modified as much as possible. Furthermore, steps may be omitted, replaced, or added as appropriate depending on the embodiment.

[0115] Fig. 10 is a flowchart showing an example of a question setting process executed by the server 1. The server 1 executes the question setting process illustrated in Fig. 10 every time it outputs a question to the terminal 2 via the network NW. The question may be a new question or a review question. Hereinafter, a question that is the target of the question setting process is also referred to as a target question. A target question is an example of a question.

[0116] The communication unit 111 outputs the target question to the terminal 2 via the network NW (step S21). Based on the acquisition of the target question output from the server 1, the terminal 2 displays the target question on the display device 27. For example, the terminal 2 displays a question statement and a plurality of first options on the display device 27.

[0117] The communication unit 111 outputs the plurality of second options to the terminal 2 via the network NW (step S22). The communication unit 111 may output the plurality of second options to the terminal 2 together with the question, or may output the plurality of second options to the terminal 2 separately from the question. The terminal 2 displays the plurality of second options on the display device 27 based on acquisition of the plurality of second options output from the server 1. The terminal 2 may display the plurality of second options on the display device 27 together with the question. For example, the terminal 2 displays the plurality of second options on the display device 27 together with the question statement and the plurality of first options. The terminal 2 may display the plurality of second options on the display device 27 on a page separate from the page on which the question is displayed.

[0118] The communication unit 111 acquires, via the network NW, from the terminal 2 an answer to the target question input via the terminal 2 (step S23). For example, the answer to the target question includes one option selected by the target user from a plurality of first options via the input device 26 of the terminal 2.

[0119] The communication unit 111 acquires the first additional input information input via the terminal 2 from the terminal 2 via the network NW (step S24). For example, the first additional input information includes information indicating the degree of confidence in an answer corresponding to one option selected from a plurality of second options by the target user via the input device 26 of the terminal 2. The communication unit 111 may acquire the first additional input information from the terminal 2 together with the answer to the target question, or may acquire the first additional input information from the terminal 2 separately from the answer to the target question.

[0120] The answer processing unit 112 judges whether the answer to the target question input via the terminal 2 is correct or incorrect (step S25). The process of step S25 may be the same as the process of step S3, and a description thereof will be omitted.

[0121] The communication unit 111 outputs the correct answer to the target question to the terminal 2 via the network NW (step S26). Based on the acquisition of the correct answer to the target question output from the server 1, the terminal 2 displays the correct answer to the target question on the display device 27. After the target user inputs first additional input information via the input device 26 of the terminal 2, the terminal 2 displays the correct answer to the target question on the display device 27. For example, the terminal 2 displays the correct answer option from among the multiple first options and an explanation of the target question on the display device 27.

[0122] The acquisition unit 113 acquires the target user's level of understanding of the target question based on the answer to the target question and the first input additional information input via the terminal 2 (step S27). In step S27, the acquisition unit 113 acquires the target user's level of understanding of the question based on a combination of the correctness or incorrectness of the answer to the question and the first input additional information. The acquisition unit 113 may acquire the target user's level of understanding of the question based on a set value corresponding to the combination of the correctness or incorrectness of the answer and the first input additional information. The acquisition unit 113 stores the acquired level of understanding of the target user for the target question in the user data storage area 142 in association with the target question.

[0123] The setting unit 114 sets the interval between the presentation of the target questions based on the target user's level of understanding of the target questions acquired by the acquisition unit 113 (step S28). The process of step S28 may be the same as the process of step S6, and the description thereof will be omitted.

[0124] The setting unit 114 sets the timing for presenting the target question based on the set question interval (step S29). The process of step S29 may be the same as the process of step S7, and a description thereof will be omitted.

[0125] (effect) The information processing device includes a communication unit that outputs questions to a terminal, an acquisition unit that acquires a user's level of understanding of questions based on answers to the questions and additional information for the questions input via the terminal, and a setting unit that sets an interval at which questions are presented to the user based on the user's level of understanding.

[0126] By using not only the answers but also the additional information, the information processing device acquires the user's level of understanding based on multifaceted information, thereby improving the accuracy of acquiring the user's level of understanding. This allows the information processing device to optimize the setting of question intervals based on the user's level of understanding, thereby supporting effective review of questions.

[0127] In the information processing device, an acquisition unit acquires the user's level of understanding of a question based on a combination of whether the answer is correct or incorrect and additional information for the question. For example, even if the answer entered by the user is correct, the information processing device can adjust the user's level of understanding by adding additional information. This allows the information processing device to obtain a level of understanding that is closer to the user's actual understanding, thereby optimizing the setting of the question interval based on the user's level of understanding.

[0128] In the information processing device, the additional information for the question includes additional information input via a terminal. By having the user input additional information, the information processing device can acquire additional information that contributes to improving the accuracy of acquiring the user's understanding without imposing a processing load on the user to acquire the additional information.

[0129] In the information processing device, the additional information input via the terminal includes additional information input before the correct answer to the question is displayed on the terminal. The information processing device can input the sensation when entering an answer as additional information, thereby acquiring additional information that contributes to improving the accuracy of acquiring the user's level of understanding. This allows the information processing device to acquire a level of understanding that is closer to the user's actual understanding, thereby optimizing the setting of the question interval based on the user's level of understanding.

[0130] [Third embodiment] The third embodiment is an embodiment in which a user's understanding of a question is acquired based on the answer to the question and second input additional information included in the first additional information for the question. In the third embodiment, the same components as those in the first or second embodiment are denoted by the same reference numerals, and their description will be omitted. In the third embodiment, the parts that are different from the first or second embodiment will mainly be described.

[0131] (Configuration example) The configuration of the server 1 is the same as the configuration example described in the first embodiment using FIG. 1. The storage device 14 includes a lesson data storage area 141. As in the first embodiment, the lesson data storage area 141 stores content data of input lessons related to each unit for each exam course. As in the first embodiment, the lesson data storage area 141 stores content data of output lessons related to each unit for each exam course. In addition to the data described in the first embodiment, the content data of the output lessons includes data of multiple second options for inputting the first additional information described in the second embodiment.

[0132] The first additional information includes second input additional information input after the display of the correct answer to the question on the terminal. The second input additional information includes information indicating the ease of the question for the user, as information indicating the user's level of understanding of the question. The ease of a question is the degree of ease of the question based on the user's subjective opinion. The ease of a question tends to increase as the user's understanding of the question increases. Therefore, the ease of a question is an example of the level of understanding. The ease of a question is the ease of one question selected by the user from multiple levels of question ease via the terminal. Here, an example will be described in which the multiple levels of question ease are three levels: "difficult," "normal," and "easy," but the multiple levels may be two levels, or four or more levels. The ease of a question increases in the order of "difficult," "normal," and "easy."

[0133] The second options include options indicating multiple levels of understanding. The second options include options indicating multiple levels of difficulty of the question as options indicating multiple levels of understanding.

[0134] The storage device 14 includes a user data storage area 142. The user data storage area 142 stores user data for each user, similar to the first embodiment. The storage device 14 includes a relationship data storage area 143. As in the first embodiment, the relationship data storage area 143 stores relationship data for at least one accuracy rate.

[0135] The communication unit 111 communicates with the terminal 2 via the network NW, similar to the first embodiment. In addition to the communication processing described in the first embodiment, the communication unit 111 outputs a plurality of second options to the terminal 2 via the network NW, similar to the second embodiment. The communication unit 111 acquires first additional information input via the terminal 2 from the terminal 2 via the network NW, similar to the second embodiment.

[0136] The answer processing unit 112 judges whether the answer to the question input via the terminal 2 is correct or incorrect, as in the first embodiment.

[0137] The acquisition unit 113 acquires the target user's level of understanding of the question. For example, similar to the second embodiment, the acquisition unit 113 acquires the target user's level of understanding of the question based on the answer to the question and the first additional information input via the terminal 2.

[0138] As in the first embodiment, the setting unit 114 sets the question presentation interval based on the target user's level of understanding of the questions acquired by the acquisition unit 113. As in the first embodiment, the setting unit 114 sets the question presentation timing based on the set question presentation interval.

[0139] As in the first embodiment, the relationship data processing unit 115 generates relationship data by machine learning based on a plurality of answer histories to one or more questions.

[0140] Since the first additional information includes the second input additional information, the notation "first additional information" in the description of the configuration example of the communication unit 111 may be read as "second input additional information." The notations "first additional information" and "degree of understanding" in the description of the configuration example of the acquisition unit 113 of the second embodiment may be read as "second input additional information" and "ease of question," respectively.

[0141] Examples of setting values ​​will be described below. FIG. 11 is a diagram illustrating an example of setting values. If the answer is correct, the set value is a positive value, and increases as the ease of the question indicated in the second additional input information increases. If the answer is correct and the ease of the question indicated in the second additional input information is "difficult," the set value is "+5%." If the answer is correct and the ease of the question indicated in the second additional input information is "normal," the set value is "+20%." If the answer is correct and the ease of the question indicated in the second additional input information is "easy," the set value is "+50%." If the answer is incorrect, the set value is a negative value, and remains the same "-50%" regardless of the ease of the question indicated in the second additional input information. Note that these values ​​are examples and are not limited to these.

[0142] An example of displaying a plurality of second options on terminal 2 will be described. FIG. 12 is a diagram showing an example of displaying a plurality of second options. Terminal 2 displays a plurality of second options on display device 27 together with the correct answer and an explanation of the question. After displaying the correct answer to the question on display device 27, terminal 2 displays a plurality of second options on display device 27 for inputting second additional input information. The plurality of second options are input keys such as buttons that can select one option. The plurality of second options may also serve as input keys for transitioning to the next question.

[0143] (Example of operation) Next, an example of the operation of the server 1 configured as above will be described. The processing procedures described below are merely examples, and each process may be modified as much as possible. Furthermore, steps may be omitted, replaced, or added as appropriate depending on the embodiment.

[0144] Fig. 13 is a flowchart showing an example of a question setting process executed by the server 1. The server 1 executes the question setting process illustrated in Fig. 13 every time it outputs a question to the terminal 2 via the network NW. The question may be a new question or a review question. Hereinafter, a question that is the target of the question setting process is also referred to as a target question. A target question is an example of a question.

[0145] The communication unit 111 outputs the target question to the terminal 2 via the network NW (step S31). Based on the acquisition of the target question output from the server 1, the terminal 2 displays the target question on the display device 27. For example, the terminal 2 displays a question statement and a plurality of first options on the display device 27.

[0146] The communication unit 111 acquires, via the network NW, from the terminal 2 an answer to the target question input via the terminal 2 (step S32). For example, the answer to the target question includes one option selected by the target user from a plurality of first options via the input device 26 of the terminal 2.

[0147] The answer processing unit 112 determines whether the answer to the target question input via the terminal 2 is correct or incorrect (step S33). The process of step S33 may be the same as the process of step S3, and a description thereof will be omitted.

[0148] The communication unit 111 outputs the correct answer to the target question to the terminal 2 via the network NW (step S34). Based on the acquisition of the correct answer to the target question output from the server 1, the terminal 2 displays the correct answer to the target question on the display device 27. For example, the terminal 2 displays the correct answer option from among the multiple first options and an explanation of the target question on the display device 27.

[0149] The communication unit 111 outputs the plurality of second options to the terminal 2 via the network NW (step S35). The communication unit 111 may output the plurality of second options to the terminal 2 together with the correct answer to the target question, or may output the plurality of second options to the terminal 2 separately from the correct answer to the target question. The terminal 2 displays the plurality of second options on the display device 27 based on acquisition of the plurality of second options output from the server 1. The terminal 2 may display the plurality of second options on the display device 27 together with the correct answer to the target question. For example, the terminal 2 displays the plurality of second options on the display device 27 together with a correct answer option from among the plurality of first options and an explanation of the target question. The terminal 2 may display the plurality of second options on the display device 27 after displaying the correct answer to the target question, on a page separate from the page on which the correct answer to the target question is displayed.

[0150] The communication unit 111 acquires the second additional input information input via the terminal 2 from the terminal 2 via the network NW (step S36). For example, the second additional input information includes information indicating the ease of the question corresponding to one option selected from the plurality of second options by the target user via the input device 26 of the terminal 2 after the correct answer to the target question is displayed on the terminal 2.

[0151] The acquisition unit 113 acquires the target user's level of understanding of the target question based on the answer to the target question and the second input additional information input via the terminal 2 (step S37). In step S37, the acquisition unit 113 acquires the target user's level of understanding of the question based on a combination of the correctness or incorrectness of the answer to the question and the second input additional information. The acquisition unit 113 may acquire the target user's level of understanding of the question based on a set value corresponding to the combination of the correctness or incorrectness of the answer and the second input additional information. The acquisition unit 113 stores the acquired level of understanding of the target user for the target question in the user data storage area 142 in association with the target question.

[0152] The setting unit 114 sets the interval between the presentation of the target questions based on the target user's level of understanding of the target questions acquired by the acquisition unit 113 (step S38). The process of step S38 may be the same as the process of step S6, and the description thereof will be omitted.

[0153] The setting unit 114 sets the timing for presenting the target question based on the set question interval (step S39). The process of step S39 may be the same as the process of step S7, and a description thereof will be omitted.

[0154] (effect) In the information processing device, the additional information input via the terminal includes additional information input after the correct answer to the question is displayed on the terminal. The information processing device can prompt the user to input additional information after showing the correct answer, thereby acquiring additional information that contributes to improving the accuracy of acquiring the user's level of understanding. For example, the user can input appropriate additional information by looking at the explanation and understanding their own level of understanding. This allows the information processing device to acquire a level of understanding that is closer to the user's actual understanding, thereby optimizing the setting of the question interval based on the user's level of understanding.

[0155] [Fourth embodiment] The fourth embodiment is an embodiment in which the user's understanding of a question is acquired based on the answer to the question and second additional information included in the additional information. In the fourth embodiment, the same components as those in the first, second, or third embodiment are denoted by the same reference numerals, and the description thereof will be omitted. In the fourth embodiment, the differences from the first, second, or third embodiment will be mainly described.

[0156] (Configuration example) FIG. 14 is a block diagram showing an example of the configuration of the server 1. The storage device 14 includes a lesson data storage area 141. As in the first embodiment, the lesson data storage area 141 stores content data of input lessons related to each unit for each exam course. As in the first embodiment, the lesson data storage area 141 stores content data of output lessons related to each unit for each exam course.

[0157] The storage device 14 includes a user data storage area 142. The user data storage area 142 stores user data for each user. As in the first embodiment, the user data includes the user's level of understanding related to each question, the question interval, the question timing, and one or more answer histories. The answer history may include the answer time in addition to the level of understanding and the correctness of the answer at the question interval and question timing described in the first embodiment. The answer time is the time required for the user to input the answer to the question via the terminal. For example, the answer time is the time from when the terminal displays the question based on the acquisition of the question output from the server 1 to when the user inputs the answer to the question via the terminal. The answer time included in the answer history is the time taken by the user to answer the question set based on the question timing. The answer time can be acquired based on data related to the answer time, which will be described later. The answer history may also include data related to the process of inputting the answer to the question. Hereinafter, data related to the process of inputting the answer to the question will also be referred to as input process data. The input process data included in the answer history is data related to the process of inputting answers to questions posed based on the question timing. The input process is the process by which a user inputs an answer to a question via a terminal. For example, the input process is the period from when a question is displayed on a terminal to when the answer is input via the terminal. The input process data is data acquired by an electronic device. The input process data is data that reflects the user's hesitation during the input process.

[0158] In a first aspect, the input process data about the user is data about the time it takes the user to answer a question. The data about the answer time may be data indicating the answer time or data indicating the time the answer was input. Since the answer time varies depending on the user's hesitation, the data about the answer time is data that reflects the user's hesitation during the input process. In this example, the electronic device is a terminal.

[0159] In a second aspect, the input process data about the user includes data on options related to the display of markers for narrowing down answers to a question. Options related to the display of markers are options that the user marked when narrowing down answers before selecting an answer option. The markers include markers attached to candidate answer options (described below) that the user wants to keep as answer candidates. The markers include markers attached to excluded options (described below) that the user does not want to keep as answer candidates. The markers may be identifiable objects such as characters or symbols, or may be identifiable colors. For example, options related to the display of markers include at least one of options related to the display of markers indicating excluded options for the question and options related to the display of markers indicating candidate answer options for the question. Hereinafter, options related to the display of markers indicating excluded options for the question are also referred to as excluded options. Options related to the display of markers indicating candidate answer options for the question are also referred to as candidate answer options.

[0160] An excluded option is an option that is removed from the plurality of first options as an option that will not be an answer option. A user can select an option that will not be an answer option from the plurality of first options as an excluded option via the terminal. The terminal displays a distinguishable marker for the excluded option. The terminal may display a cross mark as a marker associated with the excluded option. A candidate answer option is an option selected from the plurality of first options as an option that will be an answer candidate. A user can select an option that will be an answer candidate from the plurality of first options as an answer candidate option via the terminal. The terminal displays a distinguishable marker for the candidate answer option. The terminal may display a triangle mark as a marker associated with the candidate answer option.

[0161] The data of options related to the display of landmarks includes data indicating the presence or absence of options related to the display of landmarks. The data of options related to the display of landmarks includes data indicating one or more options related to the display of landmarks selected by a user from a plurality of first options via a terminal. For example, the data indicating options related to the display of one or more landmarks includes at least one of data of excluded options and data of candidate answer options. The data of excluded options includes data indicating one or more excluded options selected by a user from a plurality of first options via a terminal. The data of candidate answer options includes data indicating one or more candidate answer options selected by a user from a plurality of first options via a terminal.

[0162] By selecting an option associated with the display of one or more landmarks, the user can narrow down the number of candidate answer options and select an answer option. For example, when selecting one or more candidate answer options, the user can select an answer option from one or more candidate answer options. When selecting one or more excluded options without selecting any candidate answer options, the user can select an answer option from one or more options remaining after excluding one or more excluded options from the plurality of first options. The selection of an option associated with the display of one or more landmarks is a selection made during the process of inputting an answer to a question. Because the selection of an option associated with the display of one or more landmarks changes depending on the user's hesitation, the data of the option associated with the display of one or more landmarks is data that reflects the user's hesitation during the input process. In this example, the electronic device is a terminal.

[0163] In a third aspect, the input process data about the user includes sensing data of the user in the process of the user inputting an answer to a question via a terminal. The sensing data of the user in the process of inputting an answer to a question is data acquired in the process of inputting an answer to a question. The sensing data of the user may include photographed data of the user acquired by the terminal. The sensing data of the user may include pointer trajectory data acquired by the terminal over time. The pointer trajectory data is data indicating the trajectory of a pointer that moves based on input by the user via an input device such as a mouse. In this example, the electronic device is a terminal. The sensing data of the user may include photographed data of the user acquired by a photographing device different from the terminal. In this example, the electronic device is a photographing device. The photographing device is an example of a sensing device. The sensing data of the user may include biological movement data of at least one of the user's eyes, hands, body, etc. over time acquired by a wearable device. In this example, the electronic device is a wearable device. The wearable device is an example of a sensing device. The user's sensing data may include vital data of the user acquired over time by a wearable device. The vital data may include at least one of blood pressure data, pulse data, and body temperature data, or may include other data obtainable from a living body. In this example, the electronic device is a wearable device. The items indicated by the user's sensing data change depending on the user's hesitation, so the user's sensing data is data that reflects the user's hesitation during the input process.

[0164] The storage device 14 includes a relationship data storage area 143. As in the first embodiment, the relationship data storage area 143 stores relationship data for at least one accuracy rate.

[0165] The storage device 14 includes an additional information prediction model storage area 144. The additional information prediction model storage area 144 stores additional information prediction models. The additional information prediction model is a trained model generated by the additional information prediction model processing unit 117 based on training data. The term "generated" includes not only a newly created model but also an updated model. The training data includes multiple pieces of sensing data and multiple pieces of data related to the level of understanding of one or more users. The user's sensing data and the data related to the level of understanding are associated with each other. The additional information prediction model may be generated commonly for multiple users. The additional information prediction model may be generated for each user. The additional information prediction model may be generated for each question. The additional information prediction model outputs second additional information about the user based on the input of the user's sensing data.

[0166] The second additional information is additional information based on input process data about the user. The second additional information is information automatically acquired by the server 1 based on the input process data about the user. Because the second additional information is automatically acquired by the server 1, it is information indicating the user's degree of understanding of the problem that is not dependent on the user's subjectivity. The user's degree of understanding of the problem indicated by the second additional information is one level of understanding acquired based on the input process data about the user. The user's level of understanding of the problem indicated by the second additional information may be one level of understanding selected from multiple levels of understanding based on the input process data about the user.

[0167] The user's degree of understanding of the question includes the user's confidence in the answer to the question. The confidence in the answer is the degree of confidence in the answer, which is automatically obtained by the server 1 based on the input process data about the user and does not depend on the user's subjectivity. Confidence in the answer to the question tends to increase as understanding of the question increases. Therefore, the confidence in the answer is an example of the degree of understanding. The user's degree of understanding of the question includes the ease of the question for the user. The ease of the question is the degree of ease of the question, which is automatically obtained by the server 1 based on the input process data about the user and does not depend on the user's subjectivity. The ease of the question tends to increase as understanding of the question increases. Therefore, the ease of the question is an example of the degree of understanding. There is a correlation between the confidence in the answer and the ease of the question. In the following explanation, the term "degree of understanding" may be read as "confidence in the answer" or "ease of the question."

[0168] The communication unit 111 communicates with the terminal 2 via the network NW, as in the first embodiment. In addition to the communication processing described in the first embodiment, the communication unit 111 acquires input process data about the target user from the electronic device. In a first aspect, the communication unit 111 acquires data about the answer time of the target user to a question from the electronic device. In a second aspect, the communication unit 111 acquires data about excluded options for a question from the electronic device. In a third aspect, the communication unit 111 acquires sensing data about the target user in the process of inputting an answer to a question from the electronic device.

[0169] The answer processing unit 112 judges whether the answer to the question input via the terminal 2 is correct or incorrect, as in the first embodiment.

[0170] The acquisition unit 113 acquires the target user's level of understanding of the question. For example, the acquisition unit 113 acquires the target user's level of understanding of the question based on the answer to the question and the second additional information input via the terminal 2. The expression "first additional information" in the description of the configuration example of the acquisition unit 113 of the second embodiment may be read as "second additional information."

[0171] As in the first embodiment, the setting unit 114 sets the question presentation interval based on the target user's level of understanding of the questions acquired by the acquisition unit 113. As in the first embodiment, the setting unit 114 sets the question presentation timing based on the set question presentation interval.

[0172] As in the first embodiment, the relationship data processing unit 115 generates relationship data by machine learning based on a plurality of answer histories to one or more questions.

[0173] The additional information processing unit 116 acquires second additional information about the target user based on the input process data about the target user. In a first aspect, the additional information processing unit 116 acquires second additional information about the target user based on data related to the time the target user took to answer the question. In this example, the additional information processing unit 116 acquires the time the target user took to answer the question based on the data related to the answer time. If the data related to the answer time indicates the answer time, the additional information processing unit 116 acquires the answer time indicated by the data related to the answer time. If the data related to the answer time indicates the time the answer was input, the additional information processing unit 116 may acquire the time from the time the question was output from the server 1 to the terminal 2 to the time the answer was input as the answer time. The additional information processing unit 116 acquires second additional information about the target user based on the answer time. For example, the additional information processing unit 116 acquires second additional information indicating the target user's level of understanding of the question according to the answer time, based on the relationship between the length of the answer time and the level of understanding of the question. The target user's level of understanding of the question indicated by the second additional information increases as the answer time decreases. This is because as your understanding of the problem increases, you tend to be less confused and take less time to answer the problem.

[0174] The relationship between the length of answer time and the level of understanding of the question may be set arbitrarily. In this example, the relationship between the length of answer time and the level of understanding of the question may be set commonly for each question, or may be set for each question.

[0175] The relationship between the length of answer time and the level of understanding of the question may be set for each question based on the multiple answer times of multiple users. In this example, the additional information processing unit 116 may acquire the multiple answer times of multiple users for each question from the answer histories stored in the user data storage area 142. The additional information processing unit 116 may set the relationship between the length of answer time and the level of understanding of the question according to an index such as the median, mean, or standard deviation based on the distribution of the multiple answer times of multiple users for each question. Because the distribution of the multiple answer times of multiple users differs for each question, the level of understanding of the question varies depending on the question, even if the answer time is the same. The additional information processing unit 116 can acquire second additional information indicating the target user's relative level of understanding of the question, taking into account the understanding of the multiple users of the question, based on the target user's answer time for each question. Since the additional information processing unit 116 acquires the second additional information based on the distribution of the multiple answer times of multiple users for each question, the accuracy of acquiring the second additional information can be improved.

[0176] The relationship between the length of the answer time and the level of understanding of the question may be set for each question based on a reference answer time for each question corresponding to an arbitrary correct answer rate. The correct answer rate is the probability that the answer to the question is correct. The level of understanding may increase as the target user's answer time for the question becomes shorter than the reference answer time for that question. The level of understanding may decrease as the target user's answer time for the question becomes longer than the reference answer time for that question. In this example, the additional information processing unit 116 may acquire multiple answer times and correct answers of multiple answers for multiple users for each question from the answer history stored in the user data storage area 142. The multiple answer times and correct answers of multiple answers are associated with each other. The additional information processing unit 116 may generate an answer time prediction model for each question by machine learning based on the multiple answer times and correct answers of multiple users for each question. The answer time prediction model outputs the answer time for the question based on an input of the correct answer rate for the question. For example, the additional information processing unit 116 uses machine learning to estimate the relationship between the correct answer rate and the answer time for a question. Because the correct answer rate is calculated based on the correct answers of multiple answers, there is a certain correlation between the correct answer rate and the correct answers of multiple answers. The correct answer rate for a question may increase as the answer time for the question shortens. This is because the correct answer rate for a question increases as the user's understanding of the question improves, and as the user's understanding of the question improves, the user may become less hesitant and the answer time may shorten. Therefore, there is a certain correlation between the correct answer rate for a question and the answer time for the question. The additional information processing unit 116 generates an answer time prediction model based on the estimation. Machine learning may be, but is not limited to, a neural network. The additional information processing unit 116 acquires a reference answer time for each question corresponding to a given correct answer rate based on the given answer time and the answer time prediction model for each question. The additional information processing unit 116 acquires second additional information indicating the target user's level of understanding of the question based on a comparison between the target user's answer time for the question and the reference answer time for that question. The standard answer time varies for each question, so the level of understanding of the question varies depending on the question, even if the answer time is the same.The additional information processing unit 116 can acquire second additional information indicating the relative level of understanding of the target user for the problem, taking into consideration the understanding of the problem of multiple users, based on the answer time of the target user for the problem. Since the additional information processing unit 116 acquires the second additional information based on data acquired based on the answer time prediction model, it is possible to improve the accuracy of acquiring the second additional information.

[0177] In a second aspect, the additional information processing unit 116 acquires second additional information about the target user based on data of options associated with the display of a landmark. In this example, the additional information processing unit 116 acquires second additional information indicating the target user's level of understanding of the problem according to data of options associated with the display of a landmark, based on a relationship between the data of options associated with the display of a landmark and the level of understanding of the problem. The relationship between the data of options associated with the display of a landmark and the level of understanding of the problem includes a relationship between data indicating the presence or absence of options associated with the display of a landmark and the level of understanding of the problem. The target user's level of understanding of the problem indicated by the second additional information may be higher when there are no options associated with the display of a landmark than when there are options associated with the display of a landmark. This is because as understanding of the problem increases, the user becomes less hesitant and tends not to select an option associated with the display of a landmark. The relationship between the data of options associated with the display of a landmark and the level of understanding of the problem includes a relationship between data indicating options associated with the display of one or more landmarks and the level of understanding of the problem. The relationship between the data indicating options associated with the display of one or more markers and the degree of understanding of the problem may include a relationship between data on excluded options and the degree of understanding of the problem. The relationship between the data indicating options associated with the display of one or more markers and the degree of understanding of the problem may include a relationship between data on candidate answer options and the degree of understanding of the problem. The target user's level of understanding of the problem indicated by the second additional information may increase as the number of options associated with the display of markers decreases, regardless of whether they are excluded options or candidate answer options. This is because as understanding of the problem increases, users become less hesitant and tend not to select options associated with the display of markers.

[0178] The relationship between the data of options associated with the display of markers and the degree of understanding of the question may be set arbitrarily. The relationship between the data of options associated with the display of markers and the degree of understanding of the question may be set according to a combination of whether or not options are associated with the display of markers and the number of options associated with the display of one or more markers. In a typical example, the relationship between the data of options associated with the display of markers and the degree of understanding of the question may be set according to a combination of whether or not options are associated with the display of markers, the number of one or more exclusion options, and the number of one or more candidate answer options. In this example, the relationship between the data of options associated with the display of markers and the degree of understanding of the question may be set commonly for each question or may be set for each question.

[0179] The relationship between the option data related to the display of landmarks and the degree of understanding of the question may be a predictive model related to the option data. The predictive model related to the option data outputs second additional information based on input of option data related to the display of landmarks. In this example, the additional information processing unit 116 acquires second additional information about the target user based on the option data related to the display of landmarks and the predictive model related to the option data. The additional information processing unit 116 inputs option data related to the display of landmarks of the target user into the predictive model related to the option data. The additional information processing unit 116 acquires second additional information about the target user from the predictive model related to the option data based on input of option data related to the display of landmarks of the target user into the predictive model related to the option data. The second additional information about the target user indicates the degree of understanding of the question by the target user based on the option data related to the display of landmarks of the target user. The additional information processing unit 116 may generate the predictive model related to the option data, as exemplified below. The additional information processing unit 116 may acquire option data related to the display of multiple landmarks of multiple users for each question and the correctness or incorrectness of multiple answers from the storage device 14. Data on options associated with the display of landmarks may be included in the answer history. Data on options associated with the display of multiple landmarks and the correctness or incorrectness of multiple answers are associated with each other. The additional information processing unit 116 may generate a predictive model for the data on options for each question through machine learning based on the data on options associated with the display of multiple landmarks for each question and the correctness or incorrectness of multiple answers. The correctness or incorrectness of the multiple answers may become data on multiple levels of understanding. If an answer is correct, the level of understanding may be set to high. If an answer is incorrect, the level of understanding may be set to low. For example, the additional information processing unit 116 estimates, through machine learning, the relationship between the data on options associated with the display of landmarks and the level of understanding indicated by the data on the level of understanding. Selection of options associated with the display of landmarks varies depending on the level of understanding. As understanding of the question increases, the user may become less hesitant to select options associated with the display of landmarks and may be less likely to select them. Therefore, there is a certain correlation between the data on options associated with the display of landmarks and the level of understanding.The additional information processing unit 116 generates a prediction model for the option data based on the estimation. The additional information processing unit 116 may store the prediction model for the option data in the storage device 14. The machine learning may be, but is not limited to, a neural network or the like. Since the additional information processing unit 116 acquires the second additional information based on the prediction model for the option data, the accuracy of acquiring the second additional information can be improved.

[0180] In a third aspect, the additional information processing unit 116 acquires second additional information about the target user based on the target user's sensing data for the problem. In this example, the additional information processing unit 116 acquires the second additional information about the target user based on the target user's sensing data and the additional information prediction model. The additional information processing unit 116 inputs the target user's sensing data to the additional information prediction model. The additional information processing unit 116 acquires the second additional information about the target user from the additional information prediction model based on the target user's sensing data input to the additional information prediction model. The second additional information about the target user indicates the target user's degree of understanding of the problem based on the target user's sensing data.

[0181] The additional information prediction model processing unit 117 generates an additional information prediction model by machine learning.

[0182] (Example of operation) Next, an example of the operation of the server 1 configured as above will be described. The processing procedures described below are merely examples, and each process may be modified as much as possible. Furthermore, steps may be omitted, replaced, or added as appropriate depending on the embodiment.

[0183] Fig. 15 is a flowchart showing an example of a question setting process executed by the server 1. The server 1 executes the question setting process illustrated in Fig. 15 every time it outputs a question to the terminal 2 via the network NW. The question may be a new question or a review question. Hereinafter, a question that is the target of the question setting process is also referred to as a target question. A target question is an example of a question.

[0184] The communication unit 111 outputs the target question to the terminal 2 via the network NW (step S41). Based on the acquisition of the target question output from the server 1, the terminal 2 displays the target question on the display device 27. For example, the terminal 2 displays a question statement and a plurality of first options on the display device 27.

[0185] The communication unit 111 acquires, via the network NW, from the terminal 2 an answer to the target question input via the terminal 2 (step S42). For example, the answer to the target question includes one option selected by the target user from a plurality of first options via the input device 26 of the terminal 2.

[0186] The communication unit 111 acquires input process data for the target user from the electronic device via the network NW (step S43).

[0187] The answer processing unit 112 determines whether the answer to the target question input via the terminal 2 is correct or incorrect (step S44). The process of step S44 may be the same as the process of step S3, and a description thereof will be omitted.

[0188] The additional information processing unit 116 acquires second additional information about the target user based on the input process data about the target user (step S45).

[0189] The communication unit 111 outputs the correct answer to the target question to the terminal 2 via the network NW (step S46). Based on the acquisition of the correct answer to the target question output from the server 1, the terminal 2 displays the correct answer to the target question on the display device 27. For example, the terminal 2 displays the correct answer option from among the multiple first options and an explanation of the target question on the display device 27.

[0190] The acquisition unit 113 acquires the target user's level of understanding of the target question based on the answer to the target question and the second additional information input via the terminal 2 (step S47). In step S47, the acquisition unit 113 acquires the target user's level of understanding of the question based on a combination of the correctness or incorrectness of the answer to the question and the second additional information. The acquisition unit 113 may acquire the target user's level of understanding of the question based on a set value according to the combination of the correctness or incorrectness of the answer and the second additional information. The acquisition unit 113 stores the acquired level of understanding of the target user for the target question in the user data storage area 142 in association with the target question.

[0191] The setting unit 114 sets the interval between the presentation of the target questions based on the target user's level of understanding of the target questions acquired by the acquisition unit 113 (step S48). The process of step S48 may be the same as the process of step S6, and the description thereof will be omitted.

[0192] The setting unit 114 sets the timing for presenting the target question based on the set question interval (step S49). The process of step S49 may be the same as the process of step S7, and a description thereof will be omitted.

[0193] FIG. 16 is a flowchart showing an example of the process of generating an additional information prediction model executed by the server 1. The additional information prediction model processing unit 117 may start the generation process of the additional information prediction model at any timing to create a new additional information prediction model. The additional information prediction model processing unit 117 may start the generation process of the additional information prediction model at any timing to update the additional information prediction model.

[0194] The additional information prediction model processing unit 117 acquires learning data (step S51). In step S51, for example, the additional information prediction model processing unit 117 acquires multiple pieces of sensing data and multiple pieces of data related to the level of understanding of one or more users. The additional information prediction model processing unit 117 may acquire multiple pieces of sensing data of one or more users from answer histories stored in the user data storage area 142. The additional information prediction model processing unit 117 may acquire, as data related to the levels of understanding, the correctness or incorrectness of multiple answers associated with the multiple pieces of sensing data from the answer histories stored in the user data storage area 142. If an answer is correct, the level of understanding may be set to high. If an answer is incorrect, the level of understanding may be set to low. The additional information prediction model processing unit 117 may acquire multiple pieces of sensing data of one or more users not included in the answer histories from a device other than the storage device 14 or the server 1. In this case, the sensing data may be user sensing data acquired in a situation other than the process of inputting an answer to a question. The additional information prediction model processing unit 117 may acquire data regarding multiple levels of understanding associated with multiple sensing data from a device other than the storage device 14 or the server 1. In this case, the level of understanding may be set according to the user's situation at the time the sensing data is acquired.

[0195] The additional information prediction model processing unit 117 generates an additional information prediction model by machine learning based on the learning data (step S52). In step S45, for example, the additional information prediction model processing unit 117 estimates, by machine learning, the relationship between the level of understanding indicated by the data related to the level of understanding and the elements indicated by the sensing data. The additional information prediction model processing unit 117 generates an additional information prediction model based on the estimation. The machine learning may be, but is not limited to, a neural network or the like.

[0196] The biological movements indicated by the user's photographed data vary depending on the level of understanding. For example, as the level of understanding of a problem decreases, the user's biological movements, such as the user's hands, eyes, and body, as they search for an answer may become more frequent due to hesitation. Therefore, there is a certain correlation between the user's photographed data and the level of understanding. The pointer trajectory indicated by the pointer trajectory data varies depending on the level of understanding. For example, as the level of understanding of a problem decreases, the user's hands, as they move the pointer to search for an answer, may become more frequent due to hesitation. Therefore, there is a certain correlation between the pointer trajectory data and the level of understanding. The user's biological movements, indicated by the biological movement data of at least one of the user's eyes, hands, and body, as described above, vary depending on the level of understanding. Therefore, there is a certain correlation between the user's biological movement data and the level of understanding. The user's vital data shows different trends depending on the level of understanding. For example, as the user's level of understanding of a problem decreases, the user's blood pressure, body temperature, or heart rate may increase due to the tension associated with indecision. Therefore, there is a certain correlation between the user's vital data and the level of understanding.

[0197] The additional information prediction model processing unit 117 stores the generated additional information prediction model in the storage device 14 (step S53).

[0198] (effect) In the information processing device, the additional information for the question includes additional information based on data relating to the process of inputting the answer about the user, which is acquired by the electronic device. The information processing device can acquire additional information without relying on the user's input of the additional information, thereby reliably acquiring the additional information. The information processing device can acquire additional information that is not dependent on the user's subjectivity, thereby improving the accuracy of acquiring the user's understanding.

[0199] [Other embodiments] Although an example has been described in which the set value is a value to be added to the level of understanding at the time of the understanding level acquisition process, this is not limiting. The set value may also be a percentage value by which the level of understanding at the time of the understanding level acquisition process is multiplied. In the first embodiment, if the answer is correct, the set value may be a value greater than 1. If the answer is incorrect, the set value may be a positive value less than 1. In the second and third embodiments, if the answer is correct, the set value may be a different value greater than 1 depending on the first additional information. The positive set value increases as the level of understanding indicated by the first additional information increases. If the answer is incorrect, the set value may be a positive value less than 1 regardless of the level of understanding indicated by the first additional information. In the fourth embodiment, if the answer is correct, the set value may be a different value greater than 1 depending on the second additional information. The positive set value increases as the level of understanding indicated by the second additional information increases. If the answer is incorrect, the set value may be a positive value less than 1 regardless of the level of understanding indicated by the second additional information.

[0200] The information processing device may be realized by one device as explained above using the server 1 as an example, or may be realized by multiple devices with distributed functions. Although an example has been explained in which the storage device 14 of the server 1 stores various data, a server different from the server 1 may store various data instead of the server 1. A plurality of servers different from the server 1 may store various data in a distributed manner instead of the server 1.

[0201] The program may be transferred in a state where it is stored in an electronic device, or in a state where it is not stored in an electronic device. In the latter case, the program may be transferred via a network, or in a state where it is recorded on a recording medium. The recording medium is a non-transitory tangible medium. The recording medium is a computer-readable medium. The form of the recording medium is not important as long as it is a medium that can store the program and is computer-readable, such as a CD-ROM or a memory card.

[0202] In short, this invention is not limited to the present embodiment as it is, and in the implementation stage, the components can be modified and embodied without departing from the spirit of the invention. Furthermore, various inventions can be formed by appropriately combining multiple components disclosed in this embodiment. For example, some components may be deleted from all the components shown in this embodiment. Furthermore, components from different embodiments may be appropriately combined. [Explanation of symbols]

[0203] 1...server, 2...terminal, 11...processor, 12...ROM, 13...RAM, 14...storage device, 15...communication interface, 21...processor, 22...ROM, 23...RAM, 24...storage device, 25...communication interface, 26...input device, 27...display device, 28...capturing device, 111...communication unit, 112...answer processing unit, 113...acquisition unit, 114...setting unit, 115...relationship data processing unit, 116...additional information processing unit, 117...additional information prediction model processing unit, 141...lesson data storage area, 142...user data storage area, 143...relationship data storage area, 144...additional information prediction model storage area.

Claims

1. A communication unit that outputs questions to a terminal; an acquisition unit that acquires a user's understanding of the question based on an answer to the question inputted via the terminal; A setting unit that sets the question presentation interval for the user based on a relationship between a level of understanding and a question presentation interval and the level of understanding of the user; Equipped with The relationship is a relationship according to a value related to a possibility of correctly answering the question. Information processing device.

2. An information processing device as described in Claim 1, wherein the relationship is such that as the value increases, the interval between questions at the same level of understanding becomes shorter.

3. An information processing device as described in claim 1, wherein the value is a value set by the user.

4. Outputting a problem to a terminal; acquiring a user's understanding of the question based on an answer to the question inputted via the terminal; Setting an interval between questions for the user based on a relationship between a level of understanding and an interval between questions and the level of understanding of the user; Equipped with The relationship is a relationship according to a value related to a possibility of correctly answering the question. Information processing methods.

5. An information processing program that causes a computer to execute processing by each part of an information processing device described in any one of claims 1 to 3.

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