JP7039015B2 - Teaching material learning schedule determination device - Google Patents

Description

The present invention relates to a teaching material learning schedule determining device, and more particularly to a teaching material learning schedule determining device for improving grades in an examination.

In recent years, with the globalization of business and telecommunications and the spread of overseas travel, the need to learn a foreign language has become more and more increasing. In school education, how to efficiently improve the language skills of individual learners within the limited class time is an important issue. The computer-assisted language learning system implemented in school education prepares a large number of language teaching materials of various difficulty levels, evaluates the language proficiency of each learner in a preliminary test, and is among the many language teaching materials. There is a method to extract language teaching materials suitable for the learner's language ability from the above and present them to the learner. For example, language teaching materials with a high vocabulary learning effect can be extracted and presented to learners with weak vocabulary, and language teaching materials with a high vocabulary learning effect can be extracted and presented to learners with weak vocabulary. For learners who are weak in soft sounds, bursting sounds, liaisons (concatenation), disappearing sounds, abbreviations, etc., it is also possible to extract and present language teaching materials with high learning effects.

By the way, when hiring human resources in a company or selecting overseas work, language ability is often evaluated based on the results of a private language test or a public language test that is conducted on a large scale in society. These out-of-school language exams are fairly accurate in assessing real-life language proficiency, and it makes sense to aim to improve these language exam grades in school education. It can be said that it is a policy.
However, although the conventional computer-aided language learning system can learn to strengthen the weak points of the learner's language ability, it has not been able to efficiently improve the results of the language test conducted in society. ..

The present invention has been made in view of the above-mentioned problems of the prior art, and an object of the present invention is to provide a teaching material learning schedule determination device capable of improving the results in an examination.

In the invention according to claim 1,
A first storage means in which the learner memorizes the question question rate for each of multiple types of learning elements in the past exams in a certain exam to be taken.
A second storage means for storing the expected learning effectiveness for each of a plurality of types of learning elements for a large number of teaching materials for one learning frame for each of the above-mentioned test preparations.
It is an index for ordering determined by teaching material and by the order of learning frames in N learning frames, and the index is smaller (larger) as the teaching material is more advantageous for learning in the first order among different teaching materials with the same learning frame ranking. ), A third storage means that stores information on the ordering index, which is set so that the index becomes larger (smaller) as the rank decreases between different learning frame ranks in the same teaching material.
Using the information stored in the first to third storage means and the information on the correct answer rate or the incorrect answer rate for each learning element in the preliminary test that the learner took in advance, the same teaching material has N learning frames. Under the constraint condition of learning only once in the number, the learning effect level and the learner's wrong answer rate for each learning element when N teaching materials are selected in order from a large number of teaching materials. The first value, which is the product of the question rate in the exam and the product of the question question rate for multiple types of predetermined learning elements and the selected N teaching materials, and each of the selected ordered N teaching materials. A search means for searching for N combinations of ordering that maximizes the value obtained by weighting and adding the second value obtained by adding the ordering index of the selection order for N teaching materials by the mathematical programming method.
It is characterized by including.
In the invention according to claim 2,
The third storage means is an ordering index determined for each teaching material and for each learning frame ranking among N learning frames, and it is advantageous to study in the first order among different teaching materials with the same learning frame ranking. The index is smaller (larger) as the teaching material is used, and the index is smaller (larger) as the ranking is lower between different learning frame rankings in the same teaching material.
The search means is such that when searching by the mathematical programming method, the first value and the second value are weighted and subtracted.
It is characterized by.
In the invention according to claim 3,
A learning element setting means for the learner or teacher to set the type of learning element when obtaining the first value by the mathematical programming method is provided.
When calculating the first value, the search means is based on the learning effect level for each learning element, the learner's error rate, and the test when N teaching materials are selected in order from a large number of teaching materials. The product of the question question rate of is added for multiple types of learning elements set by the learning element setting means and for the selected N teaching materials.
It is characterized by.
In the invention according to claim 4,
A first storage means in which the learner memorizes the question question rate for each of multiple types of learning elements in the past exams in a certain exam to be taken.
A second storage means for storing the expected learning effectiveness and planned learning time for each of a plurality of types of learning elements for a large number of teaching materials for a certain test preparation.
It is an index for ordering determined by teaching material and by learning frame ranking among N learning frames, and the index is small (large) so that learning in the first order is advantageous among different teaching materials with the same learning frame ranking. , A third storage means that stores information on the ordering index, which is set so that the index becomes larger (smaller) as the rank decreases between different learning frame ranks in the same teaching material.
Using the information stored in the first to third storage means and the information on the correct answer rate or the incorrect answer rate for each learning element in the preliminary test that the learner took in advance, the same teaching material has N learning frames. The constraint that learning is done only once in the number, and the constraint that one or more teaching materials can be learned in one learning frame, but the total planned learning time of the teaching materials does not exceed the learning time for one frame. Under the conditions, the product of the learning effect level for each learning element, the error rate of the learner, and the question question rate in the exam when various N-frame teaching materials are selected in order from all the teaching materials is calculated in advance. The first value added for the learning elements in the specified range and the selected N-frame teaching materials, and the ordering index for each selection order of the selected ordered N-frame teaching materials are for N frames. A search means for searching a combination of ordered teaching materials for N frames, which maximizes the weighted addition of the second value added to the teaching materials, by a mathematical programming method.
It is characterized by including.
In the invention according to claim 5,
The third storage means is an ordering index determined for each teaching material and for each learning frame ranking among N learning frames, and it is advantageous to study in the first order among different teaching materials with the same learning frame ranking. The index is smaller (larger) as the teaching material is used, and the index is smaller (larger) as the ranking is lower between different learning frame rankings in the same teaching material.
The search means is such that when searching by the mathematical programming method, the first value and the second value are weighted and subtracted.
It is characterized by.
In the invention according to claim 6,
A learning element setting means for the learner or teacher to set the type of learning element when obtaining the first value by the mathematical programming method is provided.
When calculating the first value, the search means is the learning effect level for each learning element, the error rate of the learner, and the test when various teaching materials for N frames are selected in order from a large number of teaching materials. The product of the question question rate in is added for the multiple types of learning elements set by the learning element setting means and the teaching materials for the selected N frames.
It is characterized by.
In the invention according to claim 7,
The ordering index is based on the difficulty of the teaching materials.
It is characterized by.
In the invention according to claim 8,
The ordering index is defined by one or more specific learning elements that are advantageous for learning in the first order.
It is characterized by.
In the invention according to claim 9,
The ordering index is defined by one or more specific learning elements that are advantageous for learning in the second rank.
It is characterized by.
In the invention according to claim 10,
A first storage means in which the learner memorizes the question question rate for each of multiple types of learning elements in the past exams in a certain exam to be taken.
A second storage means for storing the expected learning effectiveness for each of a plurality of types of learning elements for a large number of teaching materials for one learning frame for each of the above-mentioned test preparations.
A specification means for designating a learning element that the learner wants to learn in the priority learning frame order from among multiple types of learning elements, and
From the learning effectiveness of each teaching material for the learning element specified by the designated means, the greater the learning effect between different teaching materials with the same learning frame ranking, by teaching material, by learning frame ranking among N learning frames. A third storage means that stores information for creating an ordering index that has a small (large) value and increases (smaller) as the rank decreases between different learning frame ranks in the same teaching material.
Using the information stored in the first to third storage means and the information on the correct answer rate or the incorrect answer rate for each learning element in the preliminary test that the learner took in advance, the same teaching material has N learning frames. Under the constraint condition of learning only once in the number, the learning effect level and the learner's wrong answer rate for each learning element when N teaching materials are selected in order from a large number of teaching materials. The first value, which is the product of the question rate in the exam and the product of the multiple types of learning elements determined in advance and the selected N teaching materials, and the selection of each of the selected N teaching materials in order. A search means for searching for N combinations of ordering that maximizes the value obtained by weighting and adding the second value obtained by adding the ranking index for N teaching materials by the mathematical programming method.
It is characterized by including.
In the invention according to claim 11,
The third storage means is based on the learning effectiveness of each teaching material for the learning element specified by the designated means, by the teaching material, by the learning frame ranking among the N learning frames, and between different teaching materials with the same learning frame ranking. Then, the larger the learning effect, the smaller (larger) the value, and the lower the ranking between different learning frame rankings in the same teaching material, the smaller (larger) the information for creating an ordering index is stored.
The search means is such that when searching by the mathematical programming method, the first value and the second value are weighted and subtracted.
It is characterized by.
In the invention according to claim 12,
The third storage means is for each learning element, for each teaching material, for each learning frame ranking among N learning frames, and for different teaching materials with the same learning frame ranking, the greater the learning effect corresponding to the learning element, the higher the value. The ordering index, which is smaller (larger) and becomes larger (smaller) as the ranking decreases between different learning frame rankings in the same teaching material, is memorized.
It is characterized by.
In the invention according to claim 13,
The third storage means is for each learning element, for each teaching material, for each learning frame ranking among N learning frames, and for different teaching materials with the same learning frame ranking, the greater the learning effect corresponding to the learning element, the higher the value. Make sure to memorize the ordering index, which is smaller (larger) and becomes smaller (larger) as the ranking decreases between different learning frame rankings in the same teaching material.
The search means is such that when searching by the mathematical programming method, the first value and the second value are weighted and subtracted.
It is characterized by.
In the invention according to claim 14,
A learning element setting means for the learner or teacher to set the type of learning element when obtaining the first value by the mathematical programming method is provided.
When calculating the first value, the search means is based on the learning effect level for each learning element, the learner's error rate, and the test when N teaching materials are selected in order from a large number of teaching materials. The product of the question question rate of is added for multiple types of learning elements set by the learning element setting means and for the selected N teaching materials.
It is characterized by.
In the invention according to claim 15,
A first storage means in which the learner memorizes the question question rate for each of multiple types of learning elements in the past exams in a certain exam to be taken.
A second storage means for storing the expected learning effectiveness and planned learning time for each of a plurality of types of learning elements for a large number of teaching materials for a certain test preparation.
A learning element designation means for designating a learning element that a learner wants to learn in a priority learning frame order from among multiple types of learning elements, and a learning element designation means.
From the learning effectiveness of each teaching material for the learning element specified by the designated means, the greater the learning effect between different teaching materials with the same learning frame ranking, by teaching material, by learning frame ranking among N learning frames. A third storage means that stores information for creating an ordering index that has a small (large) value and increases (smaller) as the rank decreases between different learning frame ranks in the same teaching material.
Using the information stored in the first to third storage means and the information on the correct answer rate or the incorrect answer rate for each learning element in the preliminary test that the learner took in advance, the same teaching material has N learning frames. The constraint that learning is done only once in the number, and the constraint that one or more teaching materials can be learned in one learning frame, but the total planned learning time of the teaching materials does not exceed the learning time for one frame. Under the conditions, the product of the learning effect level for each learning element, the error rate of the learner, and the question question rate in the exam when various N-frame teaching materials are selected in order from all the teaching materials is calculated in advance. The first value added for the specified multiple types of learning elements and the selected N-frame teaching materials, and the ordering index for each selection order of the selected ordered N-frame teaching materials are for N frames. A search means for searching the combination of ordered teaching materials for N frames, which maximizes the weighted and added value of the second value added to the teaching materials, by the mathematical programming method.
It is characterized by including.
In the invention according to claim 16,
The third storage means is based on the learning effectiveness of each teaching material for the learning element specified by the designated means, by the teaching material, by the learning frame ranking among the N learning frames, and between different teaching materials with the same learning frame ranking. Then, the larger the learning effect, the smaller (larger) the value, and the lower the ranking between different learning frame rankings in the same teaching material, the smaller (larger) the information for creating an ordering index is stored.
The search means is such that when searching by the mathematical programming method, the first value and the second value are weighted and subtracted.
It is characterized by.
In the invention according to claim 17,
The third storage means is for each learning element, for each teaching material, for each learning frame ranking among N learning frames, and for different teaching materials with the same learning frame ranking, the greater the learning effect corresponding to the learning element, the higher the value. The ordering index, which is smaller (larger) and becomes larger (smaller) as the ranking decreases between different learning frame rankings in the same teaching material, is memorized.
It is characterized by.
In the invention according to claim 18,
The third storage means is for each learning element, for each teaching material, for each learning frame ranking among N learning frames, and for different teaching materials with the same learning frame ranking, the greater the learning effect corresponding to the learning element, the higher the value. Make sure to memorize the ordering index, which is smaller (larger) and becomes smaller (larger) as the ranking decreases between different learning frame rankings in the same teaching material.
The search means is such that when searching by the mathematical programming method, the first value and the second value are weighted and subtracted.
It is characterized by.
In the invention according to claim 19,
A learning element setting means for the learner or teacher to set the type of learning element when obtaining the first value by the mathematical programming method is provided.
When calculating the first value, the search means is the learning effect level for each learning element, the error rate of the learner, and the test when various teaching materials for N frames are selected in order from a large number of teaching materials. The product of the question question rate in is added for the multiple types of learning elements set by the learning element setting means and the teaching materials for the selected N frames.
It is characterized by.
In the invention according to claim 20,
Provided an input means for inputting the information of the correct answer rate or the incorrect answer rate for each learning element in the preliminary test that the learner took in advance into the search means.
It is characterized by.
In the invention according to claim 21,
Provided a presentation means to present the search result by the search means to the learner,
It is characterized by.

According to the present invention, the learner can determine the teaching materials for N frames and the learning order suitable for improving the learner's examination results from a large number of teaching materials for public or private examination preparation scheduled to be taken. ..

It is a block diagram of the English teaching material learning schedule determination system which concerns on one Example of this invention (Example 1). It is explanatory drawing of the index for ordering. It is a flowchart which shows the operation of the processing part of the information terminal in FIG. It is a flowchart which shows the operation of the processing part of the pretest server in FIG. It is a flowchart which shows the operation of the processing part of the teaching material learning schedule determination server in FIG. It is a block diagram of the English teaching material learning schedule determination system which concerns on the modification of FIG. It is explanatory drawing which shows the example of the information to be stored in the index information storage part for ordering of the teaching material learning schedule determination system of FIG.

Hereinafter, the best embodiment of the present invention will be described based on examples.

FIG. 1 is a block diagram showing a configuration of an English teaching material learning schedule determination system according to an embodiment of the present invention, which is embodied by a computer system. In the English teaching material learning schedule determination system, for example, a learner can learn English for 15 frames in 1 frame T time (T may be 1 hour, 2 hours, 90 minutes, etc.). At the time of studying, a large number of pre-prepared English teaching materials are targeted to determine a combination of English teaching materials suitable for preparation for a specific public or private English test Z conducted outside the company. In making the decision, the question rate for each English learning element in the past questions of English Test Z, the current academic ability of each learner's English learning element, and the learning effectiveness of each learning element of each teaching material are taken into consideration. By doing so, the optimum combination of English teaching materials for improving the grades of the English test Z is determined. At the same time, the order of learning frames for the teaching materials from the first frame to the 15th frame is also determined.

In FIG. 1, 10 is a pretest server, of which 11 is a pretest information storage unit that stores a large number of pretests and correct answers for testing the learner's current English proficiency. , Learning element B _j (j = 1, 2, ... Here, for example, grammar is B ₁ , vocabulary is B ₂ , weak sounds in listening, burst sounds, liaison (concatenation), disappearing sounds, abbreviations are B ₃ to It is categorized by type (B ₇ , etc.), and it is possible to calculate the correct answer rate _pj for each learning element of the learner. Here, the correct answer rate p _j is represented by a numerical value that becomes 1 when the answer is 100% correct (0 ≦ p _j ≦ 1). 12 is a program storage unit that stores a program that controls the operation of the pretest server 10, 13 is an input / output unit that inputs / outputs data and instructions to and from the outside, and 14 is a processing unit, and the program storage unit 12 When a pretest call request is input from the outside via the input / output unit 13 based on the program stored in the pretest information storage unit 11, it is read from the pretest information storage unit 11 and transmitted to the requester via the input / output unit 13 or externally. When a scoring request including the answer of the pretest is input from, the score is collated with the correct answer, the correct answer rate for each learning element is calculated, and the result is sent to the requester.

20 is a server for determining the learning schedule of teaching materials, and 21 of them are questions given in all the past exams of English Examination Z or the exams for a certain number of recent years (10 years or 5 years). This is a question question rate information storage unit that stores the question question rate r _j for each learning element B _j , which was analyzed in advance by the teacher. Here, the question question rate r _j is represented by a numerical value that becomes 1 when 100%. (0 ≤ r _j ≤ 1). Specifically, assuming that the number of questions for the learning element B _j in the past test is E _j , j = 1, 2, ..., G, the question question rate r _j is
r _j = E _j / (E ₁ + _{E 2} + ... + EG)
It is calculated in.
22 is a large number of English teaching materials S _i (i = 1, 2, ...) For each one frame (T hours) prepared in advance by the teacher, and teaching materials S analyzed in advance by the teacher for each teaching material. It is a teaching material information storage unit that stores the learning effect level v _ij for each learning element B _j when _i is learned once. Here, it is assumed that the learning effect level v _ij is quantified into a positive numerical value that increases as it increases. Also, it is assumed that the number of teaching materials S _i is much larger than 15.

As a measure for the English test Z, empirically, it is better to preferentially select and learn teaching materials with a high learning effect for learning elements that the learner is not good at and has a high questioning rate. It is effective for. _Wrong answer rate of learning element B _j (1-p _j ), question rate of learning element B _j in English test Z, learning effect of learning element B _j of teaching material S _{i product} (= D) ), It is effective to learn the combination that maximizes D when 15 frames of learning candidate teaching materials are selected from a large number of teaching materials in any combination.
Such a combination expresses whether or not to learn the teaching material S _i by the variable x _i (learning the teaching material S _i whose value of x _i is 1), and is one of the mathematical programming methods, the mixed integer programming method. Using,
Goal function
Maximize Σ _i Σ _j (1-p _j ) ・ r _j・ v _ij・ x _i・ ・ ・ (1)
Constraint expression
Subject to Σ _i x _i = 15 ・ ・ ・ (2)
x _i ∈ {0,1}, ∀i ・ ・ ・ (3)
It can be searched by formulating and solving as follows.

However, with the mathematical planning method based on (1) to (3), although the teaching materials for 15 frames can be extracted, which teaching material should be learned in each learning frame ranking from the 1st frame to the 15th frame. Is not required.
Here, among the many teaching materials S ₁ , S ₂ , ..., learning in the order of the first of the 15 frames, such as basic, low vocabulary level and easy to understand, and few grammar problems. There are some things that are advantageous for understanding the teaching materials to be learned later. In consideration of this point, in this embodiment, as described below, the learning frame ranking of the teaching materials is also focused, and the configuration is provided so that the optimum combination of teaching materials for the learner's test preparation can be determined in order. There is.

Reference numeral 23 denotes an ordering index information storage unit that stores information on the ordering index w _ik that has been analyzed and determined in advance by the teacher for each teaching material and learning frame rank k (k = 1 to 15). The ordering index _wik determines the most effective learning frame order for improving the grades of the external English test Z for 15 teaching materials that are tentative candidates for learning from among a large number of teaching materials S ₁ , S ₂ ... Used for. Here, the index for ordering w _ik becomes smaller as the teaching material has the advantage of learning in the first order among different teaching materials with the same learning frame ranking, and the index becomes larger as the ranking decreases between different learning frame rankings in the same teaching material. It is stipulated as follows.

This ordering index _wik can be set, for example, by using the difficulty level of the teaching material (the difficulty level can be, for example, the vocabulary level of the teaching material) as an index. This is because when multiple teaching materials that are candidates for learning have different difficulty levels, empirically, the less difficult teaching material is learned first, and the more difficult teaching material is learned later. Is effective in improving academic ability. The ordering index _wik may be set so that the lower the difficulty level is, the smaller the index is, and the lower the learning frame rank is, the larger the index is.

For convenience of explanation, the total number of frames is assumed to be N'= 5, and each of the _five teaching materials s _1'to s 5'combined as tentative candidates to be learned has an indexed difficulty level m _1'to m _{5 '} , But
m _1' = 2.55 ... s _1'
m _2' = 2.80 ... s _2'
m _3' = 1.63 ... s _3'
m _4' = 1.49 ... s _4'
m _5' = 2.01 ... s _5'
However, assuming that the larger the numerical value is, the higher the difficulty level is, the ordering index w _i'k'is set as shown in FIGS. 2 (1) and 2 (2), for example. In Fig. 2, the numerical values are assumed to be in the relationship of w _i'k' = k'・ mi _' (however, k'= 1,2, ・ ・ 5, i'= 1', 2', ・ ・ 5'). An example is shown.
Here, select the teaching material s 1'in the first frame, select the teaching material s _3'in the _second frame, select the teaching material s _5'in the third frame, and select the teaching material s _2'in the fourth frame. When teaching material s _4'is selected in the 5th frame
U = w 1'1 _' + w _3'2' + w _5'3' + w _2'4' + w _4'5'
Consider U like this. When the five teaching materials s _1'to s 5'are allocated to the learning of a total of 5 frames in various orders without duplication, the order in which U is maximized is s _4' , s _3' , s _{5 '} , and s _1'. , S _2' , in ascending order of difficulty. Therefore, when there are five learning candidate teaching materials s 1'to s _{5' ,} the order in which U is the maximum is the order in which U is the best for improving grades. Incidentally, the order in which U is minimized is S _2' , S _1' , S _5' , S _3' , and S _4' .

The order in which U becomes maximum indicates whether or not to learn the teaching material S i'in the k'frame by the variable x _i'k' (when x _i'k' = 1, the teaching material S i'is _{k '} . Learning in the frame), using mathematical planning method,
Goal function
Maximize Σ _{i'Σ k'w i'k' ・}x _i'k'・ ・ ・ (4)
Constraint expression
Subject to Σ _{k'x i'k' =} 1, ∀i'・ ・ ・ (5)
x _i'k'∈ {0,1}, ∀i'... (6)
It can be searched by formulating and solving as follows.
However, in this embodiment, as will be described later, it is devised so that the teaching materials for N = 15 frames can be selected and the learning frame ranking can be determined at once.
Here, it is assumed that the information stored in the ordering index information storage unit 23 is a numerical table of the ordering index _wik according to the teaching material and the learning frame ranking (see FIG. 2 (1)).

24 is a program that searches for combinations of teaching materials to be learned in order using a mathematical programming method (mathematical optimization solver (Gorobi), etc. Objective functions, constraint condition expressions, etc. are set in this program). The stored program storage unit 25 is an input / output unit for exchanging data, commands, etc. with the outside, and functions as an input means for inputting the correct answer rate for each learning element of the pretest received by the learner. Reference numeral 26 is a processing unit, and when a teaching material learning schedule determination request including a correct answer rate for each learning element is input from the outside via the input / output unit 25 based on the program stored in the program storage unit 24, the question question rate information is stored. Using the optimization planning method while referring to various information stored in the section 21, the teaching material information storage section 22, and the ordering index information storage section 23, 15 English teaching materials for 15 frames are searched in order. And send it to the requester.

Reference numeral 30 is an information terminal used by the learner, which takes a pretest, gives an instruction to determine a learning material learning schedule for 15 frames, and confirms the teaching material learning schedule. Of these, 31 is an operation unit that performs a menu display operation, a pretest examination operation, an instruction operation for determining a teaching material learning schedule, and 32 is a display unit that displays a menu screen, a pretest examination screen, a teaching material learning schedule display screen, and the like. 33 is a speaker that outputs listening audio, 34 is an input / output unit that exchanges data / commands with the outside, 35 is a menu display, pretest call request, pretest execution, teaching material learning schedule determination. The program storage unit 36 stores various programs for displaying requests, teaching material learning schedules, etc., and 36 is a processing unit. Based on the program stored in the program storage unit 35, menu display and pretest are performed according to the operation of the operation unit 31. Call request, pretest, teaching material learning schedule determination request, teaching material learning schedule display, etc. are executed.
The information terminal 30, the pretest server 10, and the teaching material learning schedule determination server 20 can communicate with each other via a network (local network, public network, etc.).

Next, the operation of the above-described embodiment will be described with reference to FIGS. 3 to 5. FIG. 3 is a flowchart showing the operation of the processing unit 36 of the information terminal 30 in FIG. 1, FIG. 4 is a flowchart showing the operation of the processing unit 14 of the pretest server 10, and FIG. 5 is the processing of the teaching material learning schedule determination server 20. It is a flowchart which shows the operation of a part 26. Here, it is assumed that each of the large number of teaching materials S ₁ , S ₂ , ..., The scheduled learning time is T, and 15 teaching materials for N = 15 frames are determined in order.
(1) Pretest When the learner performs a menu display operation on the operation unit 31 of the information terminal 30, the processing unit 36 displays "pretest" and "teaching material learning schedule" on the display unit 32 based on the program stored in the program storage unit 35. When the menus of "decision" and "teaching material learning schedule display" are displayed (step F1 in FIG. 3) and the selection operation of "pretest" is performed, the processing unit 36 makes an external pretest call request via the input / output unit 34. It is transmitted to the pretest server 10 (YES in step F2, F3). The processing unit 14 that has input the request via the input / output unit 13 reads the pretest from the pretest information storage unit 11 and returns it to the request source (YES, F21 in step F20 in FIG. 4).

The processing unit 36 of the information terminal 30 stores the pretest input via the input / output unit 34 in an internal storage unit (not shown), and outputs the pretest from the display unit 32 and the speaker 33 (FIG. 3). Steps F4 and F5). The learner solves the pretest and inputs the answer in the operation unit 31. The pretest contains a number of questions for each of the various learning elements B _j (j = 1, 2, ...).
When the input of the answers to all the questions in the pretest is completed and the learner performs the end operation, the processing unit 36 sends a scoring request including the answers to the pretest server 10 via the input / output unit 34 (YES in step F6, F7). ). The processing unit 14 of the pretest server 10 that has input the request collates the answer with the correct answer of the pretest information storage unit 11, grades the answer, calculates the question correct answer rate p _j for each learning element B _j , and learns element B. The content of _j and the corresponding question correct answer rate p _j are returned to the information terminal 30 (YES in step F22 in FIG. 4, F23 to F25).
The processing unit 36 of the information terminal 30 stores the question correct answer rate p _j for each learning element B _j input via the input / output unit 34, and stores the content of the learning element B _j and the question correct answer rate p _j in the display unit 32. Display them in pairs (steps F8 and F9 in FIG. 3). This allows learners to understand their current English proficiency.

(2) Determination of teaching materials When the learner who has undergone the pretest performs a menu call operation and selects "determine the teaching material learning schedule" on the screen (YES in step F10, YES in F1, F11), the processing unit 36 pretests. Is transmitted to the teaching material learning schedule determination server 20 including the question correct answer rate p _j for each learning element B _j via the input / output unit 34 (YES in step F12, F13). ..
The processing unit 26, which has input the request via the input / output unit 25, has a problem accuracy rate p _j for each learning element B _j in the pretest and a problem based on the teaching material determination program stored in the program storage unit 24. Question rate Learning element B _j of the past questions of the English test Z stored in the information storage unit 21 The question question rate r j for each question rate r _j and the learning element B _j of each teaching material S _i stored in the teaching material information storage unit 22 15 teaching materials with the highest grades when the learner takes the English test Z by the optimal planning method using the effectiveness level v _ij and the ordering index w _ik stored in the ordering index information storage unit 23. The combinations of the above are searched and determined in order (YES, F31 in step F30 in FIG. 5).

Specifically, whether or not to learn the teaching material Si in the k-frame is represented by the variable x _ik (when x _ik is 1, the teaching material S _i is learned in the k-frame), and the mathematical programming method is used.
Goal function
Maximize Σ _i Σ _j Σ _k (1-p _j ) ・ r _j・ v _ij・ x _ik
＋ α ・ Σ _i Σ _k w _ik・ x _ik・ ・ ・ (7)
α: Weighting coefficient constraint condition expression
Subject to Σ _k x _ik ≤ 1, ∀i ・ ・ ・ (8)
Σ _i x _ik = 1, ∀k ・ ・ ・ (9)
x _ik ∈ {0,1}, ∀i ・ ・ ・ (10)
By formulating and solving as follows, the teaching materials for 15 frames are searched in order. In addition, α is positive here. α may be set so that the maximum value of the first term of the equation (7) is not exceeded by the maximum value of the second term, and may be a small value such as α = 0.0001.

This time, the processing unit 26 transmits the combination information of the teaching materials in order for 15 frames determined as the learning target to the requester as the teaching material learning schedule. The processing unit 36 of the information terminal 30 that inputs the teaching material learning schedule via the input / output unit 34 stores the teaching material learning schedule in the built-in storage unit, and displays the teaching material learning schedule on the display unit 32 by dividing it into the first frame to the fifteenth frame. (Steps F14 and F15 in FIG. 3). As a result, the learner can grasp the teaching material learning schedule for 15 frames in order.
The teaching material learning schedule received from the teaching material learning schedule determination server 20 can be displayed at any time by selecting "teaching material learning schedule display" from the menu (YES, F18 in steps F16 and F17).

According to this embodiment, there are a large number of teaching materials S ₁ , S ₂ , ... When it is desired to select teaching materials for 15 frames with a learning time of T, it is possible to determine the teaching materials for 15 frames and the learning order that are most suitable for improving the learner's examination results.

In the above-mentioned embodiment, the example in which the number of learning frames N is 15, has been described, but the description is not limited to 15. Further, the pretest server 10 calculates the correct answer rate pj for each learning element and returns it to the information terminal 30, but calculates the incorrect answer rate (1-p _j ) and returns it to the information terminal 30. Then, on the information terminal 30, the content of each learning element B _j and the wrong answer rate (1-p _j ) are displayed on the screen as a pair, and the teaching material learning schedule determination request is sent from the information terminal 30 to the teaching material learning schedule determination server 20. When transmitting to, the error rate (1-p _j ) for each learning element Bj may be included.

In addition, although the case where the scheduled learning time is T for all the teaching materials was explained, if the scheduled learning time _ti for each teaching material S _i is shorter or longer than T, 1 In some cases, it is possible to study multiple teaching materials with the learning time T for each frame. In this case, the scheduled learning time ti of each teaching material S _i is also stored in advance in the teaching material information storage unit, and whether or not the teaching material S _i is learned in the kth frame is represented by the variable x _ik (x _{ik )} . Learning the teaching material S _i whose value is 1 in the kth frame), using the mathematical planning method,
Goal function
Maximize Σ _i Σ _j Σ _k (1-p _j ) ・ r _j・ v _ij・ x _ik
＋ α ・ Σ _i Σ _k w _ik・ x _ik・ ・ ・ (11)
α: Weighting coefficient constraint condition expression
Subject to Σ _k x _ik ≤ 1, ∀i ・ ・ ・ (12)
Σ _i t _i x _ik ≤ T, ∀k ・ ・ ・ (13)
x _i ∈ {0,1}, ∀i ・ ・ ・ (14)
It is possible to determine the learning target teaching materials for N frames in order while allowing the case where a plurality of teaching materials are selected in one frame. Here, α is positive. In addition, when a plurality of teaching materials are selected for one frame, the learning order in the frame does not matter.

Further, in the above-described examples and modifications, the ordering index _wik is smaller for teaching materials that are more advantageous for learning in the first order among different teaching materials with the same learning frame ranking, and for different learning frame rankings in the same teaching material. The index is set to increase as the ranking goes down, but conversely, the index becomes larger for teaching materials that are more advantageous for learning in the first ranking among different teaching materials with the same learning frame ranking, and between different learning frame rankings for the same teaching material. The index may be set to become smaller as the ranking is lowered.
Unlike this, when α in Eqs. (7) and (11) is used as a negative coefficient and the weighting subtraction of the first term and the second term is performed, learning in the first order is performed between different teaching materials with the same learning frame order. The more advantageous the teaching material, the smaller the index, and the lower the ranking between the different learning frame rankings in the same teaching material, the smaller the index. The more advantageous teaching materials, the larger the index, and the lower the ranking between different learning frame rankings in the same teaching material, the larger the index may be set.

Further, in the above-mentioned examples and modifications, in the first term of the formula (7) or the formula (11), all kinds of learning elements are added, but the question is not given in the next English test Z. When a plurality of learning elements are known in advance, the teacher side can arbitrarily set the type of learning element to be added in the first term by the operation unit (not shown) of the teaching material learning schedule determination server 20. When the processing unit 26 receives the teaching material learning schedule determination request from the information terminal 30 and searches in order the optimum combination of teaching materials for N frames by the mathematical planning method, the first of the formulas (7) or (11). The types of learning elements to be added in the term may be limited to the range set by the teacher.
Alternatively, when the learner selects "teaching material learning schedule determination" in the menu selection by the information terminal 30, the processing unit 36 displays a submenu for setting the type of learning element, so that the learner can select the type of learning element desired. Is arbitrarily set, and when the learner sets the type of the desired learning element by the operation unit 31 and then performs the teaching material learning schedule determination request operation, the processing unit 36 includes the type of the learning element set by the learner. When sending the teaching material learning schedule determination request to the teaching material learning schedule determination server 20, and receiving the request, the processing unit 26 searches for the optimum combination of teaching materials for N frames in order by the mathematical programming method (7). ) Or the type of the learning element to be added in the first term of the equation (11) may be limited to the range set by the learner.

Further, in the above-mentioned examples and modifications, the case where the ordering index is determined by using the difficulty level of the teaching material as an index has been described, but the present invention is not limited to this, and for example, a grammar which is one of the learning elements. It is easier to understand the teaching materials if it is not difficult, and it is thought that it is effective to prepare for the English test Z by learning the teaching materials with high grammar learning effect later, so the learning effect of the grammar of each teaching material The ordering index may be determined using the degree ( _vi1 ) as an index.
Specifically, when the weighting coefficient α of the target function is positive, the index for ordering index _wik becomes smaller as the learning effect of grammar is smaller among different teaching materials with the same learning frame ranking, and the learning ranking is smaller for the same teaching material. The index is set to increase as the learning order decreases, or the index increases as the learning effect of grammar is smaller between different teaching materials with the same learning frame order, and the index decreases as the learning order decreases for the same teaching material. Stipulated in. If α is negative, is it decided that the index becomes smaller as the learning effect of grammar is smaller between different teaching materials with the same learning frame ranking, and the index becomes smaller as the ranking decreases between different learning frame rankings with the same teaching material? Or, it is determined that the index becomes larger as the learning effect of grammar is smaller among different teaching materials with the same learning frame ranking, and the index becomes larger as the ranking decreases between different learning frame rankings with the same teaching material.

If there are multiple types of learning elements B _j1 , B _j2 , ..., Which are advantageous for preferential learning, the sum of the learning effects of the multiple types of learning elements (v _ij1 + v _ij2 + ...) When the _weighting coefficient α of the target function is positive, the index becomes smaller as the sum of the learning effects of multiple types of learning elements is larger among different teaching materials in the same learning frame order. In the same teaching material, the index is set to increase as the learning order decreases, or the index increases as the sum of the learning effects of multiple types of learning elements is larger among different teaching materials with the same learning frame order, and the same teaching material. Then, it may be set so that the index becomes smaller as the learning order is lowered. When α is negative, the index is set to be smaller for teaching materials with a larger sum of learning effects of multiple types of learning elements among different teaching materials with the same learning frame ranking, and the index is set to be smaller as the learning ranking is lower for the same teaching material. Or, it is determined that the index becomes larger as the sum of the learning effects of multiple kinds of learning elements is larger among the teaching materials having the same learning frame order but different, and the index becomes larger as the learning order becomes lower in the same teaching material.

Also, if there are multiple types of learning elements B _j1 , B _j2 , ..., Which are advantageous to learn later, the sum of the learning effects of the multiple types of learning elements (v _ij1 + v _ij2 + ...) When the _weighting coefficient α of the target function is positive, the index becomes smaller as the sum of the learning effects of multiple types of learning elements is smaller among different teaching materials in the same learning frame order. For the same teaching material, the index is set to increase as the learning order decreases, or the index increases as the sum of the learning effects of multiple types of learning elements is smaller between different teaching materials with the same learning frame order, and the same teaching material. Then, the index may be set to become smaller as the learning order is lowered. When α is negative, the index is set to be smaller for teaching materials with a smaller sum of learning effects of multiple types of learning elements among different teaching materials with the same learning frame ranking, and the index is set to be smaller as the learning ranking is lower for the same teaching material. Or, if it is determined that the index becomes larger as the sum of the learning effects of multiple types of learning elements is smaller among different teaching materials with the same learning frame ranking, and the index becomes larger as the learning ranking decreases in the same teaching material. good.

Further, the case where the ordering exponent information storage unit 23 in FIG. 1 stores the ordering exponent itself defined in the two-dimensional numerical table as shown in FIG. 2 (1) has been described as an example. In the case of using as an index, the ordering index information storage unit 23 has a difficulty level m _i for each teaching material S _i and a w _ik = k · m _i for _obtaining the ordering index w i k from the difficulty level m _i . You may memorize the mathematical formula (k = 1, 2, ...) (When α is positive).
In this case, the processing unit 26 uses the equations (7) and (11) of the objective function used for searching the teaching material learning schedule.
Maximize Σ _i Σ _j Σ _k (1-p _j ) ・ r _j・ v _ij・ x _ik
＋ α ・ Σ _i Σ _{k k}・ mi ・ x _ik・ ・ ・ (15)
α: Weighting factor.
You can search as.
If α is negative, it may be replaced with the formula w _ij = mi / _k , for example.

In addition, when the learning effect level v _ij of a specific learning element B _j , which is advantageous to learn in the second order, is used as an index, when α is positive, w _ik = k · v _ij , and when α is negative, You may memorize the formula w _ik = v _ij / k. Furthermore, when the sum of the learning effects of specific multiple learning elements B _j1 , B _j2 ... (v _ij1 + v _ij2 + ...), which is advantageous to learn in the second order, is used as an index, α is positive. In that case, w _ik = k · (v _ij1 + v _ij2 + ···), and when α is negative, the formula w _ik = (v _ij1 + v _ij2 + ···) / k may be stored.

Further, since the learner may not be able to learn the total number of frames due to circumstances, when "determine the teaching material learning schedule" is selected from the menu displayed on the information terminal 30, the processing unit 36 sets the number of learning frames. Is displayed so that the learner can arbitrarily set the desired number of learning frames by operating the operation unit 31, and after the learner sets the desired number of learning frames by the operation unit 31, the teaching material learning schedule determination request operation Then, the processing unit 36 sends a teaching material learning schedule determination request including the number of learning frames to the teaching material learning schedule determination server 20, and the processing unit 26 sends the optimum teaching material for the number of frames set by the learner by the mathematical planning method. You may search for the combinations of the above in order.

In addition, although the above examples and modifications have been given by taking public or private English exams as examples, they are not limited to English exams, but other foreign language exams such as German and French, university entrance exams, and entrance exams. Of course, it is good for subjects such as mathematics and physics, and various qualification tests.
For example, in the case of mathematics test preparation, there are functions, figures, derivatives, integrals, probabilities, statistics, etc. as learning elements, but learning the functions first is advantageous for the test preparation, so the learning effect of the functions of each teaching material. The order index may be determined using the degree as an index. Specifically, when the weighting coefficient α of the target function is positive, the index for ordering is smaller for teaching materials with a higher learning effect of the function among different teaching materials with the same learning frame ranking, and the learning ranking is lower for the same teaching material. The index is set to be larger as the index is larger, or the index is set to be larger as the learning effect of the function is larger between different teaching materials with the same learning frame rank, and the index is set to be smaller as the learning rank is lower in the same teaching material. You can do it. If α is negative, the index will be smaller for teaching materials with a higher learning effect of the function among different teaching materials with the same learning frame ranking, and the index will be smaller for the same teaching material as the learning ranking is lower, or the same learning Among teaching materials that differ in frame order, the higher the learning effect of the learning element of the function, the larger the index, and in the same teaching material, the lower the learning order, the larger the index.

Alternatively, since it is advantageous for the test preparation to learn the statistics in the second order, the ordering index may be determined by using the learning effect of the statistics of each teaching material as an index. Specifically, when the weighting coefficient α of the target function is positive, the index for ordering becomes smaller as the learning effect of statistics is smaller between different teaching materials with the same learning frame ranking, and the learning ranking is lowered for the same teaching material. It may be set so that it becomes larger, or the index becomes larger as the learning effect of statistics becomes smaller among different teaching materials in the same learning frame order, and becomes smaller as the learning order becomes lower in the same teaching material. If α is negative, the index will be smaller for teaching materials with smaller statistical learning effectiveness among different teaching materials with the same learning frame ranking, and the same teaching material will be set to be smaller as the learning ranking is lower, or the same learning frame ranking will be used. Among different teaching materials, the smaller the learning effect of statistics, the larger the index, and the lower the learning ranking of the same teaching material, the larger the index.

Further, in the above-mentioned examples and modifications, the ordering index _wik has been described by taking a case where it is predetermined as an example, but it corresponds to the case where there is a learning element that the learner wants to learn in the priority learning frame order. It is also possible to change to the teaching material learning schedule determination system.
Specifically, FIG. 1 is modified as shown in FIG. 6, and in the ordering index information storage unit 23A of the teaching material learning schedule determination server 20A, each teaching material S corresponding to the learning element B _j arbitrarily designated by the learner If the weighting coefficient α of the target function is positive for the learning effect level _vij of _i for each teaching material and for each learning frame rank among N learning frames, the learning effect level is different between different teaching materials with the same learning frame ranking. The larger the index, the larger the exponent, and the lower the rank, the smaller the _exponent between different learning _{frame ranks} in the same teaching material. ) Is memorized (when α is negative, the index increases as the learning effect increases between different teaching materials with the same learning frame ranking, and the index increases as the ranking decreases between different learning frame rankings with the same teaching material. Store the formula to be converted to the exponent w _ik , for example, w _ik = k · v _ij (k = 1, 2, ...).

When the learner selects "teaching material learning schedule determination" in the menu selection by the information terminal 30A, the processing unit 36A displays a submenu for specifying the type of learning element to be learned in the priority learning frame order, thereby displaying the operation unit. When the learner specifies the type of the desired learning element B _J in the operation of 31, and then performs the teaching material learning schedule determination request operation, the processing unit 36 requests the teaching material learning schedule determination including the type of the designated learning element B _J. When the processing unit 26A, which is transmitted to the teaching material learning schedule determination server 20A and receives the request, searches in order the optimum combination of teaching materials for N frames by the mathematical planning method, the teaching material information storage unit 22 and the ordering index information. With reference to the storage unit 23A, the learning effect level v _iJ of the learning element B _J of each teaching material S _i is divided by k, and the ordering index w _ik (when α is positive) or the learning effect level v i J is _set to k. Using the powered ordering exponent _wik (when α is negative), the calculation of Eq. (7) or Eq. (11) is performed. As a result, the combinations of teaching materials for N frames are ordered in descending order of the learning effect of the learning elements B _J.

In the ordering index information storage unit 23A of the teaching material learning schedule determination server 20A in FIG. 6, the learning effect level v _ij of each teaching material S _i corresponding to the learning element B _j arbitrarily specified by the learner is set to the ordering index w _ik . Instead of storing the mathematical formula to be converted, as shown in FIG. 7, a plurality of two-dimensional numerical tables TB _j (j = 1, 2, ...) Prepared for each learning element are stored, and the learning element B is stored. In the j-th table TB _j corresponding to _j , the learning effect level v _ij of each teaching material S _i corresponding to the learning element B _j is set for each teaching material and for each learning frame ranking among N learning frames. When the weighting coefficient α of the function is positive, the index is set to be smaller as the learning effect is larger between different teaching materials with the same learning frame ranking, and the index is larger as the ranking is lower between different learning frame rankings with the same teaching material. Ordering index _wik (When α is negative, the index increases as the learning effect increases between different teaching materials with the same learning frame ranking, and the index increases as the ranking decreases between different learning frame rankings with the same teaching material. It is also possible to memorize the ordering index _wik ) itself determined as described above.

Further, also in the modified examples of FIGS. 6 and 7, the teacher side can arbitrarily set the type of learning element to be added in the first term by the operation unit (not shown) of the teaching material learning schedule determination server 20A. When the processing unit 26A receives the teaching material learning schedule determination request from the information terminal 30A and searches in order the optimum combination of teaching materials for N frames by the mathematical planning method, the first of the formulas (7) or (11). The types of learning elements to be added in the term may be limited to the range set by the teacher.
Alternatively, in the submenu when the learner selects "teaching material learning schedule determination" in the menu selection by the information terminal 30A, the type of learning element that the learner wants to learn in the priority learning frame order can be specified. In addition, the range of the learning elements to be added in the first term of the equation (7) or (11) can be arbitrarily set, and the learning element that the learner wants to learn by the operation unit 31 in the priority learning frame order. When the teaching material learning schedule determination request operation is performed after specifying the type of the learning element and setting the range of the desired learning elements to be added in the first term of the equation (7) or (11), the processing unit 36A has priority. A server for determining a teaching material learning schedule, including a type of learning element to be learned in the order of learning frames and a range of desired learning elements to be added in the first term of the equation (7) or (11). When the processing unit 26A that has sent to 20A and received the request searches in order the optimum combination of teaching materials for N frames by the mathematical programming method, it is added by the first term of the formula (7) or (11). The type of learning element to be used may be limited to the range set by the learner.

INDUSTRIAL APPLICABILITY The present invention can be applied to test preparation for various subjects such as university entrance examinations, entrance examinations, and qualification examinations, including preparations for language examinations such as English.

10 Pretest server 11 Pretest information storage unit 12, 24, 35 Program storage unit 14, 26, 36 Processing unit 20 Teaching material learning schedule determination server 21 Question question rate information storage unit 22 Teaching material information storage unit 23 Ordering index information Storage unit 24 Input / output unit 25 Program storage unit 30 Information terminal

Claims (21)

A first storage means in which the learner memorizes the question question rate for each of multiple types of learning elements in the past exams in a certain exam to be taken.
A second storage means for storing the expected learning effectiveness for each of a plurality of types of learning elements for a large number of teaching materials for one learning frame for each of the above-mentioned test preparations.
It is an index for ordering determined by teaching material and by the order of learning frames in N learning frames, and the index is smaller (larger) as the teaching material is more advantageous for learning in the first order among different teaching materials with the same learning frame ranking. ), A third storage means that stores information on the ordering index, which is set so that the index becomes larger (smaller) as the rank decreases between different learning frame ranks in the same teaching material.
Using the information stored in the first to third storage means and the information on the correct answer rate or the incorrect answer rate for each learning element in the preliminary test that the learner took in advance, the same teaching material has N learning frames. Under the constraint condition of learning only once in the number, the learning effect level and the learner's wrong answer rate for each learning element when N teaching materials are selected in order from a large number of teaching materials. The first value, which is the product of the question rate in the exam and the product of the question question rate for multiple types of predetermined learning elements and the selected N teaching materials, and each of the selected ordered N teaching materials. A search means for searching for N combinations of ordering that maximizes the value obtained by weighting and adding the second value obtained by adding the ordering index of the selection order for N teaching materials by the mathematical programming method.
A teaching material learning schedule determination device characterized by including. The third storage means is an ordering index determined for each teaching material and for each learning frame ranking among N learning frames, and it is advantageous to study in the first order among different teaching materials with the same learning frame ranking. The index is smaller (larger) as the teaching material is used, and the index is smaller (larger) as the ranking is lower between different learning frame rankings in the same teaching material.
The search means is such that when searching by the mathematical programming method, the first value and the second value are weighted and subtracted.
The teaching material learning schedule determination device according to claim 1. A learning element setting means for the learner or teacher to set the type of learning element when obtaining the first value by the mathematical programming method is provided.
When calculating the first value, the search means is based on the learning effect level for each learning element, the learner's error rate, and the test when N teaching materials are selected in order from a large number of teaching materials. The product of the question question rate of is added for multiple types of learning elements set by the learning element setting means and for the selected N teaching materials.
The teaching material learning schedule determination device according to claim 1 or 2, wherein the teaching material learning schedule is determined. A first storage means in which the learner memorizes the question question rate for each of multiple types of learning elements in the past exams in a certain exam to be taken.
A second storage means for storing the expected learning effectiveness and planned learning time for each of a plurality of types of learning elements for a large number of teaching materials for a certain test preparation.
It is an index for ordering determined by teaching material and by learning frame ranking among N learning frames, and the index is small (large) so that learning in the first order is advantageous among different teaching materials with the same learning frame ranking. , A third storage means that stores information on the ordering index, which is set so that the index becomes larger (smaller) as the rank decreases between different learning frame ranks in the same teaching material.
Using the information stored in the first to third storage means and the information on the correct answer rate or the incorrect answer rate for each learning element in the preliminary test that the learner took in advance, the same teaching material has N learning frames. The constraint that learning is done only once in the number, and the constraint that one or more teaching materials can be learned in one learning frame, but the total planned learning time of the teaching materials does not exceed the learning time for one frame. Under the conditions, the product of the learning effect level for each learning element, the error rate of the learner, and the question question rate in the exam when various N-frame teaching materials are selected in order from all the teaching materials is calculated in advance. The first value added for the learning elements in the specified range and the selected N-frame teaching materials, and the ordering index for each selection order of the selected ordered N-frame teaching materials are for N frames. A search means for searching a combination of ordered teaching materials for N frames, which maximizes the weighted addition of the second value added to the teaching materials, by a mathematical programming method.
A teaching material learning schedule determination device characterized by including. The third storage means is an ordering index determined for each teaching material and for each learning frame ranking among N learning frames, and it is advantageous to study in the first order among different teaching materials with the same learning frame ranking. The index is smaller (larger) as the teaching material is used, and the index is smaller (larger) as the ranking is lower between different learning frame rankings in the same teaching material.
The search means is such that when searching by the mathematical programming method, the first value and the second value are weighted and subtracted.
4. The teaching material learning schedule determination device according to claim 4. A learning element setting means for the learner or teacher to set the type of learning element when obtaining the first value by the mathematical programming method is provided.
When calculating the first value, the search means is the learning effect level for each learning element, the error rate of the learner, and the test when various teaching materials for N frames are selected in order from a large number of teaching materials. The product of the question question rate in is added for the multiple types of learning elements set by the learning element setting means and the teaching materials for the selected N frames.
The teaching material learning schedule determination device according to claim 4 or 5. The ordering index is based on the difficulty of the teaching materials.
The teaching material learning schedule determination device according to any one of claims 1 to 6, wherein the teaching material learning schedule is determined. The ordering index is defined by one or more specific learning elements that are advantageous for learning in the first order.
The teaching material learning schedule determination device according to any one of claims 1 to 6, wherein the teaching material learning schedule is determined. The ordering index is defined by one or more specific learning elements that are advantageous for learning in the second rank.
The teaching material learning schedule determination device according to any one of claims 1 to 6, wherein the teaching material learning schedule is determined. A first storage means in which the learner memorizes the question question rate for each of multiple types of learning elements in the past exams in a certain exam to be taken.
A second storage means for storing the expected learning effectiveness for each of a plurality of types of learning elements for a large number of teaching materials for one learning frame for each of the above-mentioned test preparations.
A specification means for designating a learning element that the learner wants to learn in the priority learning frame order from among multiple types of learning elements, and
From the learning effectiveness of each teaching material for the learning element specified by the designated means, the greater the learning effect between different teaching materials with the same learning frame ranking, by teaching material, by learning frame ranking among N learning frames. A third storage means that stores information for creating an ordering index that has a small (large) value and increases (smaller) as the rank decreases between different learning frame ranks in the same teaching material.
Using the information stored in the first to third storage means and the information on the correct answer rate or the incorrect answer rate for each learning element in the preliminary test that the learner took in advance, the same teaching material has N learning frames. Under the constraint condition of learning only once in the number, the learning effect level and the learner's wrong answer rate for each learning element when N teaching materials are selected in order from a large number of teaching materials. The first value, which is the product of the question rate in the exam and the product of the multiple types of learning elements determined in advance and the selected N teaching materials, and the selection of each of the selected N teaching materials in order. A search means for searching for N combinations of ordering that maximizes the value obtained by weighting and adding the second value obtained by adding the ranking index for N teaching materials by the mathematical programming method.
A teaching material learning schedule determination device characterized by including. The third storage means is based on the learning effectiveness of each teaching material for the learning element specified by the designated means, by the teaching material, by the learning frame ranking among the N learning frames, and between different teaching materials with the same learning frame ranking. Then, the larger the learning effect, the smaller (larger) the value, and the lower the ranking between different learning frame rankings in the same teaching material, the smaller (larger) the information for creating an ordering index is stored.
The search means is such that when searching by the mathematical programming method, the first value and the second value are weighted and subtracted.
10. The teaching material learning schedule determination device according to claim 10. The third storage means is for each learning element, for each teaching material, for each learning frame ranking among N learning frames, and for different teaching materials with the same learning frame ranking, the greater the learning effect corresponding to the learning element, the higher the value. The ordering index, which is smaller (larger) and becomes larger (smaller) as the ranking decreases between different learning frame rankings in the same teaching material, is memorized.
10. The teaching material learning schedule determination device according to claim 10. The third storage means is for each learning element, for each teaching material, for each learning frame ranking among N learning frames, and for different teaching materials with the same learning frame ranking, the greater the learning effect corresponding to the learning element, the higher the value. Make sure to memorize the ordering index, which is smaller (larger) and becomes smaller (larger) as the ranking decreases between different learning frame rankings in the same teaching material.
The search means is such that when searching by the mathematical programming method, the first value and the second value are weighted and subtracted.
10. The teaching material learning schedule determination device according to claim 10. A learning element setting means for the learner or teacher to set the type of learning element when obtaining the first value by the mathematical programming method is provided.
When calculating the first value, the search means is based on the learning effect level for each learning element, the learner's error rate, and the test when N teaching materials are selected in order from a large number of teaching materials. The product of the question question rate of is added for multiple types of learning elements set by the learning element setting means and for the selected N teaching materials.
The teaching material learning schedule determination device according to any one of claims 10 to 13, wherein the teaching material learning schedule is determined. A first storage means in which the learner memorizes the question question rate for each of multiple types of learning elements in the past exams in a certain exam to be taken.
A second storage means for storing the expected learning effectiveness and planned learning time for each of a plurality of types of learning elements for a large number of teaching materials for a certain test preparation.
A learning element designation means for designating a learning element that a learner wants to learn in a priority learning frame order from among multiple types of learning elements, and a learning element designation means.
From the learning effectiveness of each teaching material for the learning element specified by the designated means, the greater the learning effect between different teaching materials with the same learning frame ranking, by teaching material, by learning frame ranking among N learning frames. A third storage means that stores information for creating an ordering index that has a small (large) value and increases (smaller) as the rank decreases between different learning frame ranks in the same teaching material.
Using the information stored in the first to third storage means and the information on the correct answer rate or the incorrect answer rate for each learning element in the preliminary test that the learner took in advance, the same teaching material has N learning frames. The constraint that learning is done only once in the number, and the constraint that one or more teaching materials can be learned in one learning frame, but the total planned learning time of the teaching materials does not exceed the learning time for one frame. Under the conditions, the product of the learning effect level for each learning element, the error rate of the learner, and the question question rate in the exam when various N-frame teaching materials are selected in order from all the teaching materials is calculated in advance. The first value added for the specified multiple types of learning elements and the selected N-frame teaching materials, and the ordering index for each selection order of the selected ordered N-frame teaching materials are for N frames. A search means for searching the combination of ordered teaching materials for N frames, which maximizes the weighted and added value of the second value added to the teaching materials, by the mathematical programming method.
A teaching material learning schedule determination device characterized by including. The third storage means is based on the learning effectiveness of each teaching material for the learning element specified by the designated means, by the teaching material, by the learning frame ranking among the N learning frames, and between different teaching materials with the same learning frame ranking. Then, the larger the learning effect, the smaller (larger) the value, and the lower the ranking between different learning frame rankings in the same teaching material, the smaller (larger) the information for creating an ordering index is stored.
The search means is such that when searching by the mathematical programming method, the first value and the second value are weighted and subtracted.
15. The teaching material learning schedule determination device according to claim 15. The third storage means is for each learning element, for each teaching material, for each learning frame ranking among N learning frames, and for different teaching materials with the same learning frame ranking, the greater the learning effect corresponding to the learning element, the higher the value. The ordering index, which is smaller (larger) and becomes larger (smaller) as the ranking decreases between different learning frame rankings in the same teaching material, is memorized.
15. The teaching material learning schedule determination device according to claim 15. The third storage means is for each learning element, for each teaching material, for each learning frame ranking among N learning frames, and for different teaching materials with the same learning frame ranking, the greater the learning effect corresponding to the learning element, the higher the value. Make sure to memorize the ordering index, which is smaller (larger) and becomes smaller (larger) as the ranking decreases between different learning frame rankings in the same teaching material.
The search means is such that when searching by the mathematical programming method, the first value and the second value are weighted and subtracted.
15. The teaching material learning schedule determination device according to claim 15. A learning element setting means for the learner or teacher to set the type of learning element when obtaining the first value by the mathematical programming method is provided.
When calculating the first value, the search means is the learning effect level for each learning element, the error rate of the learner, and the test when various teaching materials for N frames are selected in order from a large number of teaching materials. The product of the question question rate in is added for the multiple types of learning elements set by the learning element setting means and the teaching materials for the selected N frames.
The teaching material learning schedule determination device according to any one of claims 10 to 18, wherein the teaching material learning schedule is determined. Provided an input means for inputting the information of the correct answer rate or the incorrect answer rate for each learning element in the preliminary test that the learner took in advance into the search means.
The teaching material learning schedule determination device according to any one of claims 1 to 19, wherein the teaching material learning schedule is determined. Provided a presentation means to present the search result by the search means to the learner,
The teaching material learning schedule determination device according to any one of claims 1 to 20, wherein the teaching material learning schedule is determined.

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