Information processing device, information processing method, and information processing program

Abstract

To provide an information processing device, an information processing method, and an information processing program for proposing teaching material data useful for a user's own learning.SOLUTION: An information processing device includes a control unit that extracts information for identifying teaching material data for which results of a test meet predetermined conditions and at least the start-up date of the teaching material data is earlier than the date of the test from learning information including a first history in which start-up dates of the teaching material data for a plurality of users and information for identifying the teaching material data are associated, and a second history in which the implementation date of the test, information for identifying the test, and results of the test for the plurality of users are associated, and outputs the extracted information for identifying the teaching material data.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an information processing device, an information processing method, and an information processing program. [Background technology]

[0002] Recent electronic devices such as electronic dictionaries are configured to store various kinds of learning material data such as reference book data to support learning in addition to dictionary data. Some of these types of information processing devices also have a learning material data adding function. Furthermore, some electronic devices support a customization function that allows the sale of electronic devices with learning material data added in response to user requests. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2012-208143 A Summary of the Invention [Problem to be solved by the invention]

[0004] Even for electronic devices that support a customization function that allows the sale of electronic devices with added teaching material data in accordance with user requests, it can be difficult for users to determine which of the many pieces of teaching material data are useful for their own studies.

[0005] An object of the present invention is to provide an information processing device, an information processing method, and an information processing program for suggesting teaching material data useful for a user's own learning. [Means for solving the problem]

[0006] An information processing device of an embodiment has a control unit that extracts information for identifying teaching material data whose test results satisfy a predetermined condition and whose start date of at least the teaching material data is earlier than the test implementation date from learning information including a first history in which the launch dates of teaching material data for multiple users and information for identifying the teaching material data are associated, and a second history in which the implementation dates of tests for multiple users, information for identifying the tests, and results of the tests are associated, and outputs the extracted information for identifying the teaching material data. Effect of the Invention

[0007] The embodiments can provide an information processing device, an information processing method, and an information processing program for suggesting teaching material data useful for a user's own learning. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of a configuration of a system according to an embodiment. [Diagram 2] FIG. 2 is a diagram showing a detailed configuration of the system. [Diagram 3] FIG. 3 is a diagram showing an example of the learning information 143. As shown in FIG. [Figure 4] FIG. 4 is a diagram showing an example of the learning information 244. As shown in FIG. [Diagram 5] FIG. 5 is a flowchart showing the operation of the server. [Figure 6] FIG. 6 is a flowchart showing the operation of the electronic dictionary. [Figure 7] FIG. 7 is a diagram showing an example of the top screen. [Figure 8] FIG. 8 is a flowchart illustrating an example of the proposal process. [Figure 9] FIG. 9 is a diagram showing an example of the proposal top screen. [Figure 10] FIG. 10 is a diagram showing an example of the proposal screen. [Figure 11] FIG. 11 is a flowchart showing the teaching material extraction process. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, an embodiment will be described with reference to the drawings. FIG. 1 is a diagram showing an example of a configuration of a system 1 according to an embodiment. The system 1 includes an electronic dictionary 10 and a server 20. The electronic dictionary 10 and the server 20 are communicatively connected via a network 30. The network 30 is, for example, the Internet. Although three electronic dictionaries 10 are shown in FIG. 1, the number of electronic dictionaries 10 is not limited to three. In the embodiment, it is assumed that the three electronic dictionaries 10 are used by different users.

[0010] Fig. 2 is a diagram showing a detailed configuration of the system 1. Here, Fig. 2 shows one electronic dictionary 10 as a representative. The electronic dictionary 10 has a processor 11, a ROM 12, a RAM 13, a storage 14, an input device 15, a display device 16, and a communication device 17. Each of these is connected to each other via a system bus 18. The electronic dictionary 10 may be an electronic device such as a personal computer (PC) on which an electronic dictionary application is installed, a tablet terminal, or a smartphone.

[0011] The processor 11 is a processor that controls various operations of the electronic dictionary 10. The processor 11 may be an integrated circuit including a CPU (Central Processing Unit) etc. The processor 11 may be a processor other than a CPU, such as an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a GPU (Graphic Processing unit).

[0012] The ROM 12 stores a start-up program for the electronic dictionary 10. The RAM 13 is a main storage device for the processor 11 and the like.

[0013] The storage 14 can operate as a memory unit. The storage 14 stores various programs, such as an electronic dictionary control program, and parameters used by the processor 11. The processor 11 controls the operation of the electronic dictionary 10 by executing the various programs in response to an input signal from the input device 15. The various programs include, for example, a teaching material processing program 141. The teaching material processing program 141 is a program for executing various processes on the content included in the teaching material data 142 based on an instruction from a user. The teaching material processing program 141 can be, for example, a program for executing a process of displaying the content included in the teaching material data 142 on the display device 16 and a process of returning a response to an instruction from the user regarding the displayed content.

[0014] The teaching material data 142 is various content data such as dictionary data and reference book data used for user learning. For example, the dictionary data is content data in which words and phrases such as words from a Japanese dictionary or an English-Japanese dictionary are associated with their meanings and the like and stored. The reference book data is content data in which explanations of textbooks and simple question set data for confirming understanding are stored. The teaching material data 142 also includes test data. The test data is content data for carrying out various tests. The test data may be generated with reference to the question set data. The teaching material data 142 may be added by being downloaded from the server 20, for example.

[0015] Furthermore, in the embodiment, the storage 14 stores learning information 143. The learning information 143 is information on the history of learning performed by the user using the electronic dictionary 10. In the embodiment, the learning history includes a start history of dictionary data, reference book data, problem set data, etc. as learning for improving one's own academic ability, and a history of tests using test data as learning for checking one's current academic ability.

[0016] FIG. 3 is a diagram showing an example of the learning information 143. The learning information 143 includes information on "date" and "contents". "Date" is information on the date of the learning. "Contents" is information indicating the contents of the learning. The contents of the learning include information for identifying the teaching material data started by the user, information for identifying the test based on the test data carried out by the user, and information such as the results of the test. The information for identifying the teaching material data is, for example, the name of the teaching material data. Also, the information for identifying the test is, for example, the name of the test. The learning information 143 is updated when the teaching material data 142 is started. Alternatively, the learning information 143 is updated when the test is carried out and grading is completed. For example, when "teaching material A" is used as the teaching material data 142, the date of its start is recorded as "date" information, and the name of the started teaching material data 142, "teaching material A", is recorded as "contents" information. Also, for example, when "Test 1" is conducted using the teaching material data 142, the date of its implementation is recorded as "date" information, and the name of the conducted test, "Test 1," is recorded as "content" information together with the marking result at that time. Here, the learning information 143 may be stored for each user of the electronic dictionary 10. In this case, the learning information 143 is stored in association with, for example, the ID of the user of the electronic dictionary 10.

[0017] The input device 15 includes an input key, a touch panel, etc. The input device 15 may also include a voice input device such as a microphone. In response to a user operation via the input device 15, a signal indicating the content of the user operation is input to the processor 11 via the system bus 18.

[0018] The display device 16 is a liquid crystal display, an organic EL display, etc. The display device 16 may be provided integrally with the electronic dictionary 10, or may be provided separately from the electronic dictionary 10. Various images are displayed on the display device 16.

[0019] The communication device 17 includes circuitry for communicating with an external communication network, such as the network 30. The communication device 17 may act as a communication unit.

[0020] The server 20 is an information processing device having a processor 21, a ROM 22, a RAM 23, a storage 24, and a communication device 25. These are connected to each other via a system bus .

[0021] The processor 21 is a processor that controls various operations of the server 20. The processor 21 may be an integrated circuit including a CPU, etc. As the processor 21, a processor other than a CPU, for example, an ASIC, an FPGA, a GPU, etc. may be used.

[0022] The ROM 22 records information used for the operation of the processor 21 etc. The RAM 23 is a main storage device for the operation of the processor 21 etc.

[0023] The storage 24 stores various programs, parameters, etc., such as a server control program used by the processor 21. The processor 21 controls the operation of the server 20 by executing the various programs. The various programs include, for example, an extraction program 241. The extraction program 241 is a program for executing a process of extracting teaching material data useful for the user's learning from the teaching material data 142 stored in the electronic dictionary 10 or from teaching material data other than the teaching material data 142. The processor 21 can operate as a control unit by executing a process in accordance with the extraction program 241.

[0024] In addition, the storage 24 stores user information 242, teaching material data 243, and learning information 244.

[0025] The user information 242 is information for identifying a user of the electronic dictionary 10. The user information may include information indicating user attributes such as a user ID, an ID of the electronic dictionary 10, and the user's age.

[0026] The teaching material data 243 is various content data, such as dictionary data, reference book data, question collection data, and test data, that can be downloaded and used in the electronic dictionary 10. The teaching material data 243 may include more content data than the teaching material data 142 pre-stored in the electronic dictionary 10.

[0027] The learning information 244 is learning information collected from a plurality of electronic dictionaries 10. FIG. 4 is a diagram showing an example of the learning information 244. Each piece of learning information collected from the electronic dictionary 10 as the learning information 244 is assigned, for example, an ID (identification information) for management purposes. FIG. 4 shows an example in which three pieces of learning information are stored. FIG. 4 shows that the IDs of the three pieces of learning information are "learning information 1", "learning information 2", and "learning information 3", respectively. The information collected as the learning information may be the same as the learning information 143 stored in the electronic dictionary 10. Here, the learning information 244 may be stored for each user of the electronic dictionary 10. In this case, different IDs are assigned to the learning information of different users collected from the same electronic dictionary 10 as different learning information. In addition, information on the results of compilation of the learning information collected from the plurality of electronic dictionaries 10 may be further stored as the learning information 244. The information on the results of compilation may include, for example, information such as the number of times the same teaching material data was used within a certain period, and the average score of the same test administered within a certain period.

[0028] The communication device 25 includes circuitry for communicating with an external communication network, such as the network 30. The communication device 25 may act as a communication unit.

[0029] Next, a description will be given of the operation of the system 1. Fig. 5 is a flowchart showing the operation of the server 20. The process of Fig. 5 is started periodically while the server 20 is in operation.

[0030] In step S1, the processor 21 of the server 20 determines whether or not learning information has been received from the electronic dictionary 10. If it is determined in step S1 that learning information has been received, the process proceeds to step S2. If it is determined in step S1 that learning information has not been received, the process proceeds to step S3.

[0031] In step S2, the processor 21 stores the learning information received from the electronic dictionary 10 in the storage 24. When the corresponding learning information is already stored in the storage 24, the processor 21 overwrites the original learning information with the learning information received from the electronic dictionary 10. On the other hand, when the corresponding learning information is not stored in the storage 24, the processor 21 newly stores the learning information received from the electronic dictionary 10. The learning information 244 stored in the storage 24 may be erased after a certain period of time has elapsed. Of course, the learning information 244 stored in the storage 24 does not have to be erased after a certain period of time has elapsed. Furthermore, as described above, the learning information may be managed for each user. In this case, the processor 21 stores the learning information for each user based on the user ID associated with the learning information received from the electronic dictionary 10 and the user ID stored in the user information 242.

[0032] In step S3, processor 21 determines whether or not a teaching material data suggestion request has been received. The teaching material data suggestion request is transmitted, for example, from electronic dictionary 10. The teaching material data suggestion request may be transmitted from an electronic device other than electronic dictionary 10, i.e., an electronic device that does not have an electronic dictionary function. If it is determined in step S3 that a teaching material data suggestion request has been received, processing proceeds to step S4. If it is determined in step S3 that a teaching material data suggestion request has not been received, processing returns to step S1.

[0033] In step S4, the processor 21 executes a teaching material extraction process. After the teaching material extraction process, the process returns to step S1. The teaching material extraction process is a process for extracting teaching material data useful for the user's learning. The teaching material extraction process will be described later.

[0034] 6 is a flowchart showing the operation of electronic dictionary 10. The operation of Fig. 6 is started, for example, every time electronic dictionary 10 is powered on. In step S101, processor 11 of electronic dictionary 10 displays the top screen of electronic dictionary 10 on display device 16.

[0035] 7 is a diagram showing an example of a top screen. Buttons and the like other than those shown in FIG. 7 may be displayed on the top screen.

[0036] The top screen in one example displays a list 161 of teaching material data recorded as teaching material data 142 in the electronic dictionary 10. The user can select teaching material data that the user wishes to use from the list 161 of teaching material data. The top screen in one example also displays a list 162 of tests that can be administered based on the teaching material data 142 in the electronic dictionary 10. The user can select a test that the user wishes to take from the list 162 of tests. Furthermore, the top screen in one example displays a suggestion button 163. The suggestion button 163 is a button that the user selects when the electronic dictionary 10 suggests teaching material data that is useful for the user's studies.

[0037] In step S102, processor 11 determines whether or not to launch the teaching material data. For example, when one piece of teaching material data in list 161 of teaching material data is selected by the user, it is determined that the teaching material data is to be launched. When it is determined in step S102 that the teaching material data is to be launched, the process proceeds to step S103. When it is not determined in step S102 that the teaching material data is to be launched, the process proceeds to step S105.

[0038] In step S103, the processor 11 starts the teaching material data selected by the user. After that, the processor 11 executes processing corresponding to the started teaching material data. After the started teaching material data is terminated, the process proceeds to step S104. For example, when the dictionary data is started, the processor 11 displays the top screen of the started dictionary on the display device 16, searches the dictionary data for a term corresponding to the search term input by the user, and displays the search result on the display device 16. When the reference book data is started, the processor 11 displays the explanation of the textbook stored as the reference book data in response to the user's operation. Furthermore, when the problem set data is started, the processor 11 displays problems of various subjects in response to the user's operation, and when the user inputs an answer to the problem, the problem is compared with the correct answer stored in advance and the explanation is displayed. After that, when the processor 11 receives an instruction from the user to end the display of the teaching material data, the process proceeds to step S104.

[0039] In step S104, the processor 11 updates the learning information 143. After that, the process proceeds to step S110. Specifically, the processor 11 registers the name of the activated teaching material data in the learning information 143 together with the activation date.

[0040] In step S105, processor 11 determines whether or not to perform a test. For example, if one test in test list 162 is selected by the user, it is determined that the test is to be performed. If it is determined in step S105 that the test is to be performed, the process proceeds to step S106. If it is not determined in step S105 that the test is to be performed, the process proceeds to step S108.

[0041] In step S106, the processor 11 starts the test data included in the teaching material data selected by the user, and conducts the test. After the test is completed, the process proceeds to step S107. For example, the processor 11 displays test questions on the display device 16 together with answer columns based on the selected test data. After the test time has elapsed or when an instruction to end the test is given by the user, the processor 11 performs grading. Grading may be performed by a device external to the electronic dictionary 10, such as the server 20. After grading, the processor 11 displays the grading results on the display device 16. After that, when an instruction to end the test is received from the user, the process proceeds to step S107.

[0042] In step S107, the processor 11 updates the learning information 143. After that, the process proceeds to step S110. Specifically, the processor 11 registers the name of the test that was conducted and the marking result at that time together with the date of the test in the learning information 143.

[0043] In step S108, processor 11 determines whether or not to propose teaching material data. For example, if suggestion button 163 is selected by the user, it is determined that teaching material data is to be proposed. If it is determined in step S108 that teaching material data is to be proposed, the process proceeds to step S109. If it is not determined in step S108 that teaching material data is to be proposed, the process proceeds to step S110.

[0044] In step S109, the processor 11 executes a suggestion process. After the suggestion process is completed, the process proceeds to step S110. The suggestion process is a process for suggesting the teaching material data extracted by the server 20 as recommended teaching material data for the user. The suggestion process will be described later.

[0045] In step S110, the processor 11 determines whether or not to power off the electronic dictionary 10. For example, if the power button of the electronic dictionary 10 is pressed by the user, it is determined that the power of the electronic dictionary 10 is to be turned off. If it is determined in step S110 that the power of the electronic dictionary 10 is to be turned off, the process proceeds to step S111. If it is not determined in step S110 that the power of the electronic dictionary 10 is to be turned off, the process returns to step S101.

[0046] In step S111, the processor 11 transmits the learning information to the server 20. Then, the process in Fig. 6 ends. Here, the learning information does not necessarily need to be transmitted immediately before the power of the electronic dictionary 10 is turned off. The learning information may be transmitted, for example, when the learning information is updated, at a predetermined time such as each night, or immediately after the power of the electronic dictionary 10 is turned on.

[0047] 8 is a flow chart showing an example of the suggestion process. In step S201, the processor 11 of the electronic dictionary 10 displays a suggestion top screen on the display device 16.

[0048] 9 is a diagram showing an example of a proposal top screen. Buttons and the like other than those shown in FIG. 9 may be displayed on the proposal top screen.

[0049] In an example of the proposal top screen, a list 164 of subjects for which a user wants to receive a proposal for teaching material data is displayed. The user can select a subject for which the user wants to receive a proposal from the list 164 of subjects. Here, in FIG. 9, the list 164 of subjects is displayed. Instead of the list 164 of subjects, a list of tests may be displayed. In this case, the user can select a test for which the user wants to improve his / her score. Furthermore, when the list of subjects is selected, a list of specific learning items for which the user wants to receive a proposal for teaching material data may be displayed. For example, when "mathematics" is selected as the subject, a list of learning items for each subject, such as "quadratic functions" and "factorization", may be displayed. In this case, the user can select a subject for which the user wants to receive a proposal from the list 164 of subjects, and then select a learning item.

[0050] Also, in the example proposal top screen, a selection field 165 for one's own learning goals is displayed. The user can select a goal close to one's own learning goal from the goal selection field 165. For example, in FIG. 9, the user can select the goal close to one's own goal from two options, "I want to improve my score" and "I want to get a high score." Here, the goals displayed in the goal selection field 165 are not limited to the two shown in FIG. 9.

[0051] Also, the example proposal top screen displays a proposal execution button 166. The proposal execution button 166 is a button selected by the user to instruct the execution of a proposal of teaching material data.

[0052] In step S202, processor 11 determines whether to execute the proposal. For example, when proposal execution button 166 is selected, it is determined that the proposal is executed. When it is not determined that the proposal is executed in step S202, the process returns to step S201. During this time, the user can select a subject for which he or she wants to receive a proposal from subject list 164, and can also select a goal that is close to his or her own learning goal from goal selection field 165. When it is determined that the proposal is executed in step S202, the process proceeds to step S203.

[0053] In step S203, the processor 11 determines whether or not the information required to execute the proposal has been input. For example, when the information on the subject and the information on the learning goal have been input on the proposal top screen of FIG. 9, it is determined that the information required to execute the proposal has been input. When it is determined in step S203 that the information required to execute the proposal has been input, the process proceeds to step S204. When it is not determined in step S203 that the information required to execute the proposal has been input, the process returns to step S201. At this time, the processor 11 may display a message on the display device 16 to prompt the user to input information.

[0054] In step S204, the processor 11 transmits a proposal request to the server 20. The proposal request includes, for example, information for identifying the electronic dictionary 10 or the user, and information on the subject and learning goal input by the user.

[0055] In step S205, the processor 11 determines whether or not proposed information has been received from the server 20. The proposed information includes information for identifying the teaching material data extracted in the server 20. In step S205, the processor 11 waits until the proposed information is received from the server 20. When it is determined in step S205 that the proposed information has been received from the server 20, the process proceeds to step S206.

[0056] In step S206, the processor 11 displays a teaching material data suggestion screen on the display device 16 based on the suggestion information received from the server 20.

[0057] Fig. 10 is a diagram showing an example of a proposal screen. Buttons and the like other than those shown in Fig. 10 may be displayed on the proposal screen.

[0058] In one example of the proposal screen, a list 167 of teaching material data extracted by the server 20 is displayed. As will be described later, the teaching material data extracted by the server 20 may include teaching material data that has already been recorded in the electronic dictionary 10 and teaching material data that has not been recorded. For teaching material data that has not been recorded in the electronic dictionary 10, an add button 168 is displayed. The add button 168 is a button that is selected by the user when adding teaching material data.

[0059] Also displayed on the proposal screen in one example is an end button 169. The end button 169 is a button selected by the user when ending the display of the proposal screen.

[0060] In step S207, processor 11 determines whether or not end button 169 has been selected. If it is determined in step S207 that end button 169 has been selected, the processing in Fig. 8 ends. In this case, the processing proceeds to step S110 in Fig. 6. If it is determined in step S207 that end button 169 has not been selected, the processing proceeds to step S208.

[0061] In step S208, the processor 11 determines whether or not the Add button 168 has been selected. If it is determined in step S208 that the Add button 168 has been selected, the process proceeds to step S209. If it is determined in step S208 that the Add button 168 has not been selected, the process returns to step S207.

[0062] In step S209, processor 11 processes the addition of teaching material data. After that, the process returns to step S207. Specifically, processor 11 requests, for example, server 20 to transmit the teaching material data corresponding to add button 168 selected by the user. The request to add teaching material data may be made after the user has completed payment of the fee. In addition, the additional teaching material data does not necessarily have to be stored in server 20. In this case, processor 11 requests the storage destination in which the corresponding teaching material data is stored to transmit the teaching material data. After receiving the additional teaching material data, processor 11 stores the received teaching material data in storage 14 as new teaching material data 142. After that, the process returns to step S207.

[0063] FIG. 11 is a flowchart showing the teaching material extraction process. In step S301, the processor 21 of the server 20 starts the process of proposing teaching material data to be recommended based on the proposal request received from the user's electronic dictionary 10. Specifically, it is determined from the information included in the proposal request whether the goal selected by the user is "want to get a high score" or "want to improve score". When it is determined in step S301 that the goal selected by the user is "want to get a high score", the process proceeds to step S302. When it is determined in step S301 that the goal selected by the user is "want to improve score", the process proceeds to step S304.

[0064] In step S302, the processor 21 extracts learning information with test scores of 90 points or more from the learning information 244 of the subject selected by the user. When the test of the subject selected by the user is test 1 and the standard for high scores is, for example, 90 points or more, the processor 21 extracts learning information with test 1 results of 90 points or more. For example, when the learning information shown in FIG. 4 is stored in the storage 24, the processor 21 extracts learning information 1 with test 1 results of 90 points as learning information with high test scores. On the other hand, the processor 21 does not extract learning information 2 with test 1 results of 70 points and learning information 3 with test 1 results of 50 points as learning information with high scores because the test scores are less than the standard score of 90 points. On the other hand, when the standard value for high scores is, for example, 70 points or more, the processor 21 extracts learning information with test results of 70 points or more. In this case, for example, when the learning information shown in FIG. 4 is stored in the storage 24, the processor 21 extracts learning information 1 in which the result of test 1 is 90 points and learning information 2 in which the result of test 1 is 70 points as learning information with high test scores, but does not extract learning information 3 in which the result of test 1 is 50 points as learning information with high test scores. The reference value of high scores is preset in the server 20. The reference value of high scores may be specified by the user. Also, when information on learning items is included in the proposal request, the processor 11 may extract learning information based on the scores of the learning items selected by the user.

[0065] In step S303, the processor 21 excludes information on teaching materials used in the period after the test from the extracted learning information. After that, the process proceeds to step S306. For example, in the learning information 1, the implementation date of the test 1 is January 6, 2022. Therefore, the processor 21 excludes information whose activation date is January 7, 2022 from the extracted learning information 1. In other words, the processor 21 extracts information whose activation date is before the implementation date of the test 1. This is because it is unclear whether the teaching material data used after the test is teaching material data that contributed to a high score. Note that even if the activation date is before the implementation date of the test 1, the teaching material data whose latest activation date is more than a predetermined period (for example, one month) before the implementation date of the test 1 is excluded from the extraction target. This is because if the activation date of the teaching material data is too old, it is unclear whether it contributed to a high score of the test.

[0066] In step S304, the processor 21 extracts learning information in which the test score has improved from the learning information 244 of the subject selected by the user. When the test of the subject selected by the user is test 1, the processor 21 extracts learning information in which the score of test 1 has improved. For example, when the learning information shown in FIG. 4 is stored in the storage 24, the processor 21 extracts learning information in which the test score has improved, that is, learning information 2 in which the result of test 1 has improved from 50 points to 70 points. On the other hand, the processor 21 does not extract learning information 1 in which test 1 has not been administered multiple times and learning information 3 in which the result of test 1 has not improved from 50 points, as learning information in which the test score has improved. Here, a reference value of the improvement range of the score may be preset in the server 20. In other words, learning information in which the improvement range of the score does not meet the reference value may not be extracted. In addition, the reference value of the improvement range of the score may be specified by the user. Furthermore, when information on the learning item is also included in the proposal request, the processor 11 may extract learning information based on the score of the learning item selected by the user.

[0067] In step S305, the processor 21 excludes information on teaching materials used outside the test period between the previous test and the next test from the extracted learning information. Then, the process proceeds to step S306. For example, in the learning information 2, the implementation date of the first test 1 is January 4, 2022, and the implementation date of the second test 1 is January 8, 2022. Therefore, the processor 21 excludes information whose start date is January 2, 2022 and information whose start date is January 3, 2022 from the extracted learning information 2. In other words, the processor 21 extracts information whose start date is later than the implementation date of the first test 1 and earlier than the implementation date of the second test 1. This is because it is unclear whether the teaching material data used outside the test period is teaching material data that contributed to the improvement of the score.

[0068] In step S306, the processor 21 refers to the learning information of the electronic dictionary 10 that sent the proposal request or its user, and excludes information on teaching materials that the user has already used from the extracted learning information. For example, if the learning information of the user of the electronic dictionary 10 is learning information 3, the processor 21 excludes information on "teaching material C," "teaching material D," and "teaching material E" from the extracted learning information. This is because teaching materials that the user has already used may not contribute to the user obtaining a high score or improving their score.

[0069] In step S307, the processor 21 transmits the proposal information to the electronic dictionary 10 that has transmitted the proposal request. After that, the process of FIG. 11 ends. The proposal information includes information for identifying the teaching material data that remains without being excluded from the extracted learning information. For example, when "I want to get a high score" is specified as the learning goal, the test of the subject selected by the user is test 1, and the reference value of the high score is, for example, 90 points or more, the processor 21 extracts the learning information 1 as described above. In this case, the proposal information includes information for identifying each of "teaching material A" and "teaching material B". The information for identifying the teaching material data may be the name, ID, etc. of the teaching material data. According to such proposal information, the proposal screen shown in FIG. 10 may be displayed on the electronic dictionary 10.

[0070] As described above, according to this embodiment, information on teaching material data useful for the user's learning is output as suggested information based on learning information collected from multiple electronic dictionaries 10. The extraction of teaching material data information at this time is performed based on not only the test scores but also the test implementation date. This makes it possible to efficiently eliminate information on teaching material data that is not considered to contribute to improving academic ability. This increases the possibility of extracting information on teaching material data useful for the user's learning. Having such teaching material data information suggested to the user helps the user determine which teaching material data among many teaching material data is useful for his or her learning.

[0071] In addition, the extraction of information from teaching material data is also performed based on the learning goal specified by the user. This increases the possibility of extracting information from teaching material data that more closely matches the user's goal. In the embodiment, the extraction of information from teaching material data based on two learning goals, such as "I want to improve my score" and "I want to get a high score," is shown. It goes without saying that for other learning goals, information from teaching material data is extracted in accordance with each learning goal.

[0072] [Variations] Modifications of the embodiment will be described below. FIG. 4 shows an example in which only three pieces of learning information are stored in the storage 24 of the server 20. In reality, a large number of pieces of learning information collected from a larger number of electronic dictionaries 10 may be stored in the storage 24. In this case, there is a possibility that learning information including information on teaching materials that have high test scores or improved scores only when used by a specific user may be extracted. Information on teaching materials that improve academic ability only when used by such a specific user may not be included in the suggested information. In other words, a process of excluding information on teaching materials that are used less than a threshold number of times among all users may be added to the process of FIG. 11. Of course, information on teaching materials that improve academic ability only when used by a specific user may also be useful, so a process of excluding information on teaching materials that are used less than a threshold number of times among all users may not be added to the process of FIG. 11.

[0073] In the above-described embodiment, the learning information stored in the storage 24 of the server 20 is collected from the electronic dictionary 10. In contrast, as long as the learning information is associated with user information, it is not necessarily required to collect the learning information from the electronic dictionary 10. For example, the results of a test conducted in an environment other than the electronic dictionary 10 may be transmitted to the server 20 as learning information associated with the user's ID or the like. The learning information may also be manually input, etc. In this case, the test does not necessarily need to be conducted using an electronic device, and may be conducted, for example, using paper.

[0074] In the above-described embodiment, the suggestion screen is displayed on the display device 16 of the electronic dictionary 10. However, the suggestion screen does not necessarily have to be displayed on the display device 16 of the electronic dictionary 10. For example, the suggestion screen shown in FIG. 10 may be displayed on the screen of an online shop that a user considering purchasing an electronic dictionary is browsing using an electronic device such as a smartphone. In this case, the user can determine whether or not to add the suggested teaching material data to the electronic dictionary that the user is considering purchasing, and add the teaching material data as necessary. In this way, the embodiment can also be applied to online sales of electronic dictionaries 10 with customization functions.

[0075] In the above-described embodiment, the extraction of information on teaching material data useful for the user's learning is generated in the server 20. In contrast, the generation of suggested information and the display of the suggested screen may be performed in the electronic dictionary 10. In this case, the electronic dictionary 10 operates as an information processing device. Here, even if the electronic dictionary 10 extracts information on teaching material data, the collection of learning information from multiple electronic dictionaries 10 may be performed in the server 20.

[0076] The present invention is not limited to the above-mentioned embodiment, and can be modified in various ways in the implementation stage without departing from the gist of the invention. In addition, each embodiment may be implemented in combination as appropriate as possible, and in that case, the combined effect can be obtained. Furthermore, the above-mentioned embodiment includes inventions at various stages, and various inventions can be extracted by appropriate combinations of the disclosed multiple constituent elements. For example, even if some constituent elements are deleted from all the constituent elements shown in the embodiment, if the problem described in the "Problem to be Solved by the Invention" column can be solved and the effect described in the "Effect of the Invention" column can be obtained, the configuration from which the constituent elements are deleted can be extracted as the invention. [Explanation of symbols]

[0077] 1 system, 10 electronic dictionary, 11 processor, 12 ROM, 13 RAM, 14 storage, 15 input device, 16 display device, 17 communication device, 18 system bus, 20 server, 21 processor, 22 ROM, 23 RAM, 24 storage, 25 communication device, 26 system bus, 30 network, 141 teaching material processing program, 142 teaching material data, 143 learning information, 241 extraction program, 242 user information, 243 teaching material data, 244 learning information.

Claims

1. extracting information for identifying the teaching material data for which the test result satisfies a predetermined condition and at least the start date of the teaching material data is earlier than the test implementation date from learning information including a first history in which activation dates of teaching material data for a plurality of users and information for identifying the teaching material data are associated with each other, and a second history in which implementation dates of tests for the plurality of users, information for identifying the tests, and results of the tests are associated with each other; outputting information for identifying the extracted teaching material data; An information processing device comprising a control unit.

2. the predetermined condition being that the test score is equal to or greater than a reference value; the control unit extracts, from the learning information in which the test score is equal to or greater than a reference value, information for identifying the teaching material data whose activation date is before the implementation date of the test. The information processing device according to claim 1 .

3. The information processing device according to claim 1, characterized in that the control unit extracts information for identifying the teaching material data whose result of the test satisfies a predetermined condition and whose start date of the teaching material data is prior to the date on which the test was conducted and within a predetermined period from the date on which the test was conducted.

4. the predetermined condition being that the test score is improved from the previous test score, the control unit extracts, from the learning information in which the test score is improved from the score of the previous test, information for identifying the teaching material data whose activation date is before the implementation date of the test and after the implementation date of the previous test. The information processing device according to claim 1 .

5. the control unit outputs information for identifying the teaching material data to the electronic device that has made the request. The information processing device according to claim 1 .

6. extracting information for identifying the teaching material data for which the test result satisfies a predetermined condition and at least the activation date of the teaching material data is earlier than the implementation date of the test from learning information including a first history in which activation dates of teaching material data for a plurality of users are associated with information for identifying the teaching material data, and a second history in which implementation dates of tests for the plurality of users are associated with information for identifying the tests, and a result of the tests; outputting information for identifying the extracted teaching material data; An information processing method comprising:

7. extracting information for identifying teaching material data for which the test result satisfies a predetermined condition and at least the start date of the teaching material data is earlier than the test implementation date from learning information including a first history in which activation dates of teaching material data for a plurality of users and information for identifying the teaching material data are associated with each other, and a second history in which implementation dates of tests for the plurality of users, information for identifying the tests, and results of the tests are associated with each other; outputting information for identifying the extracted teaching material data; An information processing program for causing a processor to execute the above.

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