Information processing device and program

Abstract

To realize a mechanism for evenly supporting learning by genres.SOLUTION: A learning device 10 executes learning processing including setting questions by genre, receiving a user's input of answers to the questions, and determining whether or not the input of the answer is correct, for each genre. The learning device 10 includes a classification unit 133 that classifies each genre into a plurality of groups by using at least a result of genre-specific evaluation based on learning data related to the learning processing, and an execution control unit 135 that executes a series of processing including selection of a selection group from the plurality of groups, selection of a selection genre from genres belonging to the selection group, and learning processing related to the selection genre, the execution control unit executing suppression control for suppressing consecutive selection of the same group as the selection group in a series of consecutive processing.SELECTED DRAWING: Figure 14

Description

Technical Field

[0001] The present invention relates to an information processing apparatus and a program.

Background Art

[0002] As a technology of an information processing apparatus that supports user learning, there is one that improves the learning efficiency of a learner. For example, Patent Document 1 discloses a technique for selecting a problem that recommends learning to achieve a learning goal based on the learning goal of a learner.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] By the way, when questions are presented by genre to support learning related to a plurality of genres, the user may be good or bad at each genre. There is a need for a mechanism that can improve the academic ability in the favorite genre and continue learning without getting bored even if there is a genre that the user is not good at.

[0005] The problem to be solved by the present invention is to realize a mechanism for evenly supporting genre-by-genre learning.

Means for Solving the Problems

[0006] Aspects of the present invention are information processing apparatuses that execute learning processes including, for each genre, posing a problem, accepting a user's answer input for the problem, and determining whether the answer input is correct or incorrect. The information processing apparatuses include a classification unit that classifies each genre into a plurality of groups using at least the results of genre-specific evaluations based on learning data related to the learning process, and an execution control unit that executes a series of processes including selecting a selected group from among the plurality of groups, selecting a selected genre from among the genres belonging to the selected group, and performing the learning process related to the selected genre. In the series of consecutive processes, the execution control unit performs suppression control to suppress consecutive selection of the same group as the selected group.

[0007] Further, there are three or more types of groups including a good-at group and a not-good-at group, and the execution control unit may select the other group as the selected group after selecting one of the good-at group and the not-good-at group as the selected group in two consecutive series of the processes.

[0008] Further, there are three or more types of groups including a good-at group and a not-good-at group, and the execution control unit may select the not-good-at group as the selected group after first selecting the good-at group as the selected group in two consecutive series of the processes.

[0009] Further, the execution control unit may perform the suppression control by selecting the selected group from among the plurality of groups in a predetermined order in the series of consecutive processes.

[0010] Further, the classification unit may update the classification of each genre every time a predetermined number of the learning processes are completed.

[0011] Further, the classification unit may update the classification of each genre every time the order of the group selected as the selected group goes around.

[0012] Further, the execution control unit may perform the same genre continuous selection suppression control for suppressing continuous selection of the same genre as the selected genre.

[0013] In addition, the group includes a good-at group, a not-good-at group, and other groups, the genre includes a determination target genre that is the target of the genre-by-genre evaluation and a non-target genre that is not the target of the genre-by-genre evaluation, and the classification unit classifies the determination target genre into the good-at group and the not-good-at group, and classifies the non-target genre into the other group.

[0014] Further, a genre-by-genre evaluation unit that performs the genre-by-genre evaluation by determining the level of proficiency or non-proficiency for each genre based on the learning data updated in response to the execution of the learning process may be further provided.

[0015] In addition, the classification unit determines the in-group ranking of the genres belonging to each classified group, and the execution control unit sequentially selects the selected genre from the same group based on the in-group ranking related to the same group.

[0016] Further, the execution control unit may set, as the learning goal of the user, to execute a number of the learning processes corresponding to a predetermined multiple of the number of the groups within a predetermined period, and perform display control indicating the learning goal.

[0017] Also, a program for causing a computer to execute learning processing including problem posing, acceptance of user answers to the problems, and correct / incorrect determination of the answer inputs for each genre, the program comprising: a classification unit that classifies each genre into a plurality of groups using at least the results of genre-specific evaluations based on learning data related to the learning processing; and an execution control unit that executes a series of processes including selection of a selected group from among the plurality of groups, selection of a selected genre from among the genres belonging to the selected group, and the learning processing related to the selected genre, the execution control unit performing suppression control for suppressing consecutive selection of the same group as the selected group in consecutive executions of the series of processes. The program may be configured to function the computer as the execution control unit.

Effect of the Invention

[0018] According to the present invention, a series of processes including classifying a genre into a plurality of groups, selecting a selected group from among the plurality of groups, selecting a selected genre from among the genres belonging to the selected group, and performing learning processing related to the selected genre are executed. And in the series of processes, consecutive selection of the same group as the selected group is suppressed. According to this, it becomes possible to evenly support the user's learning by genre.

Brief Description of the Drawings

[0019]

Figure 1

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Figure 18

Mode for Carrying Out the Invention

[0020] Hereinafter, with reference to the drawings, preferred embodiments of the present invention will be described. Hereinafter, a learning device will be exemplified as an information processing device, and a subject will be cited as an example of a genre, and a learning device that supports subject-by-subject learning will be described. Note that the present invention is not limited by the embodiments described below, and the forms to which the present invention is applicable are not limited to the following embodiments. Also, in the description of the drawings, the same reference numerals are given to the same parts.

[0021] FIG. 1 is a diagram showing an external appearance example of a learning device 10 in the present embodiment. The learning device 10 of the present embodiment is an information processing device having, for example, the form of a notebook personal computer, and includes a main body device 1 and a mouse 3. The main body device 1 includes a power button 11, a keyboard 13, and a display 15. In addition, a camera, a microphone, a speaker, etc., not shown, are provided in appropriate places.

[0022] In addition, the main body device 1 incorporates a control board 5 on which electronic components such as a microprocessor like a CPU (Central Processing Unit) 51, an IC (Integrated Circuit) memory 53, and a communication device are mounted. In this control board 5, the IC memory 53 stores a learning support program for realizing processing related to learning support, various setting data necessary for executing the learning support program, and the like. Then, the CPU 51 executes the learning support program to perform arithmetic processing, and controls each part of the learning device 10 in response to user operation inputs using the keyboard 13 and the mouse 3, thereby supporting the user's learning.

[0023] Note that the form of the learning device is not limited to the form of a notebook computer. For example, it can take the form of a smartphone, a tablet computer, a portable game device, or the like.

[0024] [Overview] The learning device 10 is a device that supports the user's learning by repeating a learning process of presenting problems, accepting answer inputs, and performing a correct / incorrect determination. The subjects (genres) that can be learned with the learning device 10 of the present embodiment include a determination target subject corresponding to the determination target genre and a non-target subject corresponding to the non-target genre. In the present embodiment, the learning device 10 performs a subject determination of the user's strong and weak subjects as an evaluation by genre based on learning data 160 (see FIG. 14) related to the learning process. The determination target subject is the subject that is the target of the subject determination, and the non-target subject is the subject that is not the target of the subject determination (for specific examples of subjects, see FIG. 10). For example, the determination target subjects are six general subjects including "Japanese", "Mathematics", and "English" which are basic subjects. On the other hand, the non-target subjects are composed of four special subjects, namely, the other three subjects and "Game" including learning menus such as an intellectual game. The other subjects include, for example, subjects including learning menus for which a correct / incorrect determination is not made for answer inputs such as a user freely drawing pictures or inputting characters, and subjects including learning menus with a determined execution order.

[0025] When the learning device 10 is started up for the first time, the learning levels of the user are initialized for each subject in, for example, five levels from "1" to "5". At that time, the level check of the user is appropriately performed. In the present embodiment, level checks are performed at the time of the first startup for three basic subjects, "Japanese", "Mathematics", and "English", among the regular subjects, and learning levels suitable for the academic ability are set. The method of the level check is not particularly limited, but test questions are presented for each subject, and the learning level of the subject is initially set according to the number of correct answers. For the three regular subjects other than the basic subjects and the four special subjects, the learning level is initially set to "1".

[0026] FIG. 2 is a diagram showing an example of a home screen W1 that is displayed when the initial setting of the learning level is made. As shown in FIG. 2, a plurality of menus including an "adventure mode" and a "free mode" are presented on the home screen W1 by their selection buttons.

[0027] 1. Regarding the adventure mode The adventure mode is a mode in which the user selects a world and a stage, and proceeds with the learning of each subject by selecting the learning menu presented for each cell. A predetermined character appears, and a voice that prompts the user to learn or an image that performs an action to support the user's learning is output. Also, as learning progresses, it becomes possible to acquire items and the like associated with the character. The items and the like are, for example, items that increase the variations of the voices emitted by the character, items that increase the variations of the images that perform actions, or items that change the clothing and equipment of the character.

[0028] In the adventure mode, first, a world is selected. A plurality of worlds are prepared, and they are released one by one in a predetermined order as learning progresses. Specifically, when all the stages constituting the first world are cleared, the second world can be selected. Each world is composed of a plurality of stages.

[0029] If the world is selected, then select a stage. Here, select one from the cleared stages that make up the selected world. Similar to the world, the stages are unlocked one by one in a predetermined order. Specifically, when all the squares that make up the first stage in the world are cleared, the second stage can be selected. Each stage is composed of a plurality of squares.

[0030] FIG. 3 is a diagram showing an example of the map screen W2 of one stage (stage E) of a certain world. As shown in FIG. 3, when a world is selected and a stage is selected, the map screen W2 of the selected stage is displayed.

[0031] On the map screen W2, a plurality of (six in the example of FIG. 3) squares 7 (7-1 to 6) that make up the stage are arranged side by side along the path from the start to the goal. When the user selects a square 7 on the map screen W2, the learning menu assigned to the square 7 is executed.

[0032] More specifically, in the selected stage, the user performs learning (more specifically, learning of the learning menu assigned to each square 7) one by one in order from the start square 7-1 for each square 7. When a learning session is completed and the learning menu is cleared, the next square 7 is unlocked and can be selected. If it cannot be cleared, the learning menu for the square 7 is executed again to repeat the learning and aim for clearance.

[0033] The map screen W2 in FIG. 3 shows an example where the user has cleared up to the third square 7-3 from the start. The three cleared squares 7-1, 2, 3, and the uncleared square 7-4 that has been released by clearing square 7-3 are in a selectable state. The stars displayed near each cleared square 7-1, 2, 3 indicate the evaluation of the learning at that square 7. In this embodiment, the learning at each square 7 is evaluated by the number of stars from 0 to 3. Since the user cannot proceed to the next square 7-5 without clearing the learning menu for square 7-4, at the time shown in FIG. 3, squares 7-5 and 7-6 cannot be selected. When the cursor of the mouse 3 (see FIG. 1) is placed over the selectable squares 7-1 to 4, the subject related to the learning menu assigned to the squares 7-1 to 4 and the type of question (the category of the questions presented in the learning menu; hereinafter referred to as the "question category") are displayed.

[0034] Also, on the map screen W2, a marker 71 indicating the daily clear goal (learning goal) is displayed. For example, learning for three squares per day is set as the clear goal, and the square 7 for achieving the clear goal is determined daily. Then, a marker 71 of a mark is displayed on the determined square 7 (square 7-5 in the example of FIG. 3).

[0035] Here, the reason for setting the number of squares as the clear goal per day to three is that the number of groups to be classified by the classification process described later is three. That is, in this embodiment, the ten subjects (see FIG. 10) that can be learned by the learning device 10 are grouped into three types: a favorite group of favorite subjects, an unfavorite group of unfavorite subjects, and an other group of special subjects. Then, the selected subjects are selected in the order of FIG. 9(b) from each group and assigned to each square. Therefore, by setting the clear goal per day to three squares, it is possible to prompt the user to learn the subjects of each group at least once a day. That is, it is possible to prompt the user to learn the favorite subjects, unfavorite subjects, and special subjects one by one in a planned manner in one day.

[0036] However, the number of squares to be cleared per day is not limited to three. In that case as well, it is advisable to set the number to a predetermined multiple of the number of groups. This is because by aiming to achieve the clearance goal, users can study their strong, weak, and special subjects in a well-balanced manner. Also, although an example of the clearance goal per day was given as an example of the clearance goal per predetermined period, the predetermined period can also be set to one week, and the clearance goal per week, etc. can be set.

[0037] FIG. 4 and FIG. 5 are diagrams showing an example of a learning screen W3 that is displayed when one square 7 is selected on the map screen W2. FIG. 4 shows an example where the subject of the learning menu assigned to the square 7 is "mathematics" and the question category is "addition". When the user selects an answer from the answer field 73 at the bottom of the screen, as shown in FIG. 5, the result of the correct / incorrect determination is displayed.

[0038] 2. Regarding the learning menu The learning menu is prepared in advance for each subject (in this embodiment, for each of the 10 subjects in FIG. 10). FIGS. 6 and 7 are diagrams showing an example of the data configuration of a learning menu list 153 in which the learning menus for each subject are registered. FIG. 6 shows an example of the learning menu list 153 (153-1) for the subject "mathematics" which is the subject to be judged, and FIG. 6 also shows an example of the learning menu list 153 (153-2) for the non-target subject "music / art". For each subject's learning menu list 153, a question category, a level, a question to be asked, the number of questions to be asked, a correct / incorrect determination flag, a clearance determination method, and an evaluation method are set in association with a unique learning menu ID for each learning menu.

[0039] The question category is the type of questions presented in the learning menu (the category of questions to be presented). In the learning menu list 153-1 in FIG. 6, examples of the question categories for the subject "mathematics" are "addition", "subtraction", and "multiplication sign". The question numbers of the questions to be presented in the learning menu are stored in the presented questions. The number of questions presented stores the number of questions to be presented in the learning menu. The presented questions will have the corresponding question numbers set for the corresponding number of questions presented. For example, there are learning menus (such as record D11 in FIG. 6) where it is stated as "5 questions" and multiple question numbers are set for the presented questions, and there are also learning menus with "1 question" (such as record D2 in FIG. 7).

[0040] In this embodiment, for each of the question categories related to the corresponding subject, a plurality of learning menus are prepared for each level from "1" to "5". And for the presented questions of each learning menu, the question numbers of the question data 155 (refer to FIG. 14) that define the questions of the corresponding level of the corresponding question category among the pre-prepared question data 155 are set. For learning menus with the same question category but different levels (for example, between record D11 and record D13 in FIG. 6), in addition to the difficulty level of the corresponding questions, the number of options to be displayed in the answer column (refer to the answer column 73 in FIG. 4) when presenting the questions is appropriately different.

[0041] The correct / incorrect judgment flag is flag information indicating whether to perform correct / incorrect judgment on the questions presented in the learning menu (ON: perform / OFF: not perform). For example, as shown in FIG. 6, in the learning menu list 153-1 for the subject "mathematics" which is the subject to be judged, all the correct / incorrect judgment flags are set to "ON". On the other hand, as shown in FIG. 7, in the learning menu list 153-2 for the non-target subject "music and art", there are learning menus such as record D2 where the correct / incorrect judgment flag is "OFF".

[0042] For the clearance determination method, a method for determining whether the learning menu has been cleared or not is set. For example, for a learning menu in which a plurality of questions are set as the corresponding number of questions to be answered, if the number of correct answers is "0", it is determined as a clearance failure, and if the number of correct answers is "1" or more, it is determined as a clearance success. A learning menu with a setting that all clearances are successful when learning is completed is also appropriately included.

[0043] For the evaluation method, a method for calculating the number of stars to be given as an evaluation of the learning when the user finishes learning related to the learning menu is set. For example, as an evaluation method when the corresponding correct / incorrect determination flag is "ON" and the number of questions to be answered is "5", if the number of correct answers is "0", the number of stars is 0; if the number of correct answers is "1" or "2", the number of stars is 1; if the number of correct answers is "3" or "4", the number of stars is 2; and if all questions are answered correctly, the number of stars is 3. For the learning menu of special subjects, etc., a learning menu with a setting that the number of stars is uniformly calculated as 3 when learning is completed can also be included.

[0044] 3. Regarding the learning menu execution process FIG. 8 is a flowchart showing the flow of learning menu execution processing performed by the learning device 10 in accordance with the selection of a cell on the map screen. In the learning menu execution processing, the learning device 10 executes learning processing for a subject related to the learning menu according to the learning menu assigned to the cell. Basically, the learning device 10 performs problem posing (step S101), acceptance of a user's answer input for the problem (step S103), and determination of the correctness of the answer input (step S105) according to the setting of the problem to be posed in the learning menu as one learning process. When the correct / incorrect determination flag related to the learning menu is "OFF", the correct / incorrect determination in step S105 is not performed. Then, according to the setting of the number of problems to be posed, when the learning menu is a learning menu that poses multiple problems, the learning processes of steps S101 to S105 are repeated for each problem. Then, when the learning device 10 has performed learning processing for all problems and the user has finished learning (step S107: YES), a clearance determination is made (step S109). The clearance determination is made according to the setting of the clearance determination method for the learning menu.

[0045] Subsequently, when the learning device 10 determines that the clearance is successful in step S109, it evaluates the user's current learning by the learning processes in steps S101 to S105 according to the evaluation method of the learning menu, and calculates the number of stars (step S111).

[0046] In addition, when the learning device 10 determines that the learning menu has been cleared as a result of the clearance determination in step S109 and satisfies a predetermined granting condition, it grants a clearance reward to the user (step S113). For example, a clearance reward such as an item is determined in advance for each cell that is a reward granting location, and it is determined with conditions such as "being the first clearance of the learning menu assigned to the reward granting location", and the corresponding item or the like is granted to the user.

[0047] Then, the learning device 10 determines whether to update the learning level of the user for the subject related to the learning menu and updates the learning level of the subject (step S115). In the present embodiment, for example, when the number of stars calculated in step S111 is 3, the learning device 10 performs a level-up determination. Specifically, first, from the subject-specific learning level transition data 180 (see FIG. 17) of the learning data 160, the learning in which the learning level of the subject has been leveled up to the current level is specified. Then, among the learnings for each cell after the level-up, the learnings in which the calculated number of stars (hereinafter also referred to as "acquired star number") is 3 are counted. When it reaches 5 times this time, it is determined that the level is raised by one and the learning level of the subject is updated. Further, when the number of stars calculated in step S111 is 0 or 1, a level-down determination is performed. That is, first, from the subject-specific learning level transition data 180 (see FIG. 17) of the learning data 160, the learning in which the learning level of the subject has been leveled up to the current level is specified. Then, among the learnings for each cell after the level-up, the learnings in which the acquired star number is 0 or 1 are counted. When it reaches 5 times this time, it is determined that the level is lowered by one and the learning level of the subject is updated.

[0048] 3. Regarding the free mode The free mode is a mode in which the user selects and executes a desired learning menu from among the subject-specific learning menus. At that time, the user can also freely select the level. Therefore, the user can lower the level and review the learning menu of the subject that the user is not good at among the learning menus executed in the adventure mode, or challenge the learning menu of the subject that the user is good at at a level higher than the user's current learning level. Also, when there are strengths and weaknesses depending on the question category even for the same subject, it is also possible to execute the learning menu focusing on a specific question category and repeat the learning.

[0049] [Details] The execution of the learning menu for each cell in the above-described adventure mode is realized by assigning a learning menu to the cell when the cell is unlocked. FIG. 9 is a diagram for explaining the assignment of the learning menu to cell 7, showing the map screen W2 shown in FIG. 3 (FIG. 9(a)) and the order of assignment (FIG. 9(b)). In the present embodiment, when unlocking cell 7, the learning device 10 selects a subject and assigns a learning menu so that the subjects of the learning menus to be assigned repeat in the order of "favorite subject", "weak subject", and "special subject" shown in FIG. 9(b).

[0050] A favorite subject is a subject that the user is good at among the six general subjects that are the subjects to be judged. A weak subject is a subject that the user is not good at (poor at) among the subjects to be judged (general subjects). For example, in the example of FIG. 9(a), assume that the subject "English" of the learning menu of the unlocked cell 7-2 is a favorite subject, and the subject "mathematics" of the learning menu of cell 7-3 is a weak subject. The subject "music·architecture" of the learning menu of cell 7-4 is a special subject. In that case, when the user clears cell 7-4 from the state of FIG. 9(a) and newly unlocks cell 7-5, since the next order is a favorite subject, a learning menu of a favorite subject is assigned.

[0051] According to the assignment of the learning menu in the above order, the user can first learn favorite subjects and then learn weak subjects. Also, a special subject can be learned after learning a weak subject. Therefore, it is possible to proceed with learning without getting bored while learning favorite subjects and special subjects even if there are weak subjects, without being biased towards learning favorite subjects. Also, as will be described in detail later, in the present embodiment, the determination of favorite subjects and weak subjects (subject determination) is performed in consideration of the results of the learning each time the user finishes learning for each cell. Therefore, it is possible to appropriately reflect the user's strengths and weaknesses, determine favorite subjects and weak subjects, and then select a subject and assign a learning menu.

[0052] Specifically, as a process therefor, the learning device 10 first performs a classification process of classifying a plurality of general subjects into a plurality of groups. Then, the learning device 10 performs an execution control process including a learning menu assignment process related to the selection of a subject and the assignment of a learning menu in the order of (b) in FIG. 9, and a learning menu execution process of executing the learning menu (see FIG. 8).

[0053] 1. Regarding the classification process FIG. 10 is a diagram for explaining the classification process. In the present embodiment, prior to the classification process, the learning device 10 performs a subject determination on the subject to be determined to determine the user's strong and weak subjects. Then, in the classification process, the learning device 10 classifies the subject to be determined and the non-target subjects (in the present embodiment, 10 subjects) into a strong group that is a group of general subjects determined to be strong subjects as a result of the subject determination, a weak group that is a group of general subjects determined to be weak subjects, and another group that is a group of special subjects. In the example of FIG. 10, an example is shown in which three of the subjects to be determined (general subjects), namely, "Japanese", "English", and "life", are classified into the strong group as strong subjects, and three of them, namely, "mathematics", "science", and "computer", are classified into the weak group as weak subjects. Since the non-target subjects are composed of special subjects, they are classified into the other group.

[0054] FIG. 11 is a diagram showing an example of subject determination. In subject determination, the learning device 10 first sorts the six general subjects, which are the subjects to be determined, in descending order of the user's learning level. Subsequently, when there are subjects with the same rank in the sorting result (subjects with the same learning level) (in the example of FIG. 11, two pairs: "English" and "Science", and "Life" and "PC"), for each corresponding subject, the learning device 10 calculates the average value (average star count) of the number of stars acquired in each cell to which the learning menu for that subject is assigned. Then, the learning device 10 rearranges the subjects with the same rank in descending order of the average star count. Subsequently, when there are still subjects with the same rank (in the example of FIG. 11, "Life" and "PC"), for each corresponding subject, the learning device 10 counts the number of cells with 3 stars (number of times of 3 stars) among the cells to which the learning menu for that subject is assigned. Then, the learning device 10 rearranges the subjects with the same rank in descending order of the number of times of 3 stars. If the learning device 10 ranks the subjects to be determined (here, six general subjects) according to the above processing procedure, the learning device 10 determines the top three general subjects among the subjects to be determined (in the example of FIG. 11, "Japanese", "Mathematics", "English") as the favorite subjects, and determines the bottom three general subjects (in the example of FIG. 11, "Science", "Life", "PC") as the unfavorite subjects.

[0055] 2. Regarding Execution Control Processing In the execution control processing, the learning device 10 repeatedly executes a series of processes including selection of a selected group from among a plurality of groups, selection of a selected subject from among the subjects belonging to the selected group, and learning processing regarding the selected subject. In the present embodiment, when releasing a cell, the learning device 10 performs learning menu assignment processing to select a selected group and a selected subject. When the user selects the cell on the map screen, the learning device 10 performs the above-described learning menu execution processing (see FIG. 8) to execute learning processing. When the user clears the learning menu for the cell, a new cell is released, and thus the series of processes is repeated.

[0056] FIG. 12 is a flowchart showing the flow of learning menu assignment processing. In the learning menu assignment processing, the learning device 10 first selects a selection group based on the classification result in the classification processing (step S201). In the present embodiment, in order to realize the selection of the selected subject in the order shown in FIG. 9(b), the selection of the selection group in the repetition of a series of processes is such that the selection group is selected in the order of (1) good-at group, (2) not-good-at group, and (3) other group. It can be realized by selecting the next-order group based on the selection group selected at the time of releasing the previous cell (during the previous series of processes). For example, if the previous selection group was the good-at group, the not-good-at group is selected as the selection group. By the processing here, the suppression control of continuous selection as the selection group of the same group in a series of continuous processes is realized. Here, the above order is also the order in which the not-good-at group is selected as the selection group after the good-at group is first selected as the selection group in two consecutive series of processes. However, it is not limited to the illustrated order, and another order in which the order of (1) to (3) is rearranged may be used. For example, it can be the order in which the not-good-at group is first selected as the selection group and then the good-at group is selected as the selection group. The order of selecting the other group between the good-at group and the not-good-at group may also be used.

[0057] If the selection group is selected, the learning device 10 selects a selected subject from among the subjects belonging to the selection group (step S203). In the present embodiment, the learning device 10 performs the selection of the selected subject from the same group in order based on the in-group ranking related to the same group in a series of continuous processes. FIG. 13 is a diagram for explaining the selection of the selected subject here. FIG. 13 illustrates the case where the selection group selected in the previous process is the not-good-at group.

[0058] As shown in FIG. 13, in this embodiment, priority orders are determined in advance for six general subjects, and the selection of the selected subject is performed with the order based on the priority order as the in-group order. Specifically, first, the learning device 10 uses the priority orders of the six general subjects to sort the subjects belonging to the selection group (here, the three subjects "mathematics", "science", and "computer", which are classified into the non-good-at group among the six general subjects) in the order of priority to obtain the in-group order.

[0059] Subsequently, the learning device 10 assigns index numbers "1", "2", and "3" to each subject in the selection group in the order of the sorted in-group order. Then, the learning device 10 uses the assigned index numbers to select a selected subject from the subjects in the selection group according to a previously prepared random number table. The random number table defines an array of index numbers and is prepared for each of the good-at group, the non-good-at group, and the other group. It is also possible to use a common random number table for all groups. Here, the learning device 10 selects the selected subject by sequentially referring to the random number table (array of index numbers) for the non-good-at group from the beginning. In the example of FIG. 13, the subject "science" with the index number "3" that the reference pointer P is referring to is selected as the selected subject. Once the selected subject is selected using the index number of the reference destination, the reference pointer is shifted to the next one.

[0060] Returning to FIG. 12. If the selected subject is selected, then subsequently, the learning device 10 determines whether the selected subject selected at the time of releasing the previous cell (during the previous series of processes) is the same subject as the selected subject selected in step S203 this time. If the learning device 10 determines that they are the same subject (step S205: YES), the learning device 10 reselects the selected subject (step S207). In that case, the subject "computer" with the index number "2", which is the next reference destination of the reference pointer P, will be selected as the selected subject. According to the processing here, consecutive selections of the same subject as the selected subject are suppressed, and the same-genre consecutive selection suppression control is realized.

[0061] After that, the learning device 10 refers to the learning menu list 153 of the selected teaching subject selected in step S203 or reselected in step S207, and selects one from the learning menus of the level that matches the learning level of the selected teaching subject among the registered learning menus (step S209). The selection here may be made after excluding the already assigned learning menus. Then, the learning device 10 assigns the learning menu of the selected teaching subject selected in step S209 to the newly released cell (step S211).

[0062] [Functional Configuration] FIG. 14 is a block diagram showing a functional configuration example of the learning device 10. As shown in FIG. 14, the learning device 10 includes an operation input unit 111, a display unit 113, a sound output unit 115, a processing unit 130, and a storage unit 150.

[0063] The operation input unit 111 is for the user to input various operations, and can be realized by a keyboard, a mouse, a touch panel, etc. In FIG. 1, the keyboard 13 and the mouse 3 correspond to this. The display unit 113 is realized by a display device such as an LCD (Liquid Crystal Display) or a touch panel, and performs various displays according to the display signal from the processing unit 130. In FIG. 1, the display 15 corresponds to this. The sound output unit 115 is realized by a speaker or the like, and emits the voice signal input from the processing unit.

[0064] The processing unit 130 can be realized by a processor which is an arithmetic circuit such as a CPU, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), etc., and electronic components such as an IC memory, and performs input / output control of data with each part of the device. Then, various arithmetic processes are performed based on a predetermined program, data, an operation input signal from the operation input unit 111, etc., and the operation of the learning device 10 is comprehensively controlled. In FIG. 1, the control board 5 and its CPU 51 correspond to this.

[0065] In the present embodiment, the processing unit 130 includes a subject determination unit 131 as a genre-specific evaluation unit, a classification unit 133, and an execution control unit 135.

[0066] The subject determination unit 131 is a functional unit that performs subject determination. In the present embodiment, for each determination target subject (ordinary subject), the subject determination unit 131 determines the learning level of the subject, the average star rating related to the subject, and the number of times of three stars related to the subject, and determines the user's strong and weak subjects among the ordinary subjects.

[0067] The classification unit 133 is a functional unit that performs classification processing. In the present embodiment, based on the result of the subject determination by the subject determination unit 131, the classification unit 133 classifies the 10 subjects (see FIG. 10) that can be learned by the learning device 10 into three types of groups: a strong group, a weak group, and an other group.

[0068] The execution control unit 135 is a functional unit that performs execution control processing. In the present embodiment, when the user newly clears a cell, the execution control unit 135 executes learning menu assignment processing using the classification result by the classification unit 133, and performs learning menu execution processing according to the selection operation of the cell by the user, thereby realizing a series of processes including selection of the selected group, selection of the selected subject, and learning processing related to the selected subject. And when selecting the selected group, the execution control unit 135 performs suppression control to suppress continuous selection as the selected group of the same group in a series of processes by selecting one from the strong group, the weak group, and the other group as the selected group in a predetermined order (see (b) of FIG. 9). Also, when selecting the selected subject, if the same subject as the selected subject selected in the previous series of processes is selected, the execution control unit 135 reselects the selected subject.

[0069] In the storage unit 150, programs for operating the learning device 10 and realizing various functions of the learning device 10, data used during the execution of this program, etc. are stored in advance, or temporarily stored each time processing is performed. For example, it can be realized by an IC memory such as a RAM or a ROM, a hard disk, or the like. In FIG. 1, the IC memory 53 corresponds to this.

[0070] Also, in the storage unit 150, a learning support program 151, a learning menu list 153 by subject (see FIGS. 6 and 7), problem data 155, mass-specific learning menu assignment data 157, and learning data 160 are stored.

[0071] The learning support program 151 is a program for causing the processing unit 130 to function as a subject determination unit 131, a classification unit 133, and an execution control unit 135.

[0072] The problem data 155 is prepared for each problem number set as a question to be presented in each of the learning menu lists 153 by subject, and stores various data such as questions, answers, and data of options to be displayed in the answer column of the learning screen at the time of question presentation.

[0073] The mass-specific learning menu assignment data 157 stores various data related to the assignment of learning menus to masses. FIG. 15 is a diagram showing an example of the data configuration of the mass-specific learning menu assignment data 157. As shown in FIG. 15, the mass-specific learning menu assignment data 157 is a data table in which a release flag, a learning menu ID, a subject, assignment time classification information, a clear flag, and the number of stars acquired are set in association with a unique mass ID for each mass.

[0074] The release flag is flag information indicating whether the mass has been released (ON: released / OFF: not released).

[0075] The learning menu ID is the learning menu ID of the learning menu assigned to the mass, and the subject stores the subject related to the learning menu.

[0076] The assignment classification information stores the type of the selected group (i.e., the group to which the corresponding subject belonged at the time of release) when releasing the cell.

[0077] The clear flag is flag information indicating whether the learning menu of the cell has been cleared (ON: cleared / OFF: not cleared).

[0078] The number of acquired stars stores the number of stars calculated as an evaluation of the learning of the cell. When the number of stars is updated (increased) as a result of repeated learning of the cell, it is rewritten with the number of stars.

[0079] The learning data 160 includes the per-cell learning data 170 and the per-subject learning level transition data 180.

[0080] The per-cell learning data 170 is generated when a cell is released and is updated by reflecting the learning results each time the learning menu assigned to the cell is executed. Specifically, as shown in FIG. 16, one per-cell learning data 170 stores the cell ID 171 of the cell, the learning menu ID 172 of the learning menu assigned to the cell, the subject 173 related to the learning menu, the assignment classification information 174, the clear flag 175, the number of acquired stars 176, and the learning history 177.

[0081] The number of acquired stars 176 is the number of stars calculated for the learning of the cell and is rewritten at any time when the learning is repeated and the number of stars is updated.

[0082] The learning history 177 is prepared for each learning in the cell and stores the result of the correct / incorrect judgment for each question at the time of the learning, the number of acquired stars in the learning, etc.

[0083] The subject-specific learning level transition data 180 is prepared for each subject and stores the transition of the learning level of each subject associated with the learning for each user's cell. FIG. 17 is a diagram showing an example of the data configuration of one subject-specific learning level transition data (in FIG. 17, the subject-specific learning level transition data for the subject of "mathematics") 180. As shown in FIG. 17, the subject-specific learning level transition data 180 stores, in the learning order for each cell to which the learning menu of the corresponding subject (in FIG. 17, "mathematics") is assigned, the cell ID, the number of stars acquired during the learning, and the learning level of the subject at the time when the learning is completed. When the user selects a cell to which the learning menu of the subject is assigned and performs learning, one record regarding the learning is added to the subject-specific learning level transition data 180. According to this subject-specific learning level transition data 180, the transition of the user's learning level associated with the learning for each cell can be grasped. In the present embodiment, the subject-specific learning level transition data 180 is referred to when determining the update of the learning level (level-up determination and level-down determination).

[0084] [Flow of processing] FIG. 18 is a diagram showing the flow of processing performed by the learning device 10 when a cell is selected on the map screen. The processing described here is realized by the processing unit 130 reading and executing the learning support program 151.

[0085] As shown in FIG. 18, when a cell is selected by the user (step S301: YES), the execution control unit 135 executes the learning menu execution process (refer to FIG. 8) and executes the learning menu assigned to the selected cell (step S303). By the processing here, the learning process regarding the subject related to the learning menu is realized.

[0086] And when the user clears the learning menu and it is the first time to clear it (step S305: YES), in order to newly release the squares, first, the subject determination unit 131 performs the subject determination described with reference to FIG. 11, and determines the user's strong and weak subjects for each of the general subjects that are the subjects to be determined (step S307). Then, the classification unit 133 performs classification processing (step S309). Here, the classification unit 133 classifies the subjects to be classified into a strong group that is a group of general subjects determined to be strong subjects in the subject determination of step S307, a weak group that is a group of general subjects determined to be weak subjects in the subject determination, and another group that is a group of special subjects.

[0087] Subsequently, the execution control unit 135 performs learning menu assignment processing (refer to FIG. 12) (step S311). Here, the execution control unit 135 selects a selection group from among the three types of groups classified in step S309, selects a selection subject from among the subjects belonging to the selection group, and assigns the learning menu of the selection subject to the square to be released by selecting one.

[0088] Thereafter, an end determination is made, and until it is determined to end (step S311: YES), the process returns to step S301 and the above-described process is repeated. When the square newly released by the user is selected, the learning menu thereof is executed in step S303, and a series of processes are realized.

[0089] As described above, according to the present embodiment, by sequentially releasing the cells that make up the stage, assigning learning menus for each subject, and executing the learning menus, a learning process is realized in which questions for the corresponding subject are presented, answer inputs are received, and correct / incorrect judgments are made. Further, when newly releasing a cell, each subject can be classified into a good-at group, a not-good-at group, and other groups, a selection group can be selected, a selected subject can be selected from among the selection groups, and a learning menu for the selected subject can be assigned to the cell. Then, when the released cell is selected, by executing the learning menu, a series of processes of selecting the selection group, selecting the selected subject, and performing the learning process related to the selected subject can be repeated. Further, when selecting the selection group, by selecting one from among the good-at group, the not-good-at group, and other groups as the selection group in a predetermined order, it is possible to suppress consecutive selections as the selection group of the same group. According to this, it becomes possible to uniformly support the learning of the user by genre.

[0090] In addition, in the above embodiment, an example in which the subjects that can be learned by the learning device 10 are classified into three types of groups has been described, but a configuration in which they are classified into two types of groups or a configuration in which they are classified into four or more types of groups may also be used. For example, a "normal group" of normal subjects that are neither good at nor not good at may be added to the "good-at group", "not-good-at group", and "other groups" exemplified in the above embodiment, and they may be classified into four types of groups. The classification in that case can be realized by dividing the normal subjects into three levels: upper, middle, and lower, based on the results of the subject determination illustrated in FIG. 11.

[0091] In addition, in the above embodiment, an example has been described in which the subject determination is performed every time the learning menu is cleared (every time a cell is released), and the classification of the subjects (for example, grouping into a "good-at group", "not-good-at group", and "other groups") is updated. On the other hand, a configuration may be adopted in which the classification of the subjects (grouping into a "good-at group", "not-good-at group", and "other groups") is updated every time a predetermined order (for example, the order in FIG. 9(b)) is completed.

[0092] In the above embodiment, textbooks are cited as an example of the genre. However, for example, it can be similarly applied when assisting learning for genres of learning for preschool children, genres of learning for adults, etc.

[0093] 〔Summary〕 The disclosure of this specification according to the above-described embodiment can be summarized as follows.

[0094] A first aspect is an information processing apparatus that executes learning processing including problem posing, reception of a user's answer input for the problem, and correct / incorrect determination of the answer input for each genre, and a classification unit that classifies each genre into a plurality of groups using at least the result of genre-by-genre evaluation based on learning data related to the learning processing, and a selection of a selected group from among the plurality of groups, a selection of a selected genre from among the genres belonging to the selected group, and an execution control unit that executes a series of processes including the learning processing related to the selected genre, and in the series of consecutive processes, an execution control unit that performs suppression control to suppress consecutive selection of the same group as the selected group.

[0095] According to the first aspect, a series of processes including classifying a genre into a plurality of groups, selecting a selected group from among the plurality of groups, selecting a selected genre from among the genres belonging to the selected group, and learning processing related to the selected genre are executed. And in the series of processes, consecutive selection of the same group as the selected group is suppressed. According to this, it becomes possible to uniformly support the user's genre-by-genre learning.

[0096] Also, as a second aspect, there are three or more types of groups including a favorite group and an unfavorite group, and in two consecutive series of the processes, the execution control unit selects one of the favorite group and the unfavorite group as the selected group and then selects the other group as the selected group, and the information processing apparatus according to the first aspect may be configured.

[0097] According to the second aspect, when classifying genres into three or more types of groups, by selecting one of the favorite group and the unfavorite group and then selecting the other group, it is possible to suppress consecutive selection of the same group in two consecutive series of processes.

[0098] Also, as a third aspect, there are three or more types of groups including a favorite group and an unfavorite group, and in two consecutive series of the processes, the execution control unit selects the favorite group as the selected group first and then selects the unfavorite group as the selected group, and the information processing apparatus according to the first aspect may be configured.

[0099] According to the third aspect, when classifying genres into three or more types of groups, by selecting the favorite group first and then the unfavorite group, it is possible to suppress consecutive selection of the same group in two consecutive series of processes.

[0100] Also, as a fourth aspect, the execution control unit may configure the information processing apparatus according to the first aspect to perform the suppression control by selecting the selected group from among the plurality of groups in a predetermined order in the consecutive series of processes.

[0101] According to the fourth aspect, by selecting each group in a predetermined order, it is possible to suppress consecutive selection of the same group in a series of processes.

[0102] Also, as a fifth aspect, the classification unit may configure an information processing apparatus according to any one of the first to fourth aspects, which updates the classification of each genre every time the learning process for a predetermined number of times is completed.

[0103] According to the fifth aspect, for example, it becomes possible to update the classification of each genre every time the learning process regarding the selected genre is completed.

[0104] Also, as a sixth aspect, the classification unit may configure an information processing apparatus according to the fourth aspect, which updates the classification of each genre every time the order of the group selected as the selected group makes a full cycle.

[0105] According to the sixth aspect, when the selection of the selected group is performed in a predetermined order, the classification of each genre can be updated every time the order of the selection makes a full cycle.

[0106] Also, as a seventh aspect, the execution control unit may configure an information processing apparatus according to the fifth or sixth aspect, which performs the same genre consecutive selection suppression control for suppressing consecutive selection of the same genre as the selected genre.

[0107] According to the seventh aspect, it is possible to suppress consecutive selection of the same genre as the selected genre.

[0108] Also, as an eighth aspect, the group includes a favorite group, an unfavorite group, and other groups, the genre includes a determination target genre that is the target of genre-by-genre evaluation and a non-target genre that is not the target of genre-by-genre evaluation, and the classification unit classifies the determination target genre into the favorite group and the unfavorite group, and classifies the non-target genre into the other group, and may configure an information processing apparatus according to any one of the first to seventh aspects.

[0109] According to the eighth aspect, it is possible to classify the genres for which genre-by-genre evaluation is performed into a favorite group and an unfavorite group, and classify the genres for which genre-by-genre evaluation is not performed into other groups.

[0110] Also, as a ninth aspect, a genre-specific evaluation unit that performs the genre-specific evaluation by determining the level of proficiency or non-proficiency for each genre based on the learning data updated in response to the execution of the learning process may be further provided to configure an information processing apparatus according to any one of the first to eighth aspects.

[0111] According to the ninth aspect, genre-specific evaluation can be performed using the level of proficiency or non-proficiency for each genre of the user determined based on the learning data related to the learning process.

[0112] Also, as a tenth aspect, the classification unit determines the in-group ranking of the genres belonging to each classified group, and the execution control unit sequentially selects the selected genre from the same group based on the in-group ranking related to the same group, and an information processing apparatus according to any one of the first to ninth aspects may be configured.

[0113] According to the tenth aspect, the genres belonging to each group can be ranked for each group, and the selected genre from the same group can be sequentially selected using the ranking.

[0114] Also, as an eleventh aspect, the execution control unit sets, as the learning goal of the user, to execute a number of the learning processes corresponding to a predetermined multiple of the number of the groups within a predetermined period, and performs display control indicating the learning goal, and an information processing apparatus according to any one of the first to tenth aspects may be configured.

[0115] According to the eleventh aspect, it becomes possible to set the learning goal for each predetermined period of the user based on the number of groups and present the set learning goal to the user.

[0116] Also, as a twelfth aspect, a program for causing a computer to execute a learning process including problem posing, accepting a user's answer input for the problem, and determining the correctness of the answer input for each genre, the program comprising: a classification unit that classifies each genre into a plurality of groups using at least the result of genre-specific evaluation based on learning data related to the learning process; an execution control unit that executes a series of processes including selection of a selected group from among the plurality of groups, selection of a selected genre from among the genres belonging to the selected group, and the learning process related to the selected genre, the execution control unit performing suppression control to suppress consecutive selection of the same group as the selected group in consecutive executions of the series of processes. The program may be configured to function the computer as the execution control unit.

[0117] According to the twelfth aspect, a program that achieves the same effect as the first aspect can be realized.

Explanation of Signs

[0118] 10…Learning device 111…Operation input unit 113…Display unit 115…Sound output unit 130…Processing unit 131…Subject determination unit 133…Classification unit 135…Execution control unit 150…Storage unit 151…Learning support program 151…Learning support program 153…Learning menu list 155…Problem data 157…Learning menu assignment data by block 160…Learning data 170…Learning data by block 180…Subject-specific learning level transition data

Claims

1. An information processing apparatus that executes learning processing including problem posing for each genre, accepting a user's answer input for the problem, and determining the correctness of the answer input, a classification unit that classifies each genre into a plurality of groups using at least the result of genre-specific evaluation based on learning data related to the learning processing, an execution control unit that executes a series of processes including selection of a selected group from among the plurality of groups, selection of a selected genre from among the genres belonging to the selected group, and the learning processing related to the selected genre, and in the series of consecutive processes, the execution control unit performs suppression control to suppress consecutive selection of the same group as the selected group, An information processing apparatus comprising the above.

2. There are three or more types of groups including a proficient group and a non-proficient group, in two consecutive series of the processes, the execution control unit selects one of the proficient group and the non-proficient group as the selected group and then selects the other group as the selected group, The information processing apparatus according to Claim 1.

3. There are three or more types of groups including a proficient group and a non-proficient group, in two consecutive series of the processes, the execution control unit first selects the proficient group as the selected group and then selects the non-proficient group as the selected group, The information processing apparatus according to Claim 1.

4. in the series of consecutive processes, the execution control unit performs the suppression control by selecting the selected group from among the plurality of groups in a predetermined order, The information processing apparatus according to Claim 1.

5. each time the learning processing for a predetermined number of times is completed, the classification unit updates the classification of each genre, The information processing apparatus according to Claim 1.

6. each time the order of the groups selected as the selected group makes a full circle, the classification unit updates the classification of each genre, The information processing apparatus according to Claim 4.

7. the execution control unit performs same-genre consecutive selection suppression control to suppress consecutive selection of the same genre as the selected genre, The information processing apparatus according to Claim 5 or 6.

8. the groups include a proficient group, a non-proficient group, and other groups, The genre includes a determination target genre that is the target of the genre-specific evaluation and a non-target genre that is not the target of the genre-specific evaluation. The classification unit classifies the determination target genre into the proficient group and the non-proficient group, and classifies the non-target genre into the other group. The information processing apparatus according to claim 1.

9. A genre-specific evaluation unit that performs genre-specific evaluation by determining the level of proficiency or non-proficiency for each genre based on the learning data updated in response to the execution of the learning process. The information processing apparatus according to claim 1, further comprising the same.

10. The classification unit determines the in-group ranking of the genres belonging to each classified group. The execution control unit sequentially selects the selected genre from the same group based on the in-group ranking related to the same group. The information processing apparatus according to claim 1.

11. The execution control unit sets, as the learning goal of the user, to execute a number of the learning processes corresponding to a predetermined multiple of the number of the groups within a predetermined period, and performs display control indicating the learning goal. The information processing apparatus according to claim 1.

12. A program for causing a computer to execute a learning process including, for each genre, presenting a problem, accepting an answer input by the user to the problem, and determining the correctness of the answer input. A classification unit that classifies each genre into a plurality of groups using at least the result of genre-specific evaluation based on the learning data related to the learning process. An execution control unit that executes a series of processes including selection of a selected group from among the plurality of groups, selection of a selected genre from among the genres belonging to the selected group, and the learning process related to the selected genre, and performs suppression control to suppress consecutive selection of the same group as the selected group in the consecutive series of processes. A program for causing the computer to function as such.

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