JP2020118864A - Determination device of achievement condition of practical skill level, determination method, program, and recording medium - Google Patents

Abstract

To provide a determination device of achievement conditions of a practical skill level in which a learning method can effectively be connected to improve the practical skill level.SOLUTION: A determination device 1 of achievement conditions of a practical skill level comprises: a memory unit 10 comprising a question memory unit 101 for storing a work-related question for a learner to learn work, and a worker information memory unit 102 for associating the practical skill level evaluated on the basis of the practical skill of the worker as worker information with correctness results on the work-related question, which are stored every worker; a correlative information generating unit 11 for generating the first correlative information of the practical skill level, a correct answer rate to the work-related question and work-related questions to answer correctly every practical skill level on the basis of the worker information of the worker belonging to the same practical skill level; and a determination unit 12 for determining the correct answer rate and the question to be answered correctly among the work-related questions necessary for the learner to clear the target practical skill level on the basis of the first correlative information.SELECTED DRAWING: Figure 1

Description

The present invention relates to a practical level achievement condition determination device, a determination method, a program, and a recording medium.

In recent years, due to the decrease in the number of agricultural workers and the aging of the population, it is important to introduce inexperienced people and to train young people. However, due to the lack of manpower, it is difficult to provide sufficient education only with practical training in the field. For this reason, it has been attempted to improve the knowledge of work for the inexperienced person, etc. by learning to solve various problems related to farm work, in addition to on-site practical education.

However, although the learner such as the inexperienced person increases the response rate by repeatedly solving the problem, there is a problem that the actual skill level of the learner is not involved when actually working in the field. .. Such problems also occur regardless of agricultural work, for example, in work related to production in a factory.

Therefore, an object of the present invention is to provide a new system for effectively connecting a learning method for solving a practice problem to the improvement of a practical skill level of an inexperienced person or the like.

In order to achieve the above-mentioned object, the determination device of the achievement condition of the practical skill level of the present invention,
Including a storage unit, a correlation information generation unit, and a determination unit,
The storage unit includes a problem storage unit and a worker information storage unit,
The problem storage unit is
Remembers multiple work-related problems for the learner to learn work,
The worker information storage unit,
For each worker, as worker information, a practical skill level evaluated based on the practical skill of the worker and a correctness result regarding the plurality of work-related problems are stored in association with each other,
The correlation information generation unit,
Based on worker information of workers who belong to the same skill level, first correlation information is generated for each of the skill levels, the skill level, a correct answer rate for the plurality of work related questions, and a work related question to be correctly answered. ,
The determination unit,
It is characterized in that, based on the first correlation information, a correct answer rate required for the learner to clear a desired practical skill level and a correct answer out of the plurality of questions are determined.

The method for determining the achievement level of the practical skill level of the present invention is
Including a correlation information generation step and a judgment step,
Using the dataset,
The data set includes a problem data set and a worker information data set,
The problem data set is
Includes multiple work-related problems for learners to learn work,
The worker information data set is
For each worker, as worker information, a skill level evaluated on the basis of the skill of the worker, and a correct/wrong result of the plurality of work-related problems, a data set associated with each other,
The correlation information generating step,
Based on worker information of workers who belong to the same skill level, first correlation information is generated for each of the skill levels, the skill level, a correct answer rate for the plurality of work related questions, and a work related question to be correctly answered. ,
The determination step is
Based on the first correlation information, a correct answer rate necessary for clearing a target practical skill level and a question to be answered correctly among the plurality of questions are determined.

A program of the present invention causes a computer to execute the determination method of the present invention.

The recording medium of the present invention is a computer-readable recording medium in which the program of the present invention is recorded.

According to the present invention, it is possible to determine a correct answer rate and a work-related question that should be correct, which are necessary for clearing a target practical skill level. Therefore, for example, the learner learns the work-related problem to be correctly answered according to the practical skill level of the learner such as an inexperienced person, and clears the required correct answer rate to thereby , It is possible to effectively reach the desired practical level.

FIG. 1 is a block diagram illustrating an example of the determination device according to the first embodiment. FIG. 2 is a block diagram showing an example of the hardware configuration of the determination device according to the first embodiment. FIG. 3 is a flowchart showing an example of the determination method of the first embodiment.

In the present invention, the “learned person” is a person who performs work learning using the determination device and the determination method of the present invention, and specifically, performs learning by solving the work-related problem. Those who do.

In the present invention, the “practical skill level” means, for example, a level evaluated by a specialist based on work (actual skill) at an actual site. The expert is not particularly limited and can be appropriately determined according to the field of work, and in the case of farm work, there are farm workers with high experience values, technical instructors and the like. The level of the practical skill level is not particularly limited and may be two or more levels, and can be classified into, for example, 2 to 20 levels. Also, the notation indicating the practical skill level is not particularly limited, and is represented by, for example, “level 1”, “level 2”, etc., “learn required”, “pass”, “serious farming”, “instruction possible”, etc. Good.

In the present invention, “work” is not particularly limited, and works in various fields are targeted. For example, in the field of agriculture, it is general agricultural work, and for example, in the case of a live industry in a factory, it is general processing steps in a factory. Hereinafter, the agricultural work in the field of agriculture will be described as an example, but the present invention is not limited thereto.

An embodiment of the present invention will be described. The present invention is not limited to the embodiments below. In each of the following figures, the same parts are designated by the same reference numerals. In addition, the description of each embodiment can be applied to each other unless otherwise specified. Furthermore, the configurations of the respective embodiments can be combined unless otherwise specified.

[Embodiment 1]
An example of the determination device and the determination method of the present invention will be described with reference to the drawings.

FIG. 1 is a block diagram showing an example of the determination device of this embodiment. The determination device 1 includes a storage unit 10, a correlation information generation unit 11, and a determination unit 12, and may further include, for example, an input unit 13 and an output unit 14. The determination device 1 is also referred to as a determination system, for example. The determination device 1 may be, for example, one device including the above-mentioned units, or may be a device in which the above-mentioned units are connectable via a communication network.

The communication line network is not particularly limited, and a known communication line network can be used and may be wired or wireless. Examples of the communication line network include an Internet line, a telephone line, a LAN (Local Area Network), and a WiFi (Wireless Fidelity). The processing of each unit of the determination device 1 may be performed on the cloud.

The storage unit 10 includes a problem storage unit 101 and a worker information storage unit 102. The problem storage unit 101 stores a plurality of work-related problems. The work-related problem is a problem for allowing a learner to learn work. The problem storage unit 101 may store, for example, the work-related question as a data set. In this case, an answer to the work-related question is stored in association with the work-related question, and the explanation of the answer is further linked. May be stored.

The worker information storage unit 102 stores worker information for each worker. In the worker information, the skill level evaluated based on the skill of the worker and the correct/wrong results of the plurality of work-related problems are associated with each other. The worker is a worker whose practical skill level is evaluated in advance, and includes, for example, a skilled worker, a worker with a high experience value, a general worker, an inexperienced worker, an inexperienced worker, and the like. Since the worker information stored in the worker information storage unit 102 is information for generating correlation information described later, it is preferable that a plurality of worker information be stored for each practical skill level, for example. The correctness result is, for example, a correctness (correctness/incorrectness) about each of the work-related problems, a correct answer rate of the plurality of work-related problems, and the like.

The various information may be input by the input unit 13 or may be stored in the storage unit 10 in advance, for example. The input unit 13 may be, for example, an input device such as a keyboard, which will be described later, or a communication device. The determination device 1 may be connectable to an external device via the communication device, for example, and the various information may be input from the external device. Examples of the external device include a database in which the various data are stored, a server, a terminal, and the like, and the terminal is, for example, a PC (personal computer), a tablet, a smartphone, and the like. The communication network is, for example, the same as that described above.

The correlation information generation unit 11, based on the worker information of workers belonging to the same skill level, for each of the skill levels, the skill level, the correct answer rate for the plurality of work-related problems, and the work-related problem to be correctly answered. Correlation information (first correlation information) is generated. The first correlation information may be, for example, a first correlation estimation model indicating a correlation between the practical skill level and the correct answer rate and the correct work-related problem. In this case, the correlation information generation unit 11 uses, for example, the actual skill level and the correct/wrong result of the worker as a learning data set by machine learning, the actual skill level, the correct answer rate, and the correct work-related problem. A first correlation estimation model showing a correlation with is generated.

The determination unit 12 determines, based on the first correlation information, a correct answer rate necessary for clearing a target skill level and a correct answer of the plurality of questions. When the first correlation estimation model is used as the first correlation information, the determination unit 12 determines, for example, a correct answer rate necessary for clearing a target skill level based on the first correlation estimation model, and A question to be correctly answered among a plurality of questions is determined. When the determination device 1 has the output unit 14, the determination result of the determination unit 12 may be output.

Further, in the determination device 1, for example, the output unit 14 may output, for example, the question to be correctly answered included in the determination result, and the learner's answer to the question may be input from the input unit 13. .. In this case, the determination device 1 further includes, for example, a correctness/incorrectness determination unit, in which the correctness/incorrectness determination unit compares the answer of the learner with the correct answer associated with the question to determine whether the answer is correct or incorrect. It may be determined, and the correctness determination result may be output from the output unit 14. In this way, the problem necessary for the learned person to clear the intended skill level is output to the learned person by the determination device 1 by, for example, sequentially outputting the problem. You can also study efficiently.

Next, FIG. 2 illustrates a block diagram of a hardware configuration of the determination device 1. The determination device 1 includes, for example, a CPU (central processing unit) 111, a memory 112, a bus 103, an input device 104, a display 105, a communication device 106, a storage device 107, and the like. The respective units of the determination device 1 are mutually connected via the bus 103 by respective interfaces (I/F).

The CPU 111 is a processor that controls the entire determination device 1, and is not limited to the CPU and may be another processor. In the determination device 1, the CPU 111 executes, for example, the program of the present invention or other programs, and also reads or writes various information. Specifically, in the determination device 1, for example, the CPU 111 functions as the correlation information generation unit 11, the determination unit 12, and the like.

The determination device 1 can be connected to a communication line network by, for example, the communication device 106 connected to the bus 103, and can also be connected to an external device via the communication line network. The external device is not particularly limited and is as described above, for example. The connection method between the determination device 1 and the external device is not particularly limited, and may be, for example, a wired connection or a wireless connection. The wired connection may be, for example, a cord connection or a cable connection for using a communication network. The wireless connection may be, for example, a connection using a communication network or a connection using wireless communication. The communication line network is not particularly limited, and, for example, a known communication line network can be used and is the same as described above. The connection format between the determination device 1 and the external device may be, for example, USB.

The memory 112 includes, for example, a main memory, and the main memory is also referred to as a main storage device. When the CPU 111 performs processing, for example, the memory 112 reads various operation programs 108 such as the program of the present invention stored in an auxiliary storage device described later, and the CPU 111 receives data from the memory 112. , The program 108 is executed. The main memory is, for example, a RAM (random access memory). The memory 112 further includes, for example, a ROM (read-only memory).

The storage device 107 is also referred to as a so-called auxiliary storage device with respect to the main memory (main storage device), for example. The storage device 107 includes, for example, a storage medium and a drive that reads and writes the storage medium. The storage medium is not particularly limited, and may be, for example, an internal type or an external type, HD (hard disk), FD (floppy (registered trademark) disk), CD-ROM, CD-R, CD-RW, MO, Examples thereof include DVD, flash memory, and memory card, and the drive is not particularly limited. The storage device 107 can also be exemplified by a hard disk drive (HDD) in which a storage medium and a drive are integrated. The operation program 108 is stored in the storage device 107 as described above, for example, and the memory 112 reads the operation program 108 from the storage device 107 when the CPU 111 is executed as described above. Further, the storage device 107 stores, for example, the work-related question data set 109 and the worker information 110 described above.

The determination device 1 may further include, for example, the input device 104 and the display 105. The input device 104 is, for example, a scanner, a touch panel, a keyboard, or the like. Examples of the display 105 include an LED display and a liquid crystal display. The input device 104 is, for example, the input unit 13, and the display 105 is, for example, the output unit 14.

Next, the determination method of this embodiment will be described. The determination method of the present embodiment can be implemented using the determination device 1 shown in FIGS. 1 and 2, for example. The determination method of this embodiment is not limited to the use of the determination device 1 shown in these drawings.

The determination method of this embodiment includes a correlation information generation step and a determination step, and uses a data set. The data set includes a problem data set and a worker information data set. The problem data set is the work-related problem data set described above, and includes the plurality of work-related problems. Further, the worker information data set includes the worker information. As the data set, for example, the data set stored in the storage unit can be used.

In the correlation information generating step, based on worker information of workers belonging to the same skill level, for each of the skill levels, the skill level, a correct answer rate for the plurality of work related questions, and a work related question to be correctly answered First correlation information is generated. The correlation information generation step can be executed by the correlation information generation unit 11 of the determination device 1, for example. The first correlation information is preferably, for example, the above-described first correlation estimation model.

The determining step determines, based on the first correlation information, a correct answer rate necessary for clearing a target practical skill level and a correct answer of the plurality of questions. The determination step can be executed by the determination unit 12 of the determination device 1, for example. When the first correlation information is the first correlation estimation model, the determining step uses, for example, the first correlation estimation model, and the correct answer rate and the plurality of correct answers necessary to clear the target skill level. Determine which of the questions should be answered correctly.

The determination method of the present embodiment further includes, for example, an output step, and the output step outputs, for example, the determination result in the determination step. The output step can be executed by the output unit 14 of the determination device 1, for example.

If the information determined in this way is used as an achievement condition for clearing the desired practical skill level, for example, in the learning of the learner, what degree of correct answer is achieved in order to reach the desired practical skill level. You can know what to do, what kind of problem can be answered correctly, and so on. In addition, since the problem to be answered correctly is a good problem for clearing the desired practical skill level, for example, if the learner concentrates on the problem to be answered correctly, only a smaller number of problems will be solved. Then, you can add the necessary force to clear the desired skill level.

An example of the determination method of this embodiment will be described with reference to the flowchart of FIG. The following is an example, and the present invention is not limited to these examples.

In the present embodiment, the practical skill level is set to five levels from level 1 (beginner) to level 5 (expert), and the practical skill level of the learner is level 2, aiming to improve to level 3. Suppose.

First, the target skill level X is set. In this embodiment, the skill level is set to 3 (S01). Next, the worker information of the workers who belong to the skill level 3 is extracted from the worker information storage unit 102 (S02), and the worker information of the skill level 3 is used as a learning data set to determine the skill level 3 by machine learning. , A correlation estimation model showing the correlation between the correct answer rate and the correct work-related problem is generated (S03).

Then, using the correlation estimation model, the correct answer rate necessary for clearing the practical skill level 3 and the correct answer of the plurality of questions are determined (S04). The determination result may be output from the output unit 14, or the determined correct question may be sequentially output (S05). When the learner's answer is input to the output question (S06), the correctness is determined depending on whether the input answer matches the correct answer associated with the output question. (S07). Then, if the answers match (YES), the determination result of the correct answer and the explanation of the correct answer are output (S08), and if the answers do not match (NO), the determination result of the incorrect answer and the correct answer are output. The answer and the explanation of the correct answer are output (S09). If the unanswered question remains, or if the incorrect answer remains, for example, the steps S05 to S10 may be repeated.

[Embodiment 2]
Still another example of the determination device and the determination method of the present invention will be described.

In the determination device of the present embodiment, for example, the worker information storage unit further includes, as the worker information, a skill level before and after work learning using the work-related problem for each worker, and Correct and false results regarding work-related problems are stored in association with each other, and the correlation information generation unit improves the practical skill level based on worker information of a worker whose practical skill level has improved before and after the work learning. , The second correlation information indicating the correlation with the correct answer rate and the work-related problem to be correctly answered is generated, and the determination unit is required to clear the improvement of the target practical skill level based on the second correlation information. The correct answer rate and the question to be answered correctly may be determined.

Further, similarly, the determination method of the present embodiment, for example, the worker information data set, as the worker information, before and after the work learning using the work-related problem for each worker A skill level and a correct/wrong result of the work-related problem are included in a linked data set, and the correlation information generation step is based on worker information of a worker whose skill level is improved before and after the work learning. , Improving the practical skill level, and generating second correlation information indicating a correlation between the correct answer rate and the work-related problem to be correct, and the determining step determines the target practical skill level based on the second correlation information. The correct answer rate necessary to clear the improvement and the question to be answered correctly may be determined.

According to the first embodiment, for example, regardless of the skill level before learning, the correct answer rate for clearing the target skill level and the question to be answered correctly are determined. On the other hand, according to the present embodiment, the second correlation information is further generated by using the information on the skill level before learning to solve the work-related problem and the information on the skill level after learning. .. Therefore, for example, what kind of correct answer rate is required and what kind of problem should be correct in improving the skill level (Ln) before learning to the skill level (Ln+m) after learning Can also be determined. Therefore, as a specific example, for example, a problem suitable for a learner having a low skill level and a problem suitable for a learner having a high skill level can be determined. That is, it is possible to more efficiently determine the achievement condition necessary for improving to the desired practical skill level based on the current practical skill level and use it for the learning of the learner.

Further, for example, as the worker information, by further using the correct/incorrect result before learning and the correct/incorrect result after learning, for example, for a problem suitable for raising from a certain correct answer rate to a certain correct answer rate, You can judge.

[Embodiment 3]
Still another example of the determination device and the determination method of the present invention will be described.

The determination device of the present embodiment further includes, for example, a practical skill level estimation unit, and the practical skill level estimation unit, from the correct/wrong result of the plurality of work-related problems regarding the subject whose practical skill level is unknown, 1 Based on the correlation information, the skill level of the subject is estimated.

Similarly, the determination method of the present embodiment further includes, for example, a skill level estimation step, wherein the skill level estimation step is based on the correct/wrong result of the plurality of work-related problems regarding the subject whose skill level is unknown. , Estimating the practical skill level of the subject based on the first correlation information.

As described above, the present invention generates correlation information between a practical skill level, a correct answer rate, and a work-related problem to be correct. For example, when the practical skill level of the learner is unknown, the work-related problem It is also possible to estimate the practical skill level from the correct/wrong result based on the first correlation condition.

[Embodiment 4]
The program of the present embodiment is a program that can execute the determination method of the present invention on a computer. Alternatively, the program of this embodiment may be recorded in a computer-readable recording medium, for example. The recording medium is not particularly limited, and examples thereof include the storage medium described above.

Although the present invention has been described with reference to the exemplary embodiments, the present invention is not limited to the above exemplary embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention.

<Appendix>
The whole or part of the exemplary embodiments and examples described above can be described as, but not limited to, the following supplementary notes.
(Appendix 1)
Including a storage unit, a correlation information generation unit, and a determination unit,
The storage unit includes a problem storage unit and a worker information storage unit,
The problem storage unit is
Remembers multiple work-related problems for the learner to learn work,
The worker information storage unit,
For each worker, as worker information, a practical skill level evaluated based on the practical skill of the worker and a correctness result of the plurality of work-related problems are stored in association with each other,
The correlation information generation unit,
Based on worker information of workers who belong to the same skill level, first correlation information is generated for each of the skill levels, the skill level, a correct answer rate for the plurality of work related questions, and a work related question to be correctly answered. ,
The determination unit,
Based on the first correlation information, the learner determines a correct answer rate necessary for the learner to clear a desired skill level and a question to be answered correctly among the plurality of questions. A device for judging the level achievement conditions.
(Appendix 2)
The correlation information generation unit,
A first correlation estimation model indicating the correlation between the skill level, the correct answer rate, and the work-related problem to be correct is generated by machine learning using the skill level of the worker and the correct/wrong result as a learning data set. Then
The determination unit,
Using the first correlation estimation model as the first correlation information, the correct answer rate necessary for clearing the target practical skill level and the question to be answered correctly among the plurality of questions are determined. The determination device described.
(Appendix 3)
Furthermore, including a practical skill level estimation unit,
The practical skill level estimation unit,
The determination device according to appendix 1 or 2, which estimates the skill level of the target person based on the first correlation information from correctness results of the plurality of work-related problems regarding the target person whose skill level is unknown. ..
(Appendix 4)
The worker information storage unit,
Further, as the worker information, for each worker, the skill level before and after the work learning using the work-related problem, and the correctness result about the work-related problem are stored in association with each other,
The correlation information generation unit,
Second correlation information indicating a correlation between the improvement in the practical skill level, the correct answer rate, and the work-related question to be correct is generated based on the worker information of the worker whose practical skill level has improved before and after the work learning. ,
The determination unit,
Based on the second correlation information, a correct answer rate necessary for clearing the improvement of the target practical skill level and the correct answer problem are determined.
The determination device according to any one of appendices 1 to 3.
(Appendix 5)
Furthermore, including an output section,
The output unit is
The determination device according to any one of appendices 1 to 4, which outputs a determination result in the determination unit.
(Appendix 6)
Including a correlation information generation step and a judgment step,
Using the dataset,
The data set includes a problem data set and a worker information data set,
The problem data set is
Includes multiple work-related problems for learners to learn work,
The worker information data set is
For each worker, as worker information, a skill level evaluated on the basis of the skill of the worker, and a correct/wrong result of the plurality of work-related problems, a data set associated with each other,
The correlation information generating step,
Based on worker information of workers who belong to the same skill level, first correlation information is generated for each of the skill levels, the skill level, a correct answer rate for the plurality of work related questions, and a work related question to be correctly answered. ,
The determination step is
Based on the first correlation information, a correctness rate necessary for clearing a desired practical skill level and a question to be correctly answered among the plurality of problems are determined, and a practical skill level achievement condition is characterized. Judgment method of.
(Appendix 7)
The correlation information generating step,
A first correlation estimation model indicating the correlation between the skill level, the correct answer rate, and the work-related problem to be correct is generated by machine learning using the skill level of the worker and the correct/wrong result as a learning data set. Then
The determination step is
Using the first correlation estimation model as the first correlation information, the correct answer rate necessary for clearing the target skill level and the question to be answered correctly among the plurality of questions are determined. Judgment method described.
(Appendix 8)
Furthermore, including the skill level estimation step,
In the skill level estimation step,
The determination method according to appendix 6 or 7, wherein the skill level of the target person is estimated based on the first correlation information from correctness results of the plurality of work-related problems regarding the target person whose skill level is unknown. ..
(Appendix 9)
The worker information data set is
Further, as the worker information, for each worker, a skill level before and after work learning using the work-related problem, and a correctness result about the work-related problem, including a data set,
The correlation information generating step,
Second correlation information indicating the correlation between the improvement in the practical skill level, the correct answer rate, and the work-related question to be correct is generated based on the worker information of the worker whose practical skill level has improved before and after the work learning. ,
The determination step is
Based on the second correlation information, a correct answer rate necessary for clearing the improvement in the target practical skill level and the correct answer problem are determined.
The determination method according to any one of appendices 6 to 8.
(Appendix 10)
Furthermore, including an output step,
The output step is
The determination method according to any one of appendices 6 to 9, wherein the determination result in the determination step is output.
(Appendix 11)
A program for causing a computer to execute the method for judging the achievement condition of the practical skill level according to any one of appendices 6 to 10.
(Appendix 12)
A computer-readable recording medium in which the program according to Appendix 11 is recorded.

1 determination device 10 storage unit 11 correlation information generation unit 12 determination unit 13 input unit 14 output unit

Claims (10)

Including a storage unit, a correlation information generation unit, and a determination unit,
The storage unit includes a problem storage unit and a worker information storage unit,
The problem storage unit is
Remembers multiple work-related problems for the learner to learn work,
The worker information storage unit,
For each worker, as worker information, a practical skill level evaluated based on the practical skill of the worker and a correctness result regarding the plurality of work-related problems are stored in association with each other,
The correlation information generation unit,
Based on worker information of workers belonging to the same skill level, first correlation information is generated for each of the skill levels, the skill level, a correct answer rate for the plurality of work related questions, and a work related question to be correctly answered. ,
The determination unit,
Based on the first correlation information, the learner determines a correct answer rate necessary for the learner to clear a desired skill level and a question to be answered correctly among the plurality of questions. A device for judging the level achievement conditions. The correlation information generation unit,
A first correlation estimation model indicating the correlation between the skill level, the correct answer rate, and the work-related problem to be correct is generated by machine learning using the skill level of the worker and the correct/wrong result as a learning data set. Then
The determination unit,
2. The first correlation estimation model is used as the first correlation information, and a correct answer rate necessary for clearing a target skill level and a question to be answered correctly among the plurality of questions are determined. The determination device described in 1. Furthermore, including a practical skill level estimation unit,
The practical skill level estimation unit,
The determination according to claim 1 or 2, wherein the subject's skill level is estimated based on the first correlation information from correctness results of the plurality of work-related problems regarding the subject whose skill level is unknown. apparatus. The worker information storage unit,
Further, as the worker information, for each worker, the skill level before and after the work learning using the work-related problem, and the correctness result about the work-related problem are stored in association with each other,
The correlation information generation unit,
Second correlation information indicating a correlation between the improvement in the practical skill level, the correct answer rate, and the work-related question to be correct is generated based on the worker information of the worker whose practical skill level has improved before and after the work learning. ,
The determination unit,
Based on the second correlation information, a correct answer rate necessary for clearing the improvement in the target practical skill level and the correct answer problem are determined.
The determination device according to any one of claims 1 to 3. Furthermore, including an output section,
The output unit is
The determination device according to claim 1, which outputs a determination result in the determination unit. Including a correlation information generation step and a judgment step,
Using the dataset,
The data set includes a problem data set and a worker information data set,
The problem data set is
Includes multiple work-related problems for learners to learn work,
The worker information data set is
For each worker, as worker information, a skill level evaluated based on the skill of the worker, and a correct/wrong result of the plurality of work-related problems, a data set associated with each other,
The correlation information generating step,
Based on worker information of workers who belong to the same skill level, first correlation information is generated for each of the skill levels, the skill level, a correct answer rate for the plurality of work related questions, and a work related question to be correctly answered. ,
The determination step is
Based on the first correlation information, a correctness rate necessary for clearing a desired practical skill level and a question to be correctly answered among the plurality of problems are determined, and a practical skill level achievement condition is characterized. Judgment method of. The correlation information generating step,
A first correlation estimation model indicating the correlation between the skill level, the correct answer rate, and the work-related problem to be correct is generated by machine learning using the skill level of the worker and the correct/wrong result as a learning data set. Then
The determination step is
7. The first correlation estimation model is used as the first correlation information, and a correct answer rate necessary to clear a target skill level and a question to be correctly answered among the plurality of questions are determined. The determination method described in. Furthermore, including the skill level estimation step,
In the skill level estimation step,
The determination according to claim 6 or 7, wherein the skill level of the target person is estimated based on the first correlation information from correctness results of the plurality of work-related problems regarding the target person whose skill level is unknown. Method. A program for causing a computer to execute the method for determining the achievement condition of the practical skill level according to any one of claims 6 to 8. A computer-readable recording medium in which the program according to claim 9 is recorded.

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