JP2019160260A - Teaching material learning schedule determining device - Google Patents

Abstract

To determine a learning schedule of teaching materials to improve your results in private trials.SOLUTION: An information storage units 21 to 23 store the rates of a plurality of types of problems, the measure of learning effect for every study element of a large number of teaching materials for one section of the material, and the index for ordering of at least the study in N top sections defined independently for the teaching-material for every study element of a private sector examination between teaching materials which are different at the same study rank, have the index becoming smaller with more advantageous study in the ranking, and the index becoming large as the rank falls with the same teaching materials. The processing unit 26 searches the N teaching materials with the maximum ordered N combinations of the learning effect degree for each learning element, the learning effect rate for a learner erroneous answer rate, and the value obtained by the N number of teaching materials, which are selected as the maximum ordered N combinations of N teaching materials, using the combination of the learning effect level and the learning effect degree of the learner's erroneous answer rate, using the positive answer rate for each of the learning elements in the preliminary test of the memory units 21 to 23.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a learning material learning schedule determination device, and more particularly to a learning material learning schedule determination device for improving results in a test.

  In recent years, with the globalization of business / communications and the spread of overseas travel, the need to learn foreign languages is increasing. In school education, how to improve the language skills of individual learners within a limited class time is an important issue. The computer-aided language learning system implemented in school education prepares a large number of language teaching materials of various difficulty levels, evaluates the language skills of individual learners in preliminary tests, and includes a number of language teaching materials. There are some that extract language teaching materials that match the learner's language skills and present them to the learner. For example, it extracts and presents language teaching materials with high grammar learning effects to learners with weak grammar, extracts and presents language teaching materials with high vocabulary learning effects to learners with weak vocabulary, For learners who are weak in weak sounds, plosives, liaisons (concatenation), disappearing sounds, abbreviations, etc., they can also extract and present language teaching materials with high learning effects.

By the way, in recruiting human resources in companies and selecting for overseas work, language skills are often evaluated based on the results of private language tests or public language tests conducted on a large scale in society. The language tests conducted outside these schools can be used to assess the language skills that can be used in the real world fairly accurately, and it makes sense to aim to improve the results of these language tests in school education. This 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 effective in improving the performance of language tests conducted in society. .

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

In invention of Claim 1,
A first storage means for storing a question assignment rate for each of a plurality of types of learning elements in a past test in a test that the learner is scheduled to take;
A second storage means for storing a degree of learning effect expected for each of a plurality of types of learning elements for a number of learning materials for each of the learning frames for the certain test measure;
An index for ordering determined by the learning material and the learning frame ranking among the N learning frames. The learning index that has the advantage of learning in the previous ranking between the different learning materials in the same learning frame ranking is smaller (larger) ), A third storage means for storing information on an index for ordering that is determined such that the index increases (decreases) 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 received in advance, the same teaching material has N learning frames. The learning effectiveness and learning error rate for each learning element when N materials are selected in order from various teaching materials under the constraint of learning only once at most And a first value obtained by adding the product of the question assignment rate in the exam for a plurality of predetermined learning elements and for the selected N teaching materials, and for each of the selected ordered N teaching materials Search means for searching for N combinations of ordering that maximizes a value obtained by weighting and adding a second value obtained by adding the ordering index of selection order for N teaching materials;
It is characterized by including.
In invention of Claim 2,
The third storage means is an index for ordering determined for each learning material and for each learning frame rank among the N learning frames, and it is advantageous to learn in the previous rank between different learning materials with the same learning frame rank. The learning index information is set so that the index is smaller (larger) and the index is smaller (larger) as the ranking is lower between different learning frames in the same teaching material.
The searching means performs weighted subtraction between the first value and the second value when searching by mathematical programming.
It is characterized by.
In invention of Claim 3,
A learning element setting means is provided for the learner or teacher to set the type of learning element when the first value is determined by mathematical programming.
When the first value is calculated, the search means determines the learning effect level for each learning element, the error rate of the learner, and the test when various N learning materials are selected from a large number of learning materials in order. The product of the question rate of questions is added for the multiple learning elements set by the learning element setting means and the selected N teaching materials,
It is characterized by.
In invention of Claim 4,
A first storage means for storing a question assignment rate for each of a plurality of types of learning elements in a past test in a test that the learner is scheduled to take;
A second storage means for storing a learning effect level and a planned learning time expected for each of a plurality of types of learning elements for a plurality of teaching materials for a certain test measure;
This is an index for ordering that is determined by the learning material and the learning frame ranking among the N learning frames, and the index is smaller (larger) between different learning materials with the same learning frame ranking, so that learning in the previous ranking is advantageous. A third storage means for storing information on an ordering index that is determined so that the index increases (decreases) 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 received in advance, the same teaching material has N learning frames. Restriction that only one learning is possible at most, and one or more teaching materials can be learned in one learning frame, but the total learning time of teaching materials does not exceed the learning time for one frame Under the conditions, the product of the learning effectiveness for each learning element, the error rate of the learner, and the question rate in the exam when the materials for N frames are selected from various teaching materials in order. The first value added for the learning elements in the defined range and the selected N-frame learning materials, and the ordering index for each selection order of the selected ordered N-frame learning materials are set for N frames. N values that maximize the weighted addition of the second value added for the learning material The number of combinations of the partial ordering of materials for, and search means for searching by mathematical programming,
It is characterized by including.
In invention of Claim 5,
The third storage means is an index for ordering determined for each learning material and for each learning frame rank among the N learning frames, and it is advantageous to learn in the previous rank between different learning materials with the same learning frame rank. The learning index information is set so that the index is smaller (larger) and the index is smaller (larger) as the ranking is lower between different learning frames in the same teaching material.
The searching means performs weighted subtraction between the first value and the second value when searching by mathematical programming.
It is characterized by.
In invention of Claim 6,
A learning element setting means is provided for the learner or teacher to set the type of learning element when the first value is determined by mathematical programming.
When the search means calculates the first value, the learning effect level for each learning element, the learner's error rate, and the test when various N frames of materials are selected in order from among a large number of materials The product of the question rate of questions at is added for the multiple learning elements set by the learning element setting means and for the selected N-frame teaching materials,
It is characterized by.
In invention of Claim 7,
The ordering index is based on the difficulty level of the teaching materials.
It is characterized by.
In invention of Claim 8,
The ordering index is based on one or more specific learning elements that are advantageous for learning in order of precedence,
It is characterized by.
In invention of Claim 9,
The ordering index is based on one or more specific learning elements that are advantageous for learning at a later rank,
It is characterized by.
In invention of Claim 10,
A first storage means for storing a question assignment rate for each of a plurality of types of learning elements in a past test in a test that the learner is scheduled to take;
A second storage means for storing a degree of learning effect expected for each of a plurality of types of learning elements for a number of learning materials for each of the learning frames for the certain test measure;
A designation means for designating a learning element that a learner wants to learn in a preferential learning frame rank from among a plurality of types of learning elements,
From the learning effect level of each learning material for the learning element specified by the designating means, the higher the learning effect level between different learning materials with the same learning frame rank, according to the learning frame rank by learning material and among the learning frame ranks among the N learning frames. Third storage means for storing information for creating an index for ordering that is smaller (larger) and 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 received in advance, the same teaching material has N learning frames. The learning effectiveness and learning error rate for each learning element when N materials are selected in order from various teaching materials under the constraint of learning only once at most And a first value obtained by adding the product of the question assignment rate in the exam and a plurality 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 by which a value obtained by weighting and adding a second value obtained by adding the ordering index for ranking to N teaching materials is maximized by mathematical programming;
It is characterized by including.
In the invention according to claim 11,
The third storage means is based on the learning effect level of each learning material for the learning element specified by the specifying means, and is based on the learning frame ranking among the learning frames in each of the learning materials and in the N learning frames. Then, the higher the learning effectiveness, the smaller the value (larger), and the information for creating an index for ordering that decreases (larger) as the ranking decreases between different learning frame rankings in the same material,
The searching means performs weighted subtraction between the first value and the second value when searching by mathematical programming.
It is characterized by.
In invention of Claim 12,
The third storage means has a larger learning effect level corresponding to a learning element between different learning materials in the same learning frame ranking for each learning element, for each learning material, and for each learning frame ranking among the N learning frames. An index for ordering that is smaller (larger) and larger (smaller) as the rank goes down between different learning frames in the same material,
It is characterized by.
In invention of Claim 13,
The third storage means has a larger learning effect level corresponding to a learning element between different learning materials in the same learning frame ranking for each learning element, for each learning material, and for each learning frame ranking among the N learning frames. Remember that the ordering index is smaller (larger) and smaller (larger) as the rank goes down between different learning frames in the same material,
The searching means performs weighted subtraction between the first value and the second value when searching by mathematical programming.
It is characterized by.
In invention of Claim 14,
A learning element setting means is provided for the learner or teacher to set the type of learning element when the first value is determined by mathematical programming.
When the first value is calculated, the search means determines the learning effect level for each learning element, the error rate of the learner, and the test when various N learning materials are selected from a large number of learning materials in order. The product of the question rate of questions is added for the multiple learning elements set by the learning element setting means and the selected N teaching materials,
It is characterized by.
In the invention of claim 15,
A first storage means for storing a question assignment rate for each of a plurality of types of learning elements in a past test in a test that the learner is scheduled to take;
A second storage means for storing a learning effect level and a planned learning time expected for each of a plurality of types of learning elements for a plurality of teaching materials for a certain test measure;
A learning element specifying means for specifying a learning element that a learner wants to learn in a priority learning frame rank from a plurality of types of learning elements,
From the learning effect level of each learning material for the learning element specified by the designating means, the higher the learning effect level between different learning materials with the same learning frame rank, according to the learning frame rank by learning material and among the learning frame ranks among the N learning frames. Third storage means for storing information for creating an index for ordering that is smaller (larger) and 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 received in advance, the same teaching material has N learning frames. Restriction that only one learning is possible at most, and one or more teaching materials can be learned in one learning frame, but the total learning time of teaching materials does not exceed the learning time for one frame Under the conditions, the product of the learning effectiveness for each learning element, the error rate of the learner, and the question rate in the exam when the materials for N frames are selected from various teaching materials in order. The first value added for the determined plural kinds 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 for N frames N is the largest value obtained by weighted addition of the second value added for the teaching materials of The number of combinations of Ma partial ordering of materials for, and search means for searching by mathematical programming,
It is characterized by including.
In the invention of claim 16,
The third storage means is based on the learning effect level of each learning material for the learning element specified by the specifying means, and is based on the learning frame ranking among the learning frames in each of the learning materials and in the N learning frames. Then, the higher the learning effectiveness, the smaller the value (larger), and the information for creating an index for ordering that decreases (larger) as the ranking decreases between different learning frame rankings in the same material,
The searching means performs weighted subtraction between the first value and the second value when searching by mathematical programming.
It is characterized by.
In the invention of claim 17,
The third storage means has a larger learning effect level corresponding to a learning element between different learning materials in the same learning frame ranking for each learning element, for each learning material, and for each learning frame ranking among the N learning frames. An index for ordering that is smaller (larger) and larger (smaller) as the rank goes down between different learning frames in the same material,
It is characterized by.
In the invention according to claim 18,
The third storage means has a larger learning effect level corresponding to a learning element between different learning materials in the same learning frame ranking for each learning element, for each learning material, and for each learning frame ranking among the N learning frames. Remember that the ordering index is smaller (larger) and smaller (larger) as the rank goes down between different learning frames in the same material,
The searching means performs weighted subtraction between the first value and the second value when searching by mathematical programming.
It is characterized by.
In the invention of claim 19,
A learning element setting means is provided for the learner or teacher to set the type of learning element when the first value is determined by mathematical programming.
When the search means calculates the first value, the learning effect level for each learning element, the learner's error rate, and the test when various N frames of materials are selected in order from among a large number of materials The product of the question rate of questions at is added for the multiple learning elements set by the learning element setting means and for the selected N-frame teaching materials,
It is characterized by.
In the invention of claim 20,
Providing an input means for inputting information on the correct answer rate or the incorrect answer rate for each learning element in the preliminary test that the learner has received in advance to the search means;
It is characterized by.
In the invention of claim 21,
Provided a presentation means for presenting the search results of the search means to the learner;
It is characterized by.

  According to the present invention, the learning material for N frames suitable for improving the student's examination results and the learning order can be determined from among a large number of public or private examination preparation materials that the learner plans to take. .

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 operation | movement of the process part of the information terminal in FIG. It is a flowchart which shows operation | movement of the process part of the server for pretests in FIG. It is a flowchart which shows operation | movement of the process part of the server for a learning material learning schedule determination 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 memorize | stored in the index information storage part for ordering of the teaching material learning schedule determination system of FIG.

  Hereinafter, the best mode 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. The learning material decision schedule system for English teaching materials allows the learner to learn English for the number of learning frames N = 15 in one frame T time (T may be 1 hour, 2 hours, 90 minutes, etc.) In this case, a combination of English teaching materials suitable for measures for a specific public or private English test Z performed outside is determined for a large number of English teaching materials prepared in advance. In making the decision, the question assignment rate for each English learning element in the past questions of the English test Z, the current academic ability of each learner's English learning element, and the learning effectiveness for each learning element of each teaching material are taken into account. Thus, the combination of English teaching materials that is most suitable for improving the results of the English test Z is determined. At the same time, the learning frame order of the teaching materials from the first frame to the 15th frame is also determined.

In FIG. 1, reference numeral 10 denotes a pretest server, of which 11 is a pretest information storage unit that stores a number of pretests and correct answers for examining 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 sound in listening, plosives, liaisons (concatenation), disappearing sounds, abbreviations are B _{3 to} B ₇ ,...), And the correct answer rate p _j for each learning element of the learner can be calculated. Here, the correct answer rate p _j is represented by a numerical value that is 1 when the answer is 100% (0 ≦ p _j ≦ 1). Reference numeral 12 denotes a program storage unit that stores a program for controlling the operation of the pretest server 10, reference numeral 13 denotes an input / output unit that inputs and outputs data and instructions to and from the outside, and reference numeral 14 denotes a processing unit. When a pretest call request is input from the outside via the input / output unit 13 based on the program stored in the program, it is read from the pretest information storage unit 11 and transmitted to the request source via the input / output unit 13 or externally. When a scoring request including a pretest answer is input from, a score is compared with the correct answer, and a correct answer rate for each learning element is calculated and transmitted to the request source.

20 is a server for determining teaching material learning schedules, and 21 of these are questions that have been given in all past exams of the English language test Z or in recent years (10 years or 5 years). Is a question assignment rate information storage unit that stores the question assignment rate r _j for each learning element B _j analyzed in advance by the teacher side. Here, the question assignment rate r _j is expressed by a numerical value that is 1 when the question assignment rate r _j is 100%. Assume that 0 ≦ r _j ≦ 1. Specifically, E _j the number of questions of the learning elements B _j of the last test, j = 1,2, ··, when is G, the Question presentation rate r _j,
r _j = E _j / (E ₁ + E ₂ + ·· + E _G )
It is calculated by.
22 are a large number of English teaching materials S _i (i = 1, 2,...) Prepared for each teacher (T = 1), and teaching materials S analyzed in advance for each teaching material. _This is a learning material information storage unit that stores a 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 as a positive value that increases as the learning effect level increases. It is assumed that the number of teaching materials S _i is much larger than 15.

As a measure of the English test Z, it is empirically selected that learning materials with high learning effectiveness for learning elements that are not good for learners and have high problem-answering ratios are used to improve results. It is effective for. Error rate of the learning elements _{B j (1-p j)} , Question presentation rate r _j of the learning elements B _j in English test Z, the learning effect of v _ij of learning elements B _j of materials S _i product (= D ), It is effective to learn the combination that maximizes D when 15 candidate learning materials for 15 frames are selected from any number of learning materials.
Such a combination expresses whether or not the learning material S _{i is} to be learned by a variable x _i (learns the learning material S _i whose value of x _i is 1), and is a mixed integer programming method which is one of mathematical programming methods. 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, in the mathematical programming method based on (1) to (3), the teaching materials for 15 frames can be extracted, but which learning material should be learned in each learning frame ranking from the first frame to the 15th frame. It is not required until.
Among the many teaching materials S ₁ , S ₂ ,..., The basic learning, low vocabulary level, easy understanding, few grammatical problems, etc. If you do this, there are things that are advantageous for understanding the learning materials that you will learn later. Considering this point, as described below, this embodiment pays attention to the learning frame ranking of teaching materials, and has a configuration that can determine the optimal combination of teaching materials for the learner's examination measures in order. Yes.

An ordering index information storage unit 23 stores information on the ordering index w _ik determined in advance by the teacher for each learning material and for each learning frame rank k (k = 1 to 15). The ordering index w _ik determines the most effective learning frame order for improving the grade of the external English test Z for 15 teaching materials that are candidates for learning from among a large number of teaching materials S ₁ , S _2. Used for. The ordering index w _ik is smaller here for the teaching materials that are advantageous in learning in the first rank between different learning materials in the same learning frame ranking, and the index increases as the ranking decreases in different learning frame rankings in the same learning material. It is determined as follows.

This ordering index w _ik can be determined by using, for example, the difficulty level of the teaching material (the difficulty level can be set, for example, as the vocabulary level of the teaching material). This is because, when the difficulty level of multiple learning materials that are candidates for learning is different, it is empirically learned to learn less difficult materials first and later to learn more difficult materials. This is because it is effective in improving academic ability. The ordering index w _ik may be set such that the lower the difficulty level between different learning materials in the same learning frame rank, the smaller the index, and the same learning material the larger the index as the learning frame ranking decreases.

For convenience of explanation, it is assumed that the total number of frames N ′ = 5, and the combinations of _five teaching materials s _{1 ′ to} s _{5 ′} that are tentative candidates for learning are indexed difficulty levels 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, if the larger value indicates that the difficulty level is higher, the ordering index w _{i′k ′} is set as shown in FIGS. 2 (1) and 2 (2), for example. In FIG. 2, numerical values are assumed to have a relationship of w _{i′k ′} = k ′ · m _{i ′} (where k ′ = 1, 2,..., I ′ = 1 ′, 2 ′,... 5 ′). An example is shown.
Here, the learning material s _{1 ′} is selected in the first frame, the learning material s _{3 ′} is selected in the second frame, the learning material s _{5 ′} is selected in the third frame, and the learning material s _{2 ′} is selected in the fourth frame. When you select teaching material s _{4 '} in frame 5,
U = w _{1'1 '} + w _3'2' + w _{5'3 '} + w _2'4' + w _{4'5 '}
Think of U like When five teaching materials s _{1 ′ to} s _{5 ′} are allocated to learning of a total of five frames in various orders without overlapping, the order in which U becomes the maximum is s _{4 ′} , s _{3 ′} , s _{5 ′} , s _{1 ′.} , S _{2 ′} , and in descending order of difficulty. Therefore, when there are _five learning candidate teaching materials s _{1 ′ to} s _{5 ′} , the order in which U is the largest is the best order for improving the results. Incidentally, the order in which U becomes the minimum is S _{2 ′} , S _{1 ′} , S _{5 ′} , S _{3 ′} , S _{4 ′} .

The order in which U becomes the maximum is expressed by a variable x _{i′k ′} whether or not the learning material S _{i ′} is learned in the k ′ frame (when x _{i′k ′} = 1, the learning material S _{i ′} is represented by k ′. Learning on the top), using mathematical programming,
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 the present embodiment, as will be described later, it is devised so that selection of teaching materials for N = 15 frames and determination of learning frame ranking can be performed at a time.
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 for each teaching material and for each learning frame ranking (see FIG. 2 (1)).

  24 is a program that uses mathematical programming to search for a combination of learning materials in order (such as a mathematical optimization solver (Gorobi), in which a target function, constraint expression, etc. are set). The stored program storage unit 25 is an input / output unit that exchanges data and commands 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 denotes a processing unit. 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 a program stored in the program storage unit 24, a question assignment rate information storage is performed. 15 English teaching materials for 15 frames are searched in order using the optimization planning method while referring to various information stored in the section 21, teaching material information storage section 22, and ordering index information storage section 23. Determined and sent to the requester.

Reference numeral 30 denotes an information terminal used by the learner, which receives a pretest, instructs the learning material learning schedule for 15 frames to be learned, and confirms the learning material learning schedule. Of these, 31 is an operation unit for performing menu display operation, pretest test operation, instruction operation for determining teaching material learning schedule, 32 is a display unit for displaying a menu screen, pretest test screen, teaching material learning schedule display screen, etc. 33 is a speaker for outputting listening sound, 34 is an input / output unit for exchanging data / commands with the outside, 35 is a menu display, pre-test call request, pre-test execution, teaching material learning schedule determination A program storage unit 36 for storing various programs for displaying requests, learning material learning schedules, etc., 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 in the operation unit 31. Call request, pretest, teaching material learning schedule decision request, teaching material learning schedule display To perform the processing.
The information terminal 30 can communicate with the pretest server 10 and the learning material learning schedule determination server 20 via a network (local network, public network, etc.).

Next, the operation of the above embodiment will be described with reference to FIGS. 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 a process of the learning material learning schedule determination server 20 4 is a flowchart showing the operation of a unit 26. Here, it is assumed that each of a large number of teaching materials S ₁ , S ₂ ,... Has a planned learning time 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 “determining” and “learning material learning schedule display” menus are displayed (step F1 in FIG. 3) and the “pretest” selection operation is performed, the processing unit 36 sends a pretest call request to an external device via the input / output unit 34. Transmit 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 in step F20 in FIG. 4, F21).

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 an answer through the operation unit 31. The pretest includes a number of problems for each of the various learning elements B _j (j = 1, 2,...).
When the answer input for all the questions in the pretest is completed and the learner performs an end operation, the processing unit 36 transmits a scoring request including the answer 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 in the pretest information storage unit 11, performs scoring, calculates the problem correct answer rate p _j for each learning element B _j , and learns element B _The correct answer rate p _j corresponding to the contents of _j is 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 the contents of the learning element B _j and the question correct answer rate p _j are displayed on the display unit 32. A pair is displayed (steps F8 and F9 in FIG. 3). Thereby, the learner can grasp the current English ability.

(2) Determination of teaching materials When a learner who has received a pretest performs a menu call operation and selects “deciding learning material learning schedule” on the screen (YES in step F10, YES in F1 and F11), the processing unit 36 performs pretesting. Has been executed, a teaching material learning schedule determination request including the correct answer rate p _j for each learning element B _j is transmitted to the learning material learning schedule determination server 20 via the input / output unit 34 (YES in step F12, F13). .
Based on the teaching material determination program stored in the program storage unit 24, the processing unit 26 that has input the request via the input / output unit 25 determines the problem correct answer rate p _{j for} each learning element B _j in the pretest, and question presentation rate r _j for each of the past problems learning elements B _j of stored in the question index information storage unit 21 English test Z, learning of the learning elements B _j of each materials S _i stored in the learning material information storage section 22 15 teaching materials that achieve the best results when the learner takes the English test Z by the optimal programming method using the effectiveness v _ij and the ordering index w _ik stored in the ordering index information storage unit 23 Are searched in order and determined (YES in step F30 of FIG. 5, F31).

Specifically, the variable x _ik represents whether or not the learning material Si is to be learned in the k-th frame (when x _ik is 1, the learning material S _i is learned in the k-th frame), and using mathematical programming,
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 factor constraint 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. Α is positive here. α may be set so that the maximum value of the first term of equation (7) does not exceed the maximum value of the second term, and may be a small value such as α = 0.0001.

At this time, the processing unit 26 transmits, to the request source, the learning material combination schedule with the order of the 15 frames determined as learning objects. The processing unit 36 of the information terminal 30 that has input the learning material learning schedule via the input / output unit 34 stores it in the built-in storage unit, and displays the learning material learning schedule on the display unit 32 from the first frame to the 15th frame. (Steps F14 and F15 in FIG. 3). Thereby, the learner can grasp the teaching material learning schedule for 15 frames with an order.
The learning material learning schedule received from the learning material learning schedule determination server 20 can be displayed at any time by selecting “Display learning material learning schedule” from the menu (YES in steps F16 and F17, F18).

According to this embodiment, there are a large number of teaching materials S ₁ , S ₂ ,... For public or private English test preparations that the learner plans to take, each of which is scheduled to be T, If the learning time is T and it is desired to select teaching materials for 15 frames, it is possible to determine the teaching materials for 15 frames and the learning order most suitable for improving the student's examination results.

In the above-described embodiment, an example in which the number of learning frames N is 15 has been described. However, the number is not limited to 15. In addition, the pretest server 10 calculates the correct answer rate pj for each learning element and sends it back to the information terminal 30, but calculates the error rate (1-p _j ) and sends it back to the information terminal 30. Thus, the information terminal 30 displays a screen with the content of each learning element B _j and the error rate (1-p _j ) as a pair, or sends a learning material learning schedule determination request from the information terminal 30 to the learning material learning schedule determination server 20. , The error rate (1-p _j ) for each learning element Bj may be included.

In addition, if any teaching materials is also scheduled learning time the case has been described where a T, Wakashi, the Toka short shopping than planned learning time t _i is T of each teaching materials S _i, are also mixed Toka long, 1 In some cases, a plurality of learning materials can be learned with a learning time T corresponding to a frame. In this case, the scheduled learning time t _i of each learning material S _i is also stored in the learning material information storage unit in advance, and whether or not the learning material S _i is learned at the k-th frame is represented by a variable x _ik (of x _ik learning teaching materials S _i the value becomes 1 in the k th frame), using a mathematical programming 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 factor constraint 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)
The learning target teaching materials for N frames can be determined with an order, while allowing a plurality of teaching materials to be selected for one frame. Here, α is positive. It should be noted that the learning order within a frame when a plurality of teaching materials are selected for one frame is not limited.

Further, in the above-described embodiments and modifications, the ordering index w _ik is smaller in the learning material that is advantageous in learning in the first order between different learning materials in the same learning frame ranking, and between different learning frame rankings in the same learning material. The index was set to increase as the ranking decreased, but conversely, between the different learning materials with the same learning frame ranking, the learning material with the advantage of learning in the previous ranking increased, and between the different learning frame rankings with the same learning material You may set so that an index may become small, so that a rank falls.
On the other hand, when α in Equations (7) and (11) is a negative coefficient and weighted subtraction of the first term and the second term is performed, learning in the previous order is performed between different learning materials with the same learning frame order. Set the index so that the index becomes smaller as the teaching material is advantageous and the index decreases as the ranking decreases between different learning frames in the same teaching material, or learning in the previous ranking is performed between different teaching materials in the same learning frame ranking. An advantageous teaching material may be set such that the index increases and the index increases as the ranking decreases between different learning frame rankings in the same teaching material.

Further, in the above-described embodiments and modifications, all kinds of learning elements are added in the first term of the formula (7) or the formula (11). In the case where 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 learning 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 for an optimal teaching material combination for N frames by mathematical programming, the first of the equations (7) or (11) is used. You may make it limit the kind of learning element added by a term to the range set by the teacher.
Alternatively, when the learner selects “study material learning schedule determination” by 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. If the learner sets a desired learning element type by the operation unit 31 and then performs a teaching material learning schedule determination request operation, the processing unit 36 includes the learning element type set by the learner. The learning unit learning schedule determination request is transmitted to the learning material learning schedule determination server 20, and the processing unit 26 having received the request searches for an optimal combination of teaching materials for N frames in order by mathematical programming (7). ) Or the type of learning element added in the first term of equation (11) may be limited to the range set by the learner.

In the above-described embodiments and modifications, the case where the ordering index is determined using the difficulty level of the teaching material as an index has been described. However, the present invention is not limited to this, and for example, a grammar that is one of learning elements. If you are not difficult, it is easier to understand the teaching materials, and it is considered effective to take the learning materials that have a high grammatical learning effect later as a measure for the English test Z. The ordering index may be determined using the degree (v _i1 ) as an index.
Specifically, when the weighting coefficient α of the target function is positive, the ordering index w _ik has a smaller index as the learning effect of the grammar less effective between the different learning materials in the same learning frame order, and the learning order in the same learning material Decrease the index so that the index becomes larger, or between the different learning materials in the same learning frame order, the lesser the learning effect of the grammar, the larger the index, the lower the learning rank in the same teaching material, the index becomes smaller Stipulated in Whether α is negative, the lesser the grammar learning effectiveness between different learning materials in the same learning frame ranking, the smaller the index, and the lower the ranking between different learning frame rankings in the same learning material, the smaller the index? Alternatively, the index is set such that the lesser the grammatical learning effect level between different learning materials in the same learning frame ranking, the higher the index, and the lower the ranking between different learning frame rankings in the same learning material, the larger the index.

Further, when there are a plurality of types of learning elements B _j1 , B _j2 ,... _That are advantageous to learn preferentially, the sum of the learning effect levels of the plurality of types of learning elements (v _ij1 + v _ij2 + _.. ) As an index, the ordering index w _ik is positive when the weighting coefficient α of the objective function is positive, and the teaching material having a larger sum of the learning effectiveness of multiple types of learning elements between the different learning materials in the same learning frame ranking is smaller, Set the index so that the lower the learning order for the same material, or the higher the index, the more the learning effect of the multiple learning elements between the different learning materials in the same learning frame order, the larger the index. Then, it may be determined so that the index decreases as the learning order decreases. When α is negative, the index is set so that the index becomes smaller as the sum of the learning effectiveness of multiple types of learning elements becomes larger between different learning materials in the same learning frame order, and the index decreases as the learning order decreases in the same learning material. Alternatively, between the different learning materials in the same learning frame ranking, the learning material having a larger sum of the learning effect levels of a plurality of types of learning elements has a larger index, and the same learning material has a larger index as the learning order decreases.

In addition, when there are a plurality of types of learning elements B _j1 , B _j2 ,... _That are advantageous to learn later, the sum of the learning effect levels of the plurality of types of learning elements (v _ij1 + v _ij2 + _.. ) If the weighting coefficient α of the target function is positive, the ordering index w _ik has a smaller index between the different learning materials with the same learning frame rank and the smaller the learning effect level of the multiple learning elements, Set the index so that the lower the learning rank for the same learning material, or the smaller the learning effect level of the multiple learning elements between the different learning materials in the same learning frame ranking, the higher the index, and the same learning material Then, it may be determined so that the index decreases as the learning rank decreases. When α is negative, the index is set to be smaller for different learning materials with the same learning frame ranking, with a smaller learning effect sum of multiple types of learning elements, and with the same learning material the lower the learning ranking, the smaller the index. Or, between different learning materials with the same learning frame order, the index becomes larger as the learning effect of the learning elements of the plurality of learning elements is smaller, and the index becomes larger as the learning order decreases in the same learning material. good.

Further, the ordering index information storage unit 23 in FIG. 1 has been described by taking as an example the case where the ordering index itself defined by the two-dimensional numerical table as shown in FIG. 2 (1) is stored. If the index is, the materials S _i different difficulty levels m _i is the ordering for the index information storage unit 23, for determining the index w _ik for ordering from difficulty levels _{m i w ik = k · m} i (K = 1, 2,...) May be stored (when α is positive).
In this case, the processing unit 26 obtains the equations (7) and (11) of the target function used for searching the learning 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 · m _i · x _ik (15)
α: Weighting coefficient.
The search can be performed as
If α is negative, it can be replaced with, for example, a mathematical formula of w _ij = m _i / k.

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

  In addition, since the learner may not be able to learn the total number of frames due to circumstances, the sub-menu in which the processing unit 36 sets the number of learning frames when “determine learning material learning schedule” is selected from the menu displayed on the information terminal 30. , 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 learning material learning schedule determination request operation Then, the processing unit 36 transmits a learning material learning schedule determination request including the number of learning frames to the learning material learning schedule determination server 20, and the processing unit 26 uses the mathematical programming method to determine the optimal teaching materials for the number of frames set by the learner. The combinations may be searched in order.

Moreover, in the above-mentioned examples and modifications, public or private English exams have been described as examples, but they are not limited to English exams, other foreign language exams such as German and French, university entrance exams and entrance exams Of course, subjects such as mathematics, physics, etc., and various qualification exams may be targeted.
For example, in the case of mathematics test preparation, there are functions, figures, differentiation, integration, probability, statistics, etc. as learning elements, but learning the function in the first order is advantageous for test preparation, so the learning effect of the function 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 has a smaller index as the learning effect of the function increases between different learning materials with the same learning frame rank, and the learning rank decreases with the same learning material. Set the index so that the index increases, or between different teaching materials in the same learning frame order, the index increases as the learning effect of the function increases and the index decreases as the learning rank decreases in the same teaching material You can do that. If α is negative, set the index so that the index of the learning material with the higher learning effect of the function between the different learning materials in the same learning frame rank becomes smaller, and the index decreases as the learning rank decreases with the same learning material. It is only necessary to determine that an index with a learning effect of a function learning element having a larger learning effect is larger between teaching materials having different frame ranks, and that the index increases with a decrease in the learning order with the same learning material.

  Alternatively, since it is advantageous for the examination measures to learn the statistics in the rear rank, the order index may be determined using the learning effect of the statistics of each teaching material as an index. Specifically, when the weighting coefficient α of the objective function is positive, the index for ordering becomes smaller as the learning effect of statistics is smaller between different learning materials with the same learning frame ranking, and the learning ranking decreases with the same learning material. It may be determined so that the index increases as the learning effect level of statistics decreases between different learning materials with the same learning frame ranking, or decreases as the learning ranking decreases with the same learning material. If α is negative, set the index so that the lesser the learning effectiveness of the statistics, the smaller the index between the different learning materials in the same learning frame ranking, the smaller the learning ranking in the same learning material, or the same learning frame ranking Therefore, it is possible to set the index so that the lesser the learning effect of statistics is, the higher the index is between different teaching materials, and the larger the learning order is, the lower the learning order is.

Further, in the above-described embodiments and modifications, the ordering index w _ik has been described as an example, but it corresponds to the case where there is a learning element that the learner wants to learn in the preferential learning frame ranking. It is also possible to change to a learning material learning schedule determination system.
Specifically, FIG. 1 is changed as shown in FIG. 6, and each learning material S _j corresponding to the learning element B _j arbitrarily designated by the learner is stored in the ordering index information storage unit 23A of the learning material learning schedule determination server 20A. _If the learning effect level v _ij of _{i is determined by} the learning material and the learning frame rank among the N learning frames, and the weighting coefficient α of the target function is positive, the learning effect level is different between different learning materials in the same learning frame rank. The larger the index is, the larger the index is, and the lower the ranking is, the lower the index is between the different learning frame rankings in the same teaching material. The formula is converted into an ordering index w _ik , for example, w _ik = v _ij / k (k = 1, 2,... (If α is negative, the index increases as the learning effect increases between different learning materials in the same learning frame ranking, and the index increases as the ranking decreases between different learning frame rankings in the same learning material ranking) For index w _ik Formula to be converted, for example, w _ik = k · v _ij (k = 1, 2,...) Is stored).

When the learner selects “determine learning material learning schedule” by menu selection by the information terminal 30A, the processing unit 36A displays a submenu for designating the type of learning element to be learned in the preferential learning frame order, thereby operating the operation unit When the learner designates a desired learning element B _J type in the operation 31 and then performs a learning material learning schedule determination request operation, the processing unit 36 issues a learning material learning schedule determination request including the designated learning element B _J type. The processing unit 26A, which is transmitted to the learning material learning schedule determination server 20A and receives the request, searches for the optimal combination of teaching materials for N frames by mathematical programming, with the teaching material information storage unit 22 and the ordering index information. by referring to the storage unit 23A, the learning elements (if α is positive) B _J learning degree v _iJ Xu and ordering for index at k w _ik of each materials S _i, Others with learning degree v _iJ ordering for index was multiplied by k to w _ik (if α is negative), the equation (7) or (11) of the calculation. Thereby, the combinations of the teaching materials for N frames are ordered in descending order of the learning effect level of the learning element B _J.

The learning effect level v _ij of each learning material S _i corresponding to the learning element B _j arbitrarily specified by the learner is stored in the ordering index w _ik in the ordering index information storage unit 23A of the learning material learning schedule determination server 20A of FIG. Instead of storing the mathematical expression to be converted, a plurality of two-dimensional numerical tables TB _j (j = 1, 2,...) Prepared for each learning element are stored as shown in FIG. _In the j-th table TB _j corresponding to _j , the learning effect level v _ij of each learning material S _i corresponding to the learning element B _j is set according to the learning frame ranking among the learning frames and the learning frame rank among the N learning frames. When the weighting coefficient α of the function is positive, the index is smaller as the learning effect level is larger between different learning materials in the same learning frame ranking, and the index is larger as the ranking decreases between different learning frame rankings in the same learning material. ordering for the index w _ik (α is negative If, in between different materials with the same learning frame rank the greater the index larger materials are learning degree, the ordering for index w _ik which defines as index higher rank decreases becomes large between different learning frame rank the same materials) You may make it memorize itself.

Also, in the modified examples of FIGS. 6 and 7, the teacher can arbitrarily set the type of learning element to be added in the first term by the operation unit (not shown) of the learning 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 for the optimal combination of teaching materials for N frames by mathematical programming, the first of the equations (7) or (11) is used. You may make it limit the kind of learning element added by a term to the range set by the teacher.
Alternatively, in the submenu when the learner selects “determine learning material learning schedule” by menu selection by the information terminal 30A, the learner can specify the type of learning element that the learner wants to learn in the preferential learning frame order. In addition, the range of learning elements to be added in the first term of the expression (7) or (11) can be arbitrarily set, and the learning element that the learner wants to learn with the priority learning frame rank by the operation unit 31. When the teaching material learning schedule determination requesting operation is performed after setting the range of the desired learning element to be added in the first term of the expression (7) or (11), the processing unit 36A is given priority. A learning material learning schedule determination request including a learning element type to be learned in the learning frame order and a desired learning element range to be added in the first term of the expression (7) or (11) When the processing unit 26A receives the request and searches for the optimum combination of teaching materials for N frames by mathematical programming, the formula (7) or (11) The type of learning element added in the first term may be limited to a range set by the learner.

  The present invention can be applied to test preparations for various subjects such as university entrance examinations, entrance examinations, and qualification examinations, as well as language examination preparations such as English.

DESCRIPTION OF SYMBOLS 10 Pretest server 11 Pretest information storage part 12, 24, 35 Program storage part 14, 26, 36 Processing part 20 Teaching material learning schedule determination server 21 Problem question rate information storage part 22 Teaching material information storage part 23 Indexing information for ordering Storage unit 24 Input / output unit 25 Program storage unit 30 Information terminal

Claims (21)

A first storage means for storing a question assignment rate for each of a plurality of types of learning elements in a past test in a test that the learner is scheduled to take;
A second storage means for storing a degree of learning effect expected for each of a plurality of types of learning elements for a number of learning materials for each of the learning frames for the certain test measure;
An index for ordering determined by the learning material and the learning frame ranking among the N learning frames. The learning index that has the advantage of learning in the previous ranking between the different learning materials in the same learning frame ranking is smaller (larger) ), A third storage means for storing information on an index for ordering that is determined such that the index increases (decreases) 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 received in advance, the same teaching material has N learning frames. The learning effectiveness and learning error rate for each learning element when N materials are selected in order from various teaching materials under the constraint of learning only once at most And a first value obtained by adding the product of the question assignment rate in the exam for a plurality of predetermined learning elements and for the selected N teaching materials, and for each of the selected ordered N teaching materials Search means for searching for N combinations of ordering that maximizes a value obtained by weighting and adding a second value obtained by adding the ordering index of selection order for N teaching materials;
A learning material learning schedule determination device including: The third storage means is an index for ordering determined for each learning material and for each learning frame rank among the N learning frames, and it is advantageous to learn in the previous rank between different learning materials with the same learning frame rank. The learning index information is set so that the index is smaller (larger) and the index is smaller (larger) as the ranking is lower between different learning frames in the same teaching material.
The searching means performs weighted subtraction between the first value and the second value when searching by mathematical programming.
The learning material learning schedule determination device according to claim 1. A learning element setting means is provided for the learner or teacher to set the type of learning element when the first value is determined by mathematical programming.
When the first value is calculated, the search means determines the learning effect level for each learning element, the error rate of the learner, and the test when various N learning materials are selected from a large number of learning materials in order. The product of the question rate of questions is added for the multiple learning elements set by the learning element setting means and the selected N teaching materials,
The learning material learning schedule determination device according to claim 1 or 2, characterized in that: A first storage means for storing a question assignment rate for each of a plurality of types of learning elements in a past test in a test that the learner is scheduled to take;
A second storage means for storing a learning effect level and a planned learning time expected for each of a plurality of types of learning elements for a plurality of teaching materials for a certain test measure;
This is an index for ordering that is determined by the learning material and the learning frame ranking among the N learning frames, and the index is smaller (larger) between different learning materials with the same learning frame ranking, so that learning in the previous ranking is advantageous. A third storage means for storing information on an ordering index that is determined so that the index increases (decreases) 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 received in advance, the same teaching material has N learning frames. Restriction that only one learning is possible at most, and one or more teaching materials can be learned in one learning frame, but the total learning time of teaching materials does not exceed the learning time for one frame Under the conditions, the product of the learning effectiveness for each learning element, the error rate of the learner, and the question rate in the exam when the materials for N frames are selected from various teaching materials in order. The first value added for the learning elements in the defined range and the selected N-frame learning materials, and the ordering index for each selection order of the selected ordered N-frame learning materials are set for N frames. N values that maximize the weighted addition of the second value added for the learning material The number of combinations of the partial ordering of materials for, and search means for searching by mathematical programming,
A learning material learning schedule determination device including: The third storage means is an index for ordering determined for each learning material and for each learning frame rank among the N learning frames, and it is advantageous to learn in the previous rank between different learning materials with the same learning frame rank. The learning index information is set so that the index is smaller (larger) and the index is smaller (larger) as the ranking is lower between different learning frames in the same teaching material.
The searching means performs weighted subtraction between the first value and the second value when searching by mathematical programming.
The learning material learning schedule determination device according to claim 4. A learning element setting means is provided for the learner or teacher to set the type of learning element when the first value is determined by mathematical programming.
When the search means calculates the first value, the learning effect level for each learning element, the learner's error rate, and the test when various N frames of materials are selected in order from among a large number of materials The product of the question rate of questions at is added for the multiple learning elements set by the learning element setting means and for the selected N-frame teaching materials,
The learning material learning schedule determination device according to claim 4 or 5, characterized in that: The ordering index is based on the difficulty level of the teaching materials.
The teaching material learning schedule determination device according to any one of claims 1 to 6, wherein The ordering index is based on one or more specific learning elements that are advantageous for learning in order of precedence,
The learning material learning schedule determination device according to any one of claims 1 to 6, wherein The ordering index is based on one or more specific learning elements that are advantageous for learning at a later rank,
The learning material learning schedule determination device according to any one of claims 1 to 6, wherein A first storage means for storing a question assignment rate for each of a plurality of types of learning elements in a past test in a test that the learner is scheduled to take;
A second storage means for storing a degree of learning effect expected for each of a plurality of types of learning elements for a number of learning materials for each of the learning frames for the certain test measure;
A designation means for designating a learning element that a learner wants to learn in a preferential learning frame rank from among a plurality of types of learning elements,
From the learning effect level of each learning material for the learning element specified by the designating means, the higher the learning effect level between different learning materials with the same learning frame rank, according to the learning frame rank by learning material and among the learning frame ranks among the N learning frames. Third storage means for storing information for creating an index for ordering that is smaller (larger) and 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 received in advance, the same teaching material has N learning frames. The learning effectiveness and learning error rate for each learning element when N materials are selected in order from various teaching materials under the constraint of learning only once at most And a first value obtained by adding the product of the question assignment rate in the exam and a plurality 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 by which a value obtained by weighting and adding a second value obtained by adding the ordering index for ranking to N teaching materials is maximized by mathematical programming;
A learning material learning schedule determination device including: The third storage means is based on the learning effect level of each learning material for the learning element specified by the specifying means, and is based on the learning frame ranking among the learning frames in each of the learning materials and in the N learning frames. Then, the higher the learning effectiveness, the smaller the value (larger), and the information for creating an index for ordering that decreases (larger) as the ranking decreases between different learning frame rankings in the same material,
The searching means performs weighted subtraction between the first value and the second value when searching by mathematical programming.
The learning material learning schedule determination device according to claim 10. The third storage means has a larger learning effect level corresponding to a learning element between different learning materials in the same learning frame ranking for each learning element, for each learning material, and for each learning frame ranking among the N learning frames. An index for ordering that is smaller (larger) and larger (smaller) as the rank goes down between different learning frames in the same material,
The learning material learning schedule determination device according to claim 10. The third storage means has a larger learning effect level corresponding to a learning element between different learning materials in the same learning frame ranking for each learning element, for each learning material, and for each learning frame ranking among the N learning frames. Remember that the ordering index is smaller (larger) and smaller (larger) as the rank goes down between different learning frames in the same material,
The searching means performs weighted subtraction between the first value and the second value when searching by mathematical programming.
The learning material learning schedule determination device according to claim 10. A learning element setting means is provided for the learner or teacher to set the type of learning element when the first value is determined by mathematical programming.
When the first value is calculated, the search means determines the learning effect level for each learning element, the error rate of the learner, and the test when various N learning materials are selected from a large number of learning materials in order. The product of the question rate of questions is added for the multiple learning elements set by the learning element setting means and the selected N teaching materials,
The learning material learning schedule determination device according to any one of claims 10 to 13, characterized in that: A first storage means for storing a question assignment rate for each of a plurality of types of learning elements in a past test in a test that the learner is scheduled to take;
A second storage means for storing a learning effect level and a planned learning time expected for each of a plurality of types of learning elements for a plurality of teaching materials for a certain test measure;
A learning element specifying means for specifying a learning element that a learner wants to learn in a priority learning frame rank from a plurality of types of learning elements,
From the learning effect level of each learning material for the learning element specified by the designating means, the higher the learning effect level between different learning materials with the same learning frame rank, according to the learning frame rank by learning material and among the learning frame ranks among the N learning frames. Third storage means for storing information for creating an index for ordering that is smaller (larger) and 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 received in advance, the same teaching material has N learning frames. Restriction that only one learning is possible at most, and one or more teaching materials can be learned in one learning frame, but the total learning time of teaching materials does not exceed the learning time for one frame Under the conditions, the product of the learning effectiveness for each learning element, the error rate of the learner, and the question rate in the exam when the materials for N frames are selected from various teaching materials in order. The first value added for the determined plural kinds 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 for N frames N is the largest value obtained by weighted addition of the second value added for the teaching materials of The number of combinations of Ma partial ordering of materials for, and search means for searching by mathematical programming,
A learning material learning schedule determination device including: The third storage means is based on the learning effect level of each learning material for the learning element specified by the specifying means, and is based on the learning frame ranking among the learning frames in each of the learning materials and in the N learning frames. Then, the higher the learning effectiveness, the smaller the value (larger), and the information for creating an index for ordering that decreases (larger) as the ranking decreases between different learning frame rankings in the same material,
The searching means performs weighted subtraction between the first value and the second value when searching by mathematical programming.
The learning material learning schedule determination device according to claim 15, wherein: The third storage means has a larger learning effect level corresponding to a learning element between different learning materials in the same learning frame ranking for each learning element, for each learning material, and for each learning frame ranking among the N learning frames. An index for ordering that is smaller (larger) and larger (smaller) as the rank goes down between different learning frames in the same material,
The learning material learning schedule determination device according to claim 15, wherein: The third storage means has a larger learning effect level corresponding to a learning element between different learning materials in the same learning frame ranking for each learning element, for each learning material, and for each learning frame ranking among the N learning frames. Remember that the ordering index is smaller (larger) and smaller (larger) as the rank goes down between different learning frames in the same material,
The searching means performs weighted subtraction between the first value and the second value when searching by mathematical programming.
The learning material learning schedule determination device according to claim 15, wherein: A learning element setting means is provided for the learner or teacher to set the type of learning element when the first value is determined by mathematical programming.
When the search means calculates the first value, the learning effect level for each learning element, the learner's error rate, and the test when various N frames of materials are selected in order from among a large number of materials The product of the question rate of questions at is added for the multiple learning elements set by the learning element setting means and for the selected N-frame teaching materials,
The learning material learning schedule determination device according to any one of claims 10 to 18, wherein Providing an input means for inputting information on the correct answer rate or the incorrect answer rate for each learning element in the preliminary test that the learner has received in advance to the search means;
The learning material learning schedule determination device according to any one of claims 1 to 19, wherein Provided a presentation means for presenting the search results of the search means to the learner;
The learning material learning schedule determination device according to any one of claims 1 to 20, wherein

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