JP2001202000A - Learning system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To automatically select the combination of teaching materials which can be mastered in the shortest time or the combination of teaching materials which brings out most the learning effect according to a user's schedule inputted by the user by preparing the teaching materials with a plurality of media to the same unit. SOLUTION: The learning system has as a database the correspondence of education and each unit constituting it, the correspondence of the unit and a plurality of teaching materials for learning it, and the correspondence of teaching materials and the action classification which can be used with the teaching materials. By matching the action classification for every time zone of the schedule inputted by the user with the teaching materials in the database by all time searches, and by evaluating each combination, the combination of the teaching materials having the shortest acquisition time or the combination having the highest evaluation value by the valuation basis prepared previously can be determined.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to a system for supporting learning.

[0002]

2. Description of the Related Art Conventionally, a general method of learning alone is to read, listen, and view reference materials, cassette tapes, VTRs, and other teaching materials in the order intended by the creator of the teaching materials. Met. In the case of self-education using a reference book or the like, the order of the items to be learned is determined according to the user's will, and there is a case where the user learns from a favorite place. In correspondence education, books, cassette tapes, VTRs
In some cases, a combination of multiple teaching materials was used to provide education according to one curriculum.

[0003]

Conventionally, there are mainly three methods for learning all contents of a specific range (for example, mathematics to be acquired in the third grade of junior high school) using teaching materials. The first method uses a single teaching material (for example, junior high school 3).
Reference book that covers all the mathematics to be acquired in a year)
Is learned in the order assumed by the creator of the teaching material. The second method is a method in which a learner selects one or a plurality of teaching materials and selects which parts of the teaching materials to write using in what order and in which order. The third method is similar to the first method, but is configured so that the learning content can be effectively learned by learning by combining a plurality of media teaching materials (for example, a book and a VTR) in a certain order. This is a method of learning using teaching materials.

[0004] There are two problems in learning using the first method. The first problem is that the educational effect is limited by the type of the media of the teaching material. For example, depending on the educational content, it may be better to look at a VTR than to read a reference book, or vice versa. In the case of single-media teaching materials, the use of other media limits the educational benefits that might be possible. The second problem is that there is a limit in shortening the period required for completing the education due to restrictions on places and time where the media can be used. For example, you may not be able to read reference books on a crowded train, but you may be able to learn with a portable cassette recorder. Even if you can use a cassette recorder in a crowded train to learn some units, if you want to learn everything in a reference book, you can not use the time you are on the crowded train for learning However, there is a problem that it is not possible to shorten the time required for completing the acquisition of the entire educational contents.

Next, consider a case where learning is performed using the second method. In this case, if the user selects the teaching material in the correct manner, it is possible to learn in a short time using the most effective teaching material for each learning item. However, since users are originally trying to learn things they do not know, it cannot be expected that they will always make the right decision on which teaching material to use. In addition, when learning with "knack eating" a plurality of teaching materials,
It is also difficult to check for missing items to learn.

Next, consider the case of learning using the third method. In this case, if you study according to the curriculum, one of the problems when using the first method is "restriction on the improvement of educational effect possible by using other media".
Can be solved by preparing the most efficient teaching materials for each unit in advance, but there is a limit to shortening the time required to finish education due to restrictions on where and where the media can be used. It can be said that not only the second problem is not solved but also the problem becomes more serious. For example, if a part of the learning content is a VTR teaching material, the content can be acquired only in a limited environment (than an environment where a reference book can be read) in an environment where a VTR exists. In other words, when the learning progresses to the point where the VTR teaching material is required in the curriculum, if the user cannot use the VTR in daily life, the learning plan will be significantly confused.

[0007] In the above description, the cases are divided, but in any case, when an action plan in the daily life of the user is given, the most suitable teaching material for the action plan is determined according to the consistency of the entire learning plan. -It is not possible to make a selection while ensuring completeness, and it is extremely difficult to make this decision correctly at the discretion of the user. The above is the problem to be solved.

[0008] An object of the present invention is to provide a learning system capable of determining learning materials and media in consideration of a user's action plan and presenting them to the user to support learning.

[0009]

In order to achieve the above object, the present invention first provides a means for inputting and registering a user's action plan, and registers what kind of action the user performs in each time zone. I do. In addition, the type of the action is also registered in the action for each time zone. On the other hand, the education content consisting of a set of teaching materials, information on which "type of action" each teaching material can be used when conducting the above, and the start of education when learning using each teaching material And then register the time it takes to complete.

[0010] By the above-mentioned method, it is possible to know which teaching material can be used in each time zone. Therefore, a computer or the like is used to perform a combined search for which learning material is to be used in which time zone. Then, many learning patterns are created, and each learning pattern is evaluated by a certain method (for example, whether a period until learning of all educational contents is completed is short). Thus, according to the present invention, the most appropriate learning method can be automatically selected and presented to the user.

[0011] Further, there is actually a demand such as "I want to use teaching materials that are as effective as possible". For this,
For each teaching material, the degree of the effect is registered, and when each of the learning patterns is evaluated, the evaluation value can be realized by totaling the “degree of the effect” and using the evaluation value as one criterion. In addition, the method (calculation formula) used to evaluate each pattern also determines whether to make a plan that emphasizes the desire to “learn the study in a short time” or the desire to “learn an effective study”. This can be realized by performing arbitrary weighting.

[0012] Further, there may be a condition regarding a learning order between a plurality of learning materials, such that "the content of learning using the learning material B cannot be understood until after learning using the learning material A". Such a condition can always generate a learning plan that satisfies the condition by excluding a learning pattern that does not satisfy the constraint when generating a learning pattern using a combinatorial search. Also, a learning pattern that meets the condition can be determined by lowering the evaluation value of the learning pattern that does not satisfy the condition.

[0013] Further, by registering the location of the teaching material and the reproducing method as data for each teaching material, it is possible to automatically reproduce the appropriate teaching material when actually learning according to the presented learning pattern. It is possible to greatly reduce the trouble of acquiring and reproducing the teaching materials presented by the user.

[0014]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A learning system according to the first aspect of the present invention comprises means for registering one or a plurality of teaching materials for a range to be learned (a learning unit) and media to be used, and media for each teaching material. Means for registering an estimated time required for learning, means for inputting a user's action schedule, means for specifying a type of media that can be used from the type of user's action registered in the action schedule, Means for determining a learning unit for each time period so that all the learning units to be learned can be learned while satisfying the restriction on the type of used medium determined from the schedule.

According to the above configuration, there is an effect that the combination of the teaching material and the media that is optimized for the user's action schedule and satisfies the entire learning item coverage is automatically determined. The invention according to claim 2 is means for registering the effectiveness of learning for each learning material, means for totalizing the effectiveness of the learning material for each time zone based on a certain standard, and determining overall effectiveness, and By weighting some or all of the three values of the effectiveness, the overall effectiveness, and the shortest predicted time to complete the entire learning by a certain standard,
Calculating means for calculating an evaluation value for a combination of teaching materials; determining means for determining a learning plan having the largest evaluation value among learning plans satisfying the constraints of the user's action plan;
And determining a learning plan having the largest evaluation value among learning plans satisfying the constraints of the user's action plan. According to the above configuration, the effect of the learning and the short time required are weighted according to the request, so that the learning plan that meets the user's request can be determined.

According to a third aspect of the present invention, there is provided means for registering, for each learning unit, a set of learning units which need to be learned in advance in order to perform learning of the learning unit;
Before learning a learning unit, only the combination of teaching materials that can learn all the learning units that need to be learned in advance is to be determined, and learning of the learning unit is performed for each learning unit. Means for registering a set of learning units that need to be acquired in advance in order to
It is characterized in that, before learning the learning unit, only the combination of the teaching materials that can acquire all the learning units that must be acquired in advance is to be determined.

According to the above configuration, when there is a condition regarding the order of learning, a learning plan that takes into consideration not only a short time and a learning effect but also an appropriate learning order can be automatically generated. . Hereinafter, embodiments of the present invention will be described with reference to FIGS. 1 to 12. (Embodiment 1) [Overall Configuration of Learning System] FIG. 1 is an embodiment for realizing claim 1 of the present invention. In FIG. An input / output unit that outputs information to be presented to the user,
Reference numeral 2 denotes a schedule data storage unit for storing schedule data in which a user's action plan is stored as digital data. Reference numeral 3 divides contents to be educated into a plurality of learning units, and each learning unit can be realized by using any learning material. A learning material data storage unit for storing learning material information data for storing information about the learning conditions, the use conditions of each learning material, and the time taken or the estimated time required for learning using each learning material. A learning pattern generation unit that generates a learning pattern that can be realized on the schedule of the user, a learning pattern storage unit that stores the learning pattern generated by the learning pattern generation unit;
Is a learning pattern evaluation unit that evaluates each learning pattern under certain conditions and determines an optimal learning pattern for the user.

The schedule data stored in the schedule data storage unit is, for example, as shown in FIG. 2, in which daily activities and behavior types are arranged in chronological order. The user inputs this schedule data through the input / output unit 1. The teaching material information data stored in the teaching material information data storage unit 2 includes education data, teaching material data, and action type data. As shown in FIG. 2, the education data describes an education name that can be selected as a learning target (in the figure, only education A is shown) and a unit name that constitutes the education content. As shown in FIG. 3, the teaching material data describes the name of the teaching material for learning each unit, the type of media of the teaching material, and the time required for learning each teaching material. As can be seen from the figure, the unit 1 can be learned using the teaching material 1 which is a book teaching material, or can be learned using the teaching material 2 which is a VTR teaching material. Similarly, the unit 2 can be learned by using either the teaching material 3 which is a book teaching material or the teaching material 4 which is a cassette tape teaching material. When learning was performed using each teaching material, the expected value of the learning time was 3
The time, the teaching material 2 is 1 hour, the teaching material 3 is 2 hours, and the teaching material 4 is 2 hours 30 minutes. The activity type data describes which media can be used for each activity type as shown in FIG. In the diagram, the type of user action is
In order to match the contents of the schedule data, it is classified into “No work at home”, “Commuting (non-rush)”, “Commuting (rush)”, “Company (off time)”, “Company (work)”, “sleeping”, “meal” Indicate these categorizations and use the media (books,
VTR, cassette) can be used.

Education data and teaching material data can be input in advance by a user, but can be obtained from a third party provided through a network or the Internet. On the other hand, the behavior type data is input by the user himself. The learning pattern generation unit 4 uses the schedule data and the learning material information data described above to
The operations 0, 11, and 12 are executed to generate a learning pattern suitable for the user. Details of the operations in these figures will be described later.

The learning pattern storage unit 5 stores the learning pattern generated by the learning pattern generation unit 4. The learning pattern evaluation unit 6 evaluates all generated learning patterns. [Learning Pattern Generation Procedure and Evaluation Method] Next, a learning pattern generation operation and an evaluation method using the above learning system will be described. In the following description, in the case of learning the education A, it is assumed that the difficulty remains the same regardless of which unit 1 or unit 2 is studied first (that is, “understand the contents of the unit 2 It is difficult to do this only after you have already mastered 1)). [Explanation of Recursive Call Processing (func1)] FIGS. 10 and 11 are flowcharts showing processing in the learning pattern generation unit in the present embodiment. Basically, the learning pattern generation unit assigns all patterns while performing trial and error on learning items in a time zone. Therefore, a tree search algorithm using a backtrack is adopted. As a method of realizing backtracking, a recursive call is used here.

Func1 is a subroutine for performing a recursive call. When assigning a learning item to a time zone, it is necessary to determine a unit for managing the time zone. Here, the time zone is specified in units of 5 minutes. First, the contents of the learning pattern storage unit 5 are emptied (step S1). Next, a subroutine func1 is called (step S2). The processing as a whole has been described above. Next, the processing content of func1 will be described in detail with reference to FIG.

Func1 takes three types of information as arguments.
The first argument is the start time. The second argument is the accumulation schedule. The storage schedule is information in the form of a list, and includes a plurality of “unit schedules”.
Each "unit schedule" has a start time, a continuation time, a unit,
It consists of four sets of information of teaching materials. FIG. 12 shows the contents of each argument and an example of data in a table format. In the figure, the second
The data enclosed in parentheses, such as (6:00 to 6:05, unit 1, VTR) shown in the data example of the argument of, is the unit schedule. The first data in parentheses is 6: 00-
6:05, which indicates start time and duration, the second data (for example, unit 1, unit 2, etc.) is data indicating unit name, and the third data (for example, VTR,
Cassette etc.) is data indicating the name of the teaching material. In the storage schedule, which is the second argument, a unit schedule for which allocation has been completed is registered. Therefore, immediately after the processing is started, nothing is registered in the accumulation schedule, but as the processing proceeds, unit schedules are sequentially registered, and the number of registrations increases. As will be understood from the above description, the unit schedule for which the assignment has been completed is registered in the storage schedule.

The third argument is "unselected unit list". The “unselected unit list” is a list including a plurality of unit information. The unit information is a set of three pieces of information of the unit, the teaching material, and the remaining time, as shown as a data example of the third argument in FIG. Both the unit and the teaching material are selected and registered in this list until the remaining time becomes zero, and when the remaining time becomes zero, they are deleted from the list. At the first stage when the learning pattern generation process is started, the “unselected unit list” includes the unit type, (unit 1, teaching material undecided, remaining time indefinite), (unit 2, teaching material undecided, remaining time indefinite). Is created. In the item, the value of the teaching material "undecided" means that it is not yet decided which teaching material to assign. Then, in this case, the “remaining time” is undefined.

From the viewpoint of the caller, func1 can be regarded as a subroutine having the following functions as a whole. That is, all learning patterns starting from the “start time” for acquiring the units specified in the “unselected unit list” of the third argument (each unit needs to acquire the remaining time) are created. . Next, one obtained by connecting the “storage schedule” of the second argument before each learning pattern is output to the learning pattern storage unit 5 as one schedule. Function. However, the output to the learning pattern storage unit 5 is not performed all at once, but is performed sequentially in each step of a tree search for performing a recursive call.

[Explanation of processing contents of func1] When func1 is called in step S2, the processing proceeds to FIG. 11, and in S101, attention is paid to a time zone of 5 minutes from the start time. With reference to the user's schedule in this time zone (FIG. 5), the attribute is determined from the "action type". Next, a type list is determined from the type information (FIG. 4) of the teaching material that can be used in this attribute. When the teaching material information in the unselected unit list is “undecided”, all the teaching materials that can be determined to be acquired in the “action type” can be used. If the teaching material information is not "undecided" and is designated, the processing is performed on the assumption that the corresponding unit can use only the designated teaching material.

Next, the third argument "unselected unit list"
Check if there is a unit in which you can study with the teaching materials in this teaching material type list. If a unit exists, the process proceeds to S102. If it does not exist, the start time is advanced by 5 minutes in S103, and the process returns to S101. In S102, among the units registered in the unselected selection list, which is the third argument, those which can be learned in the currently focused time zone and combinations of the learning materials are listed in a list L (temporary variable).
Copy to The list L has a data structure similar to that of the third argument “unselected unit list”. However,
There are no "undecided" teaching materials in List L,
On the other hand, there can be multiple units with the same unit (different teaching materials).

Next, one selectable teaching material is selected from the list L (the unit corresponding to the teaching material is also determined). As for the “remaining time” of each teaching material in the list L, if the teaching material is already specified in the original “unselected unit list”, the remaining time is copied. Otherwise, referring to the teaching material information (FIG. 3), all the time required for learning with the corresponding teaching material is designated as the remaining time. For the convenience of the following description, the teaching material selected here is (A). Subsequently, assuming that the selected teaching material (A) is allocated to the time zone of interest, the remaining time required for learning is calculated (S
104 → S105 → S106 → S109 → S110 → S10
4). This refers to the remaining time of (A) in list L,
Subtract 5 minutes from this value. As a result, the remaining time is 0
(Below), the assignment of the unit that can be acquired with the teaching material (A) (hereafter, the unit that can be acquired with the selected teaching material (A) is called unit (A)) is completed. Will be. In this case, if there is a unit other than the unit (A) in the "unselected unit list", the unit (A) has been assigned, but there is still a unit to be learned other than the unit (A) (S107). At that time, func1
Is recursively called to assign a schedule other than the unit (A) (S108). Since it is a schedule other than the unit (A), the “start time” of the first argument of func1 specifies the time immediately after the unit (A) is assigned (that is, from the time after the unit (A) is assigned) Start assignment). The accumulation schedule is based on the original accumulation schedule (when the function is called,
The information to which the information of the unit (A) for 5 minutes assigned to S101) is added is designated. This is because when the schedule is completed to the end, this information is used as the “assigned schedule” (calling func1 generates the schedule of any combination after the assigned 5 minutes. .).

In this way, since all schedules in which the unit (A) is assigned to the time zone of interest in the original func1 should be generated, the unit (A) is then deleted from the list (S109). ). The list L represents "things that can be learned in the currently focused time zone". The reason for deleting (A) from the list L is that func1 has already been deleted in step S108.
This is because, when is called, all schedules in the form of (A) assigned to the currently focused time zone have been exhausted. Next, it is checked whether the list L is empty (step S110). If (A) is the last unit to be learned, this will be YES and the function will exit. Conversely (A)
If there is another unit that can be selected in the current time zone of interest, the process returns to S104, and another unit from the list L (because (A) has already been deleted from L; ) And repeat the same.

Next, the processing in the case where "other than (A) does not exist in the unselected selection list" in step S107 will be described (step S111). The fact that there is nothing other than (A) in step S107 means that at the time immediately after calling the function (time of step S101), only (A) already exists in the third argument “unselected unit list”, and , (A) is assigned a time of 5 minutes (step S104), which means that the learning of the unit (A) is completed. In this case, since the schedule to which all the units to be learned have been allocated has just been completed at that time, the completed schedule is output to the “learning pattern storage unit”. At this time, since the schedule in the time zone before the assigned (A) is stored in the “storage schedule” of the second argument, the “storage schedule” and the just assigned (A) are connected,
The completed version schedule may be used.

Finally, a description will be given of a case where "all the time necessary for learning (A) has not been allocated" in step S105. In this case, (A) is assigned to the time zone of interest, but it is still necessary to take time to complete learning of (A). Also at this time, from the next time slot to which (A) is assigned, a schedule must be established to learn the rest of (A) and anything other than (A) in the "unselected unit list", so that func1 is recursive. To call. The argument “start time” is the next time zone to which the current (A) is assigned, and the “unselected unit list” is the time period to be learned in (A) reduced by the assigned time and the original “unassigned”. Specify a unit other than (A) in the "Unit of selection" list and call it. Thereby, a schedule after (A) is assigned is generated. Again,
Since the method of allocating (A) to the time zone of interest has already been tried, it is necessary to consider a case where a unit other than (A) is subsequently allocated. Therefore, after deleting (A) from the list L (step S109), if there is another option, the process returns to step S104 to create a schedule in which options other than (A) are assigned to the time zone of interest. .

[Explanation of specific processing using func1]
An operation example of the learning pattern generation unit according to the above algorithm will be described. The unit of allocation is 5 minutes, the educational configuration information is shown in FIG. 2, the teaching material information is shown in FIG. 3, the schedule type information is shown in FIG. 4, and the schedule is as shown in FIG. The schedule creation start time is set to 3/2 6:00.

First, in step S1, the contents of the "learning pattern storage section" are cleared. Next, the process proceeds to step S2, and func1 is called. At this time, the start time is 3/2
At 6:00, the storage schedule is empty, and the unselected unit list is ((unit 1, teaching material undecided, remaining time undefined), (unit 2, teaching material undecided, remaining time undefined)). In the first call of func1, 6: 00-6: 05 is the time zone of interest. The behavior type in this time zone is “sleeping” from FIG.
From FIG. 4, it can be seen that "book", "VTR", and "cassette" cannot be used in "sleep". Therefore, naturally, both the unit 1 and the unit 2 in the “unselected unit list” are 6: 00-6: 0.
5 cannot be assigned. Therefore, step S1
The condition of 01 is NO, and the process proceeds to step S103. Here, the start time is advanced by 5 minutes, and attention is paid to the time zone of 6: 05-6: 10. However, because he is still "sleeping"
S101 becomes NO. Thus, 6: 30-6:
Step S101 and step S1 until the time period of 35 is reached
Loop between 03.

When the time zone becomes 6: 30-6: 35, the action type becomes "meal (home)", and from FIG. 4, "book" cannot be used, but "VTR" and "cassette" can be used. . Unit 1 can be learned using the teaching material "Teaching Material 2" using "VTR". The unit 2 can be acquired by using the teaching material "teaching material 4" using the "cassette". Other than that, there is no teaching material to learn the “unselected unit list”. As described above, in S102, in the list L, ((unit 1, teaching material 2,
1:00 remaining time), (2 units, 4 teaching materials, 2 remaining time)
30)) are registered. Next, in S104, from list L (unit 1, teaching material 2, remaining time 1:
00) and assign it to the time zone 6: 30-6: 35. Since only 5 minutes have been allocated for the time required for learning, the condition of S105 is NO and S1
Proceed to 06. In S106, func1 is recursively called. At this time, the start time of the first argument is 6:35.
The accumulation schedule of the second argument is (6:30 to 6:35 unit 1, teaching material 1). In the third argument “unselected unit list”, the already allocated portion is updated, and ((unit 1, teaching material 1, remaining time 0:55), (unit 2, teaching material undecided, remaining time undecided)) specify.

Thereafter, the processing is repeated in the func1 called in the same manner, and "the teaching material 1 is set between 6: 30-6: 35.
All schedules that meet the premise of "assigned" are generated. When the calling of func1 ends, (unit 1, teaching material 2, remaining time 1:00) is deleted from the list L (S109). As a result, the content of the list L becomes ((unit 2, teaching material 4, remaining time 2:30)). Then S1
Returning to 04, selectable teaching materials from list L are selected.
This time, teaching material 4 is selected and registered at 6: 30-6: 35. Since only 5 minutes are allocated out of the remaining time of 2:30, the condition of S105 is NO, and the process proceeds to S106. With the call of S106, the process is repeated, and all schedules meeting the premise that "the teaching material 1 has been allocated between 6: 30-6: 35" are generated.

In step S106, the item including the teaching material 4 is deleted from the list L. Since list L is empty, step S
The condition of 110 is now YES, and the function returns. As a result, since the process exits func1 in FIG. 10, all the processes are completed. In the above processing, as a whole, all schedules that meet the premise that “the teaching material 1 is allocated between 6: 30-6: 35” and “6:30
-6: 35 was assigned to the teaching material 4 ".
Since either the teaching material 1 or the teaching material 4 is assigned to the time period from 6:30 to 6:35, “all schedules” is called up after all.

As described above, the recursive call is repeated, and in one recursive call, only a 5-minute schedule is assigned, and the rest proceeds to "deeper recursive call". Step S108 is performed when the function of the step has been assigned for the last 5 minutes of a certain teaching material. In this case as well, the schedule after the assignment is continued by recursive call. However, the difference from step S106 is that instead of reducing the remaining time of the corresponding unit in the “unselected unit list”,
That is, the unit data itself is deleted. For example, if the last 5 minutes of teaching material 1 have been allocated, there is no longer a need to allocate unit 1 for schedules after that time, so there is no need to leave unit 1 in the argument “unselected unit list” of func1. is there.

Step S110 is a unit 1 and a unit 2.
Were assigned one after another, the whole "last 5
Called when "minutes" are assigned. In this case, a complete schedule for learning the unit 1 and the unit 2 has been completed, and it may be simply output to the “learning pattern storage”. The schedule assigned so far should have been stored in the accumulation schedule of the second argument, and may be used.

(Embodiment 2) Next, a second embodiment of the present invention will be described. This embodiment implements claims 2 and 3 of the present invention. FIG. 1 is a configuration diagram of the present embodiment. There are three differences between the present embodiment and the first embodiment. The first difference is that in the teaching material information data 3,
The point is that the following two pieces of information are stored in addition to the information of the first embodiment. The first information is information on a unit assumed by the unit for each unit. FIG. 8 shows an example in which this information is represented in a table format. The second information is information indicating the effectiveness of each teaching material as a numerical value. For example, when it is considered that the same unit can be learned with the teaching material 1 only and the learning with the teaching material 2 alone, it is possible to learn the contents more deeply when learning with the teaching material 1 alone. Of the teaching material 2 is set to be higher than that of the teaching material 2. FIG. 9 shows an example in which effectiveness is assigned to each teaching material. Other information about each teaching material is registered in the same manner as in the first embodiment.

The second difference is that the learning pattern generator 4 checks the order of learning. When the learning pattern generation unit 4 allocates the teaching materials to each time zone, the learning materials are allocated in the order of the earliest time zone on the schedule. At this time, the assignment of a certain unit is determined only when the prerequisite unit is obtained from the information shown in the table of FIG. 8 and the teaching material for learning the prerequisite unit is already assigned to the schedule. Configure so that it can be assigned. This can be realized by inputting the information in FIG. 8 as constraint information and checking whether there is a media that can be used in consideration of the content of the constraint information.

The third difference is an evaluation method in the learning pattern evaluation section 6. In the present embodiment, the learning pattern evaluation unit 6 evaluates each learning pattern by the following equation. -(Period (time unit) from learning start to learning end) +
Aggregation of effectiveness of teaching materials * constant Here, the constant can be changed depending on which of the time and the effectiveness of the teaching material is more important, and is set to 1 in this embodiment. The functions and roles of other parts in FIG. 1 of the present embodiment are the same as those of the first embodiment.

In the present embodiment, first, when there is a restriction on the order of learning, only the learning pattern that matches the restriction is generated by the learning pattern generation unit 4, and is finally presented to the user. The learning pattern that satisfies the above-mentioned restrictions is always satisfied. When the two learning patterns are compared with each other, if there is a large difference in the period required for learning, the learning pattern evaluation unit 6 selects the learning pattern with the greater effect. When there is no large difference in effectiveness and there is a large difference in the period for learning, there is a feature that the evaluation value of a learning pattern having a short period becomes high.

In general, when learning is performed, both the time required for learning and the effectiveness of learning are almost always user's requests. In such a case, a learning plan most suited to the user's request is used. Can be presented.

[0043]

As described above, according to the present invention, first, the user can input the schedule and present the learning method which is completed at the earliest time for the user. You can learn much more efficiently than if you did. If the learning period and the range to be studied are both limited, such as when studying for an exam, and the learning period is short compared to the range to be learned, the user will be able to perform all of the possibilities without trial and error. This is particularly effective because the most appropriate learning method can be scheduled from.

In addition to the viewpoint that the learning effect of each teaching material to be used is high or low, it is possible to cope not only with the viewpoint of ending early but also by changing the evaluation method of the learning pattern evaluation unit. Further, it is possible to make a comprehensive judgment from a plurality of viewpoints only by changing the expression of the learning pattern evaluation unit. The evaluation expression of the learning pattern evaluation unit can be implemented by any expression that can be implemented by software using items that can be obtained from the teaching material information data and schedule data. Can be adjusted freely based on

[Brief description of the drawings]

FIG. 1 is a diagram showing an embodiment of the present invention.

FIG. 2 is a diagram showing educational configuration information in educational material information data.

FIG. 3 is a diagram showing teaching material information in the teaching material information data.

FIG. 4 is a diagram showing schedule type information in schedule data.

FIG. 5 is a diagram showing a schedule in schedule data.

FIG. 6 is a diagram showing one learning pattern that is an example of assigning teaching materials to a schedule.

FIG. 7 is a diagram showing another learning pattern as an example of assigning teaching materials to a schedule.

FIG. 8 is a diagram showing unit constraint information in the teaching material information data.

FIG. 9 is a diagram showing configuration information of education including efficiency in the teaching material information data.

FIG. 10 is a main flowchart showing the operation of a learning pattern generation unit.

FIG. 11 is a subroutine showing a learning system generation process.

FIG. 12 is a diagram showing data of each argument used in a recursive call process (func1).

Claims (3)

[Claims] 1. A means for registering one or more teaching materials for a range to be learned and a medium to be used, a means for registering an estimated time required for learning by using a medium for each teaching material, and a user action Means for inputting a schedule; means for specifying the type of media that can be used from the type of action of the user registered in the action schedule; and learning while satisfying the constraint on the type of media used from the action schedule. Means for determining a learning unit for each time zone so that all the learning units to learn can be learned. 2. A means for registering the effectiveness of learning for each learning material, a means for totalizing the effectiveness of the learning material for each time zone based on a certain standard and determining the overall effectiveness, Calculate an evaluation value for a combination of teaching materials by weighting some or all of the three values of the overall effectiveness and the shortest predicted time required for completing the entire learning by a certain standard. Calculating means; and determining means for determining a learning plan having the largest evaluation value among learning plans satisfying the constraint by the user's action plan, wherein the evaluation value is selected from the learning plan satisfying the constraint by the user's action plan. The learning system according to claim 1, wherein a learning unit that determines the maximum is determined. 3. A means for registering a set of learning units that need to be learned in advance for each learning unit in order to perform learning of the learning unit, and learning in advance before learning the learning unit. The learning system according to claim 1, wherein only a combination of learning materials for learning all necessary learning units is to be determined.