KR20240012720A - A technique for diagnosing question-solving skills of a user - Google Patents

Abstract

A method of diagnosing a user's problem-solving skills using a processor of a device according to some embodiments of the present disclosure is disclosed. The method includes: providing a first problem among a plurality of problems to the user; Receiving solution data for the first problem from the user's user terminal; selecting one of a minimum skill value and a maximum skill value constituting a skill range of a unit related to the first problem based on whether the solution data is correct; determining whether to change the selected value to the difficulty value of the first problem based on whether the difficulty value of the first problem is greater than a selected value among the minimum skill value and the maximum skill value; and when the selected value is changed to the difficulty value of the first problem, changing the skill range of the dependent unit that has a dependency relationship with the unit to be the same as the changed skill range of the unit.

Description

A technique for diagnosing a user's problem-solving skills {A TECHNIQUE FOR DIAGNOSING QUESTION-SOLVING SKILLS OF A USER}

The present disclosure relates to a technique for diagnosing a user's problem-solving skills. Specifically, the minimum skill value and maximum skill value constituting the skill range of the unit related to the problem are based on whether the solution data received after providing the problem to the user is correct. Select which of the skill values to perform an update on, decide whether to change the selected value to the difficulty value based on whether the selected value is greater than the difficulty value of the problem, and determine the skill range of the unit that has a dependency relationship with the unit related to the problem. It also relates to an updating device and method.

Recently, the use of the Internet and electronic devices has become active in various fields, and the educational environment is also rapidly changing. In particular, the development of various educational media has enabled learners to select and use a wider range of learning methods. Among them, education services through the Internet have become a major means of learning due to the advantages of overcoming time and space constraints and enabling low-cost education.

In response to this trend, it is now possible to provide customized education services that were not possible with offline education with limited human and material resources. For example, by analyzing the learner's ability in advance and providing educational content tailored to the learner's ability, we are breaking away from the uniform education method of the past and providing educational content according to the learner's individual ability.

Assuming that a student has 6 discrete levels of proficiency for N units included in a math subject, the number of ways to select one of the 6 levels per unit is It is a branch. In other words, a student's ability for each unit is an absolute value, and diagnosing it means It is a problem of finding the number of one case among the number of possible cases.

If you are conducting a skill diagnosis assuming that you are looking for the skills of each unit without considering the relationship between the members and doctors, when finding a unit's skills from grades 1 to 6, a grade 3 problem is recommended first, and if you get it right, you will be awarded a grade 2 problem. If you have skills, you can update them. Also, if a level 5 problem is recommended and you get it right, it can be inferred that you have level 4 skills. In this way, if one grade can be determined with two questions for one unit, if there are 100 units, 200 questions must be solved to diagnose the student's skills for all units. In this case, a problem arises in that it takes too much time to diagnose the user's skills.

Therefore, there is an urgent need to develop technology that can overcome the above-mentioned problems and quickly diagnose students' problem-solving skills.

Republic of Korea Patent Registration No. 10-2406458 (registered on 2022.06.02)

The present disclosure aims to solve the above-described problems and other problems. The technical task sought to be achieved by some embodiments of the present disclosure aims to quickly diagnose a user's problem-solving skills.

The technical problems to be achieved in the present disclosure are not limited to the technical problems mentioned above, and other technical problems not mentioned can be clearly understood by those skilled in the art of the present disclosure from the description below. There will be.

A method of diagnosing a user's problem-solving skills by a processor of a device according to some embodiments of the present disclosure includes: providing a first problem among a plurality of problems to the user; Receiving solution data for the first problem from the user's user terminal; selecting one of a minimum skill value and a maximum skill value constituting a skill range of a unit related to the first problem based on whether the solution data is correct; determining whether to change the selected value to the difficulty value of the first problem based on whether the difficulty value of the first problem is greater than a selected value among the minimum skill value and the maximum skill value; and when the selected value is changed to the difficulty value of the first problem, changing the skill range of the dependent unit that has a dependency relationship with the unit to be the same as the changed skill range of the unit.

According to some embodiments of the present disclosure, the step of selecting one of the minimum skill value and the maximum skill value constituting the skill range of the unit related to the first problem based on whether the solution data is correct is: the solution data If the answer is correct, selecting the minimum skill value; Alternatively, if the solution data is an incorrect answer, selecting the maximum skill value may be included.

According to some embodiments of the present disclosure, whether to change the selected value to the difficulty value of the first problem based on whether the difficulty value of the first problem is greater than the selected value of the minimum skill value and the maximum skill value. The step of determining is: when the selected value is the maximum skill value, determining to change the maximum skill value to the difficulty value of the first problem when the difficulty value of the first problem is less than the maximum skill value; or when the selected value is the minimum skill value, determining to change the minimum skill value to the difficulty value of the first problem when the difficulty value of the first problem is greater than the minimum skill value; may include.

According to some embodiments of the present disclosure, the step of providing a first problem among the plurality of problems to the user includes: providing a plurality of expected values related to the plurality of problems expected when each of the plurality of problems is provided to the user. calculating step; and providing the user with a problem having the smallest expected value among the plurality of expected values as the first problem. Includes, and each of the plurality of expected values is expressed in the equation Calculated by, and is an expected value related to a second problem, which is one of the plurality of problems, c is a probability value of the user correcting the second problem, and is the expected first skill range associated with the first unit related to the second problem when the user correctly guesses the second problem, and the expected second skill range associated with the first dependent unit that is dependent on the first unit. It is the first average skill length value calculated using may be a second average skill length value calculated using the expected third skill range associated with the first unit and the expected fourth skill range associated with the first dependent unit when the user answers the second problem incorrectly. .

According to some embodiments of the present disclosure, the fifth skill range of the first unit before being updated has a range greater than or equal to the first minimum skill value and less than or equal to the first maximum skill value, and the first skill range has a range that is greater than or equal to the second minimum skill value and less than or equal to the first maximum skill value, where the second minimum skill value is greater than the difficulty value assigned to the second problem. Has the same value as the first minimum skill value, has the same value as the difficulty value assigned to the second problem if the first minimum skill value is less than the difficulty value assigned to the second problem, and has the second skill value The range has a range that is greater than or equal to the second minimum skill value and is less than or equal to the first maximum skill value, and the third skill range is greater than or equal to the first minimum skill value and is less than the second maximum skill value. has a range that is less than or equal to that of the first maximum skill value, and the second maximum skill value has the same value as the first maximum skill value when the first maximum skill value is less than the difficulty value assigned to the second problem, and the first maximum skill value is less than or equal to the difficulty value assigned to the second problem. If the value is greater than the difficulty value assigned to the second problem, the fourth skill range has a value equal to the difficulty value assigned to the second problem, and the fourth skill range is greater than or equal to the first minimum skill value and the second maximum skill range is greater than or equal to the first minimum skill value. It can have a range that is less than or equal to the skill value.

According to some embodiments of the present disclosure, the first average skill length value is, the first skill length value calculated using each of the first skill range and the second skill range, and the first skill length value among the plurality of units. It is a value calculated by calculating the average of at least one skill length value calculated using at least one skill range for the unit and at least one remaining unit excluding the first dependent unit, and the second average skill length value is, It may be a value calculated by calculating the average of a plurality of second skill length values calculated using each of the third skill range and the fourth skill range and the at least one skill length value.

According to some embodiments of the present disclosure, each of the plurality of first skill length values is a value obtained by subtracting the second minimum skill value from the first maximum skill value, and each of the plurality of second skill length values is the It may be a value obtained by subtracting the first minimum skill value from the second maximum skill value.

According to some embodiments of the present disclosure, the step of providing a problem with the smallest expected value among the plurality of expected values to the user as the first problem is: When there are a plurality of problems with the smallest expected value, the smallest expected value is: It may include randomly selecting one problem among problems with an expected value as the first problem and providing it to the user.

According to some embodiments of the present disclosure, the method is: When the user first diagnoses the problem-solving skill, each of the plurality of units is greater than or equal to a preset minimum skill value before calculating the plurality of expected values. It may further include initializing the skill range of each of the plurality of units to have an initial skill range that is less than or equal to the maximum skill value.

According to some embodiments of the present disclosure, the probability value is determined by one method selected based on the number of first units related to the second problem among methods for calculating the probability value, the methods being: a first method selected when there is only one first unit related to the second problem; and a second method different from the first method selected when there are a plurality of first units related to the second problem.

According to some embodiments of the present disclosure, the first method includes calculating a first average skill value for the unit using the first minimum skill value and the first maximum skill value; and calculating the probability value using the difficulty value assigned to the second problem and the first average skill value. , and the probability value is expressed by the equation Calculated by, and is the probability value, and is a preset first parameter value corrected to minimize the difficulty error of the second problem, is a second parameter value whose value changes depending on the problem type to correct the probability of the user guessing the second problem correctly, and is the difficulty value assigned to the second problem, and is the first average skill value, and may be a preset constant value.

According to some embodiments of the present disclosure, the second method: uses the minimum skill value and maximum skill value included in the skill range before the update of the plurality of first units related to the second problem to the plurality of units. calculating a plurality of second average skill values; calculating a plurality of probability values using the difficulty value assigned to the second problem and the plurality of second average skill values; and determining a probability value having the smallest value among the plurality of probability values as the probability value of correcting the second problem. Each of the plurality of probability values may be expressed by Equation Calculated by, and is a preset first parameter value corrected to minimize the difficulty error of the second problem, is a second parameter value whose value changes depending on the problem type to correct the probability of the user guessing the second problem correctly, and is the difficulty value assigned to the second problem, and is the average skill value for one of the plurality of first units and is one of the plurality of second skill values, above is a probability value calculated by substituting into the above equation, and may be a preset constant value.

According to some embodiments of the present disclosure, the problem type includes a first type representing a multiple-choice question and a second type representing a subjective question, and the second parameter value is, when the question is of the first type, It has a value greater than 0, and may be 0 if the problem is the second type.

A computer program stored in a computer-readable storage medium according to some embodiments of the present disclosure, when executed on a processor of a device, performs steps for diagnosing a user's problem-solving skills, the steps comprising: solving a first problem among a plurality of problems; providing to the user; Receiving solution data for the first problem from the user's user terminal; selecting one of a minimum skill value and a maximum skill value constituting a skill range of a unit related to the first problem based on whether the solution data is correct; determining whether to change the selected value to the difficulty value of the first problem based on whether the difficulty value of the first problem is greater than a selected value among the minimum skill value and the maximum skill value; and when the selected value is changed to the difficulty value of the first problem, changing the skill range of the dependent unit that has a dependency relationship with the unit to be the same as the changed skill range of the unit.

An apparatus for providing problems for diagnosing a user's problem-solving skills according to some embodiments of the present disclosure includes: a storage unit storing at least one program command; a processor executing the at least one program instruction; and Ministry of Communications; It includes, wherein the processor provides a first problem among a plurality of problems to the user, receives solution data for the first problem from the user terminal of the user through the communication unit, and determines whether the solution data is correct. Based on this, one of the minimum skill value and the maximum skill value constituting the skill range of the unit related to the first problem is selected, and the difficulty value of the first problem is greater than the selected value among the minimum skill value and the maximum skill value. It may be determined whether to change the selected value to the difficulty value of the first problem based on whether or not it is large.

The technical solutions obtainable from this disclosure are not limited to the solutions mentioned above, and other solutions not mentioned above will be clearly apparent to those skilled in the art from the description below. It will be understandable.

The effect of the method for diagnosing a user's problem-solving skills according to the present disclosure will be described as follows.

According to some embodiments of the present disclosure, a user's problem-solving skills can be quickly and accurately diagnosed.

The effects that can be obtained through the present disclosure are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the description below. will be.

Various embodiments of the present disclosure are described with reference to the drawings, where like reference numerals are used to collectively refer to like elements. In the following examples, for purposes of explanation, numerous specific details are set forth to provide a thorough understanding of one or more embodiments. However, it will be clear that such embodiment(s) may be practiced without these specific details.
1 is a block diagram illustrating an apparatus for diagnosing a user's problem-solving skills according to some embodiments of the present disclosure.
FIG. 2 is a flowchart illustrating an example of a method for updating the skill range of a unit related to a problem provided to a user and a dependent unit that has a dependency relationship with the unit, according to some embodiments of the present disclosure.
FIG. 3 is a flowchart illustrating an example of a method of providing a problem for diagnosing a user's problem-solving skills according to some embodiments of the present disclosure.
FIG. 4 is a diagram illustrating an example of a method for updating the skill range of a unit related to a problem provided to a user according to some embodiments of the present disclosure.
FIG. 5 is a diagram illustrating an example of a dependent unit that has a dependency relationship with a unit related to a problem according to some embodiments of the present disclosure.
FIG. 6 is a flowchart illustrating an example of a method for updating the skill range of a unit related to a problem provided to a user and a unit that has a dependency relationship with the unit, according to some embodiments of the present disclosure.
FIG. 7 is a flowchart illustrating an example of a method for calculating a probability value of correcting a problem related to one or more units according to some embodiments of the present disclosure.
FIG. 8 is a diagram illustrating an example of a mathematical equation used when calculating a probability value of correcting a problem according to some embodiments of the present disclosure.
FIG. 9 is a diagram illustrating an example of a mathematical equation for calculating a difficulty value when the problem is a question asked by a preset institution according to some embodiments of the present disclosure.

Hereinafter, various embodiment(s) of the device and the control method of the device according to the present disclosure will be described in detail with reference to the drawings. However, regardless of the reference numerals, identical or similar components are assigned the same reference numbers and overlapping The explanation will be omitted.

The purpose and effects of the present disclosure, and technical configurations for achieving them, will become clear by referring to the embodiments described in detail below along with the accompanying drawings. In describing one or more embodiments of the present disclosure, if it is determined that a detailed description of related known technology may obscure the gist of at least one embodiment of the present disclosure, the detailed description will be omitted.

The terms in this disclosure are terms defined in consideration of the functions in this disclosure, and may vary depending on the intention or custom of the user or operator. In addition, the attached drawings are only intended to facilitate understanding of one or more embodiments of the present disclosure, and the technical idea of the present disclosure is not limited by the attached drawings, and all changes included in the spirit and technical scope of the present disclosure are not limited. , should be understood to include equivalents or substitutes.

The suffixes “module” and “part” for components used in the following description are given or used interchangeably only considering the ease of preparation of the present disclosure, and do not have distinct meanings or roles in themselves.

Terms containing ordinal numbers, such as first, second, etc., may be used to describe various components, but the components are not limited by the terms. The above terms are used only for the purpose of distinguishing one component from another. Accordingly, the first component mentioned below may also be the second component within the technical spirit of the present disclosure.

Singular expressions include plural expressions unless the context clearly dictates otherwise. That is, unless otherwise specified or clear from context to indicate a singular form, the singular in this disclosure and claims should generally be construed to mean “one or more.”

In the present disclosure, terms such as “comprising,” “includes,” or “have” are intended to indicate the presence of features, numbers, steps, operations, components, parts, or combinations thereof described in the present disclosure. It should be understood that this does not exclude in advance the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

In the present disclosure, the term “or” should be understood not as “or” in the exclusive sense but as “or” in the connotative sense. That is, unless otherwise specified or clear from context, “X utilizes A or B” is intended to mean one of the natural implicit substitutions. That is, either X uses A; X uses B; Or, if X uses both A and B, “X uses A or B” can apply to either of these cases. Additionally, the term “and/or” as used in this disclosure should be understood to refer to and include all possible combinations of one or more of the related listed items.

As used in this disclosure, the terms “information” and “data” may be used interchangeably.

Unless otherwise defined, all terms (including technical and scientific terms) used in this disclosure may be used with meanings that can be commonly understood by those skilled in the art. Additionally, terms defined in commonly used dictionaries are not overly interpreted unless specifically defined.

However, the present disclosure is not limited to the embodiments disclosed below and may be implemented in various different forms. Only some embodiments of the present disclosure are provided to fully inform those skilled in the art of the present disclosure of the scope of the present disclosure, and the present disclosure is only defined by the scope of the claims. Therefore, the definition should be made based on the content throughout this disclosure.

In general, problems for diagnosing a user's skills may be problems related to one unit or problems related to multiple units.

According to some embodiments of the present disclosure, the processor of the device may provide a first problem among a plurality of problems to the user and receive solution data for the first problem from the user's user terminal. The processor may select one of the minimum and maximum skill values constituting the skill range of the unit related to the first problem based on whether the solution data is correct. The processor may determine whether to change the selected value to the difficulty value based on whether the difficulty value of the first problem is greater than the selected value among the minimum skill value and the maximum skill value. Additionally, when the selected value is changed to a difficulty value, the processor may change the skill range of the dependent unit that has a dependency relationship with the unit related to the problem to be the same as the changed skill range of the unit related to the problem.

Hereinafter, a method for diagnosing a user's problem-solving skills will be described with reference to FIGS. 1 to 9.

1 is a block diagram illustrating an apparatus for diagnosing a user's problem-solving skills according to some embodiments of the present disclosure.

Referring to FIG. 1 , the device 100 for diagnosing a user's problem-solving skills may include a processor 110, a storage unit 120, and a communication unit 130. The components shown in FIG. 1 are not essential for implementing the device 100, so the device 100 described in this disclosure may have more or less components than those listed above.

Each component of the device 100 of the present disclosure may be integrated, added, or omitted depending on the specifications of the device 100 that is actually implemented. That is, as needed, two or more components may be combined into one component or one component may be subdivided into two or more components. Additionally, the functions performed by each block are for explaining the embodiments of the present disclosure, and the specific operations or devices do not limit the scope of the present invention.

The device 100 described in this disclosure may include all devices that perform at least one of transmitting and receiving data, content, services, and applications.

The device 100 of the present disclosure is capable of pairing or connecting to other devices, external servers, etc. through a wired/wireless network, and can transmit/receive predetermined data through this. You can. In this case, data transmitted/received through the device 100 may be converted before transmission/reception.

The device 100 of the present disclosure includes, for example, a standing device such as a server, a personal computer (PC), a microprocessor, a mainframe computer, a digital processor, a device controller, a smart phone, All mobile devices (mobile devices or handheld devices) such as tablet PCs, laptops, etc. may be included. However, the present disclosure is not limited to this.

In this disclosure, “server” refers to a device or system that supplies data to or receives data from various types of user terminals, that is, clients. A server, for example, a web server or portal server that provides web pages, web content or web services, or an advertisement that provides advertising data. Advertising server, content server providing content, SNS server providing SNS (Social Network Service), service server provided by the manufacturer, VoD (Video on Demand) or It may include an MVPD (Multichannel Video Programming Distributor) for providing streaming services, a service server for providing paid services, etc.

In the present disclosure, when the name device 100 is used, it refers to a server depending on the context, but may also refer to a fixed device or a mobile device, or may be used to include all of them unless specifically mentioned.

The processor 110 may generally control the overall operation of the device 100 in addition to operations related to application programs. The processor 110 can provide or process appropriate information or functions by processing signals, data, information, etc. input or output through the components of the device 100 or by running an application program stored in the storage unit 120. there is.

The processor 110 may control at least some of the components of the device 100 to run an application program stored in the storage unit 120. Furthermore, the processor 110 may operate in combination with at least two or more of the components included in the device 100 to run an application program.

The processor 110 may consist of one or more cores and may be any of a variety of commercial processors. For example, the processor 110 may include a central processing unit (CPU), a general purpose graphics processing unit (GPUGP), a tensor processing unit (TPU), etc. You can. However, the present disclosure is not limited to this.

The processor 110 of the present disclosure may be configured with a dual processor or other multiprocessor architecture. However, the present disclosure is not limited to this.

The processor 110 can read the computer program stored in the storage unit 120 to diagnose the user's problem-solving skills.

In the present disclosure, the processor 110 may provide the first problem among a plurality of problems stored in the storage unit 120 to the user.

Specifically, the processor 110 may calculate a plurality of expected values related to the plurality of problems expected when each of the plurality of problems is provided to the user. Additionally, the processor 110 may provide the user with the problem with the smallest expected value among the plurality of expected values as the first problem. Here, when there are a plurality of problems with the smallest expected value, the processor 110 may randomly select one problem from among the plurality of problems as the first problem and provide it to the user. A detailed description of this will be provided later with reference to FIG. 3 .

According to some embodiments of the present disclosure, when a user first diagnoses a problem-solving skill, the processor 110 determines that each of the plurality of units has an initial skill level that is greater than or equal to a preset minimum skill value and is less than or equal to a preset maximum skill value. You can reset the skill range of each of multiple units to have a range.

In the present disclosure, each of the plurality of expected values is expressed by the equation Calculated by, is the expected value related to the second problem, which is one of a plurality of problems, and c is the probability value of the user correcting the second problem, is calculated using the expected first skill range related to the first unit related to the second problem when the user answers the second problem correctly and the expected second skill range related to the first dependent unit that is dependent on the first unit. is the first average skill length value, may be a second average skill length value calculated using the expected third skill range related to the first unit and the expected fourth skill range related to the first dependent unit when the user answers the second problem incorrectly.

The fifth skill range of the first unit before being updated in this disclosure may have a range that is greater than or equal to the first minimum skill value and less than or equal to the first maximum skill value.

In the present disclosure, the first skill range has a range that is greater than or equal to the second minimum skill value and is less than or equal to the first maximum skill value, and the second minimum skill value is the difficulty level at which the first minimum skill value is assigned to the first problem. If it is greater than the difficulty value, it may have the same value as the first minimum skill value, and if the first minimum skill value is less than the difficulty value, it may have the same value as the difficulty value.

In the present disclosure, the second skill range may have the same range as the first skill range. That is, the second skill range may be greater than or equal to the second minimum skill value and less than or equal to the first maximum skill value. This is because dependent units of the first unit must have the same skill range as the first unit.

In the present disclosure, the third skill range has a range that is greater than or equal to the first minimum skill value and is less than or equal to the second maximum skill value, and the second maximum skill value is the level of difficulty assigned to the first problem by the first maximum skill value. If it is smaller than the value, it may have the same value as the first maximum skill value, and if the first maximum skill value is greater than the difficulty value, it may have the same value as the difficulty value.

In the present disclosure, the fourth skill range may have the same range as the third skill range. That is, the fourth skill range may be greater than or equal to the first minimum skill value and less than or equal to the second maximum skill value. This is because dependent units of the first unit must have the same skill range as the first unit.

In the present disclosure, the first average skill length value includes a plurality of first skill length values calculated using each of the first skill range and the second skill range and at least the first unit and the first dependent unit among the plurality of units. It may be a value calculated by calculating the average of at least one skill length value calculated using at least one skill range for one remaining unit. And, the second average skill length value is a plurality of second skill length values calculated using the third skill range and the fourth skill range and at least one of the plurality of units excluding the first unit and the first dependent unit. It may be a value calculated by calculating the average of at least one skill length value for the remaining units. Here, each of the plurality of first skill length values is a value obtained by subtracting the second minimum skill value from the first maximum skill value, and each of the plurality of second skill length values is obtained by subtracting the second minimum skill value from the second maximum skill value. It may be a subtracted value.

In the present disclosure, the processor 110 may receive solution data for the first problem provided to the user from the user's user terminal through the communication unit 130. The processor 110 may select one of the minimum skill value and the maximum skill value constituting the skill range of the unit related to the first problem provided to the user based on whether the solution data is correct. The processor 110 may determine whether to change the selected value to a difficulty value based on whether the difficulty value of the first problem is greater than the selected value among the minimum skill value and the maximum skill value. Additionally, when the selected value is changed to a difficulty value, the processor 110 may change the skill range of the dependent unit that is dependent on the unit related to the first problem to be the same as the skill range of the unit related to the first problem.

In the present disclosure, the dependent unit that has a dependency relationship with the unit related to the first problem is a player unit that is learned before the unit related to the first problem or a follower unit that is learned after the unit related to the first problem, depending on whether the user answered the first problem correctly. It can be defined as a unit.

For example, when the user answers the first problem correctly, the dependent unit may be defined as a prerequisite unit learned before the unit related to the problem. Here, the prerequisite unit is a unit learned before the unit related to the first problem in the learning process, and the user must understand the contents of the dependent unit to correctly answer the unit related to the first problem.

As another example, if the user answers the first problem incorrectly, the dependent unit may be defined as a subsequent unit learned after the unit related to the problem. Here, the subsequent unit is a unit learned later than the unit related to the first problem in the learning process, and the user must understand the contents of the unit related to the first problem to answer the problem related to the subsequent unit.

According to some embodiments of the present disclosure, when the skill range for a unit related to the first problem is changed, the processor 110 may define which unit is a dependent unit that has a dependency relationship with the unit related to the first problem. Additionally, if the dependent unit is defined as a preceding unit, the processor 110 may change the skill range of the preceding unit to be the same as the skill range of the unit related to the first problem, and if the dependent unit is defined as a following unit, the skill range of the following unit may be changed. The skill range can be changed to be the same as the skill range of the unit related to the first problem. However, the present disclosure is not limited to this.

In the present disclosure, the problem may be related to one of the subjects of elementary school, middle school, and high school. For example, problems may include elementary math problems, middle school math problems, high school math problems, elementary Korean language problems, middle school Korean language problems, etc. However, the present disclosure is not limited to this.

In the present disclosure, a unit may refer to a learning unit centered around one topic or content. For example, if the problem is an advanced math problem, the unit may consist of a first unit learning addition, subtraction, multiplication, and division of polynomials, a second unit learning how to solve quadratic equations, etc. However, the present disclosure is not limited to this.

In the present disclosure, a problem related to one unit may mean a problem that can be solved only by knowing the contents of one unit among a plurality of units. For example, a problem that can be solved by knowing the contents of Unit 1 may be a problem related to Unit 1, which is one unit. However, it is not limited to this.

In the present disclosure, a problem related to a plurality of units may mean a problem that can be solved only by knowing the contents of each of the plurality of units related to the problem among all units. For example, a problem that can be solved by knowing the contents of the second unit as well as the contents of the first unit may be a problem related to multiple units.

The storage unit 120 may store data supporting various functions of the device 100. The storage unit 120 may store a plurality of application programs (application programs or applications) running on the device 100, data for operation of the device 100, commands, and at least one program command. . At least some of these applications can be downloaded from an external server through wireless communication. Additionally, at least some of these application programs may exist on the device 100 from the time of shipment for the basic functions of the device 100. Meanwhile, the application program may be stored in the storage unit 120, installed on the device 100, and driven by the processor 110 to perform the operation (or function) of the device 100.

The storage unit 120 may store any type of information generated or determined by the processor 110 and any type of information received through the communication unit 130.

The storage unit 120 is a flash memory type, a hard disk type, a solid state disk type, an SDD type (Silicon Disk Drive type), and a multimedia card micro type. type), card-type memory (e.g. SD or XD memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), EEPROM (electrically erasable programmable memory) It may include at least one type of storage medium among read-only memory (PROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, and optical disk. The device 100 may be operated in connection with web storage that performs the storage function of the storage unit 120 on the Internet.

In the present disclosure, the storage unit 120 may store a plurality of problems. Here, a difficulty value may be assigned to each of the plurality of problems. Additionally, which of the plurality of units each of the plurality of problems is related to may be assigned to each of the plurality of problems. However, the present disclosure is not limited to this.

According to some embodiments of the present disclosure, a plurality of problems may be stored in various program languages (eg, HTML, etc.). According to the prior art, the problem was stored in the storage unit 120 in the form of an image, so there was a problem in that the resolution deteriorated depending on the size of the display unit of the user terminal. However, when a plurality of problems are stored in a program language as in the present disclosure, when the size of the display unit of the user terminal changes, the number of texts in one line can be adjusted accordingly, so the problems of the prior art can be solved.

In the present disclosure, the difficulty value of a problem may be a value calculated by analyzing a data set provided from a preset server when the problem is a problem provided by a preset organization (eg, Korea Institute for Educational Evaluation). However, the present disclosure is not limited to this.

The preset server may be a server of a preset institution, or may be a server of an education platform different from the preset institution. However, the present disclosure is not limited to this.

In general, the percentage of correct answers for each question in mock evaluations, academic ability evaluations, and CSAT questions is not provided by the Korea Educational Institutions Evaluation Institute, which is the agency that prepares mock evaluations, academic ability evaluations, and CSAT questions. However, students who have solved mock assessments, academic ability assessments, and college entrance exam questions can enter the correct answers they wrote on the test into the education platform they are using. Therefore, the server of the education platform may store the percentage of correct answers for each question in the mock evaluation, academic ability evaluation, and college entrance exam problem in the storage unit 120. In order to calculate the difficulty value of the problem provided by a preset institution, a plurality of problems are required. Because each correct response rate is required, it is appropriate to view the preset server as an education platform server.

The data set includes multiple problems, points allocated to each of multiple problems, problem type of multiple problems, percentage of correct answers to each of multiple problems, raw scores by grade of multiple users who solved multiple problems, and multiple users who solved multiple problems. Standard scores for each level of users, cumulative ratio for each level of multiple users who solved multiple problems, average score of multiple users who solved multiple problems, and standard score of multiple users who solved multiple problems May contain deviations. However, the present disclosure is not limited to this.

Meanwhile, in the present disclosure, if the problem is a self-produced problem, the difficulty value of the problem may be a value calculated by calculating the average of the difficulty values input from a preset number of difficulty setters. However, the present disclosure is not limited to this.

In the present disclosure, the storage unit 120 may store skill data for each of a plurality of users. Here, the skill data may record the user's skill range for each of a plurality of units. Accordingly, the processor 110 can check the skill range for the entire unit by using the skill data of the user whose skill needs to be confirmed among the skill data of each of the plurality of users stored in the storage unit 120. However, the present disclosure is not limited to this.

In the present disclosure, the storage unit 120 includes a preset first parameter value that corrects to minimize the difficulty error of the problem used when calculating the probability value of the user correcting the problem, and the problem correcting the probability of the user correcting the problem by selecting the problem. It may store a second parameter whose value changes depending on the type and a preset constant value used in a mathematical equation that calculates the probability of correcting the problem. However, the present disclosure is not limited to this.

In the present disclosure, the first parameter value is It can be. This will be described in more detail later with reference to FIG. 8.

In the present disclosure, the problem type may include a first type representing a multiple-choice question and a second type representing a subjective question. However, the present disclosure is not limited to this.

In the present disclosure, the second parameter value that changes depending on the problem type may have a value greater than 0 (e.g., 0.2) when the problem type is the first type, and may be 0 when the problem type is the second type. . That is, the second parameter value may have a larger value when the problem is of the second type than when the problem is of the first type. However, the present disclosure is not limited to this.

In the present disclosure, the storage unit 120 may store a precedence relationship between a plurality of units.

The communication unit 130 may include one or more modules that enable wired/wireless communication between the device 100 and a wired/wireless communication system, between the device 100 and another device, or between the device 100 and an external server. there is. Additionally, the communication unit 130 may include one or more modules that connect the device 100 to one or more networks.

The communication unit 130 refers to a module for wired/wireless Internet access and may be built into or external to the device 100. The communication unit 130 may be configured to transmit and receive wired/wireless signals.

The communication unit 130 uses technical standards or communication methods for mobile communication (e.g., Global System for Mobile communication (GSM), Code Division Multi Access (CDMA), Code Division Multi Access 2000 (CDMA2000), and EV-DO ( Enhanced Voice-Data Optimized or Enhanced Voice-Data Only), Wideband CDMA (WCDMA), High Speed Downlink Packet Access (HSDPA), High Speed Uplink Packet Access (HSUPA), Long Term Evolution (LTE), Long Term (LTE-A) It is possible to transmit and receive wireless signals with at least one of a base station, an external terminal, and a server on a mobile communication network built according to (Evolution-Advanced), etc.).

Wireless Internet technologies include, for example, WLAN (Wireless LAN), Wi-Fi (Wireless-Fidelity), Wi-Fi (Wireless Fidelity) Direct, DLNA (Digital Living Network Alliance), WiBro (Wireless Broadband), and WiMAX (Worldwide). There may be Interoperability for Microwave Access), High Speed Downlink Packet Access (HSDPA), High Speed Uplink Packet Access (HSUPA), Long Term Evolution (LTE), and Long Term Evolution-Advanced (LTE-A). However, the communication unit 130 can transmit and receive data according to at least one wireless Internet technology, including Internet technologies not listed above.

In addition, the communication unit 130 may be configured to transmit and receive signals through short range communication. The communication unit 130 includes Bluetooth™, Radio Frequency Identification (RFID), Infrared Data Association (IrDA), Ultra Wideband (UWB), ZigBee, Near Field Communication (NFC), and Wireless-Fidelity (Wi-Fi). ), Wi-Fi Direct, and Wireless USB (Wireless Universal Serial Bus) technologies can be used to perform short-distance communication. The communication unit 130 may support wireless communication through wireless area networks. Local area wireless networks may be wireless personal area networks.

The device 100 according to some embodiments of the present disclosure may be connected to a test device and a wired/wireless network through the communication unit 130. Here, “wired/wireless network” collectively refers to a communication network that supports various communication standards or protocols for pairing or/and data transmission/reception between the device 100 and the test device. These wired/wireless networks include all communication networks that are currently or will be supported in the future according to the standard, and can support one or more communication protocols for them.

In the present disclosure, the device 100 may be connected to a user terminal for communication through the communication unit 130. Here, the user terminal may refer to a student terminal that performs learning or diagnoses problem-solving skills by solving a plurality of problems stored in the storage unit 120 of the device 100, and the user terminal may be a mobile phone or smart phone (smart phone). It may be a mobile device such as a phone, tablet PC, ultrabook, etc. However, the present disclosure is not limited to this.

Meanwhile, according to some embodiments of the present disclosure, the processor 110 controls the communication unit 130 to provide a first problem among a plurality of problems to the user and to receive solution data for the first problem from the user's user terminal. You can. The processor 110 may select one of the minimum skill value and the maximum skill value constituting the skill range of the unit related to the first problem based on whether the solution data is correct, and whether the difficulty value of the first problem is greater than the selected value. Based on this, it can be decided whether to change the selected value (minimum skill value or maximum skill value). Additionally, when the selected value is changed to a difficulty value, the processor 110 may change the skill range of the dependent unit that has a dependency relationship with the unit related to the problem to be the same as the changed skill range of the unit related to the problem. This is explained in more detail with reference to FIGS. 2 to 6.

FIG. 2 is a flowchart illustrating an example of a method for updating the skill range of a unit related to a problem provided to a user and a dependent unit that has a dependency relationship with the unit, according to some embodiments of the present disclosure. FIG. 3 is a flowchart illustrating an example of a method of providing a problem for diagnosing a user's problem-solving skills according to some embodiments of the present disclosure. FIG. 4 is a diagram illustrating an example of a method for updating the skill range of a unit related to a problem provided to a user according to some embodiments of the present disclosure. FIG. 5 is a diagram illustrating an example of a dependent unit that has a dependency relationship with a unit related to a problem according to some embodiments of the present disclosure. FIG. 6 is a flowchart illustrating an example of a method for updating the skill range of a unit related to a problem provided to a user and a unit that has a dependency relationship with the unit, according to some embodiments of the present disclosure. In relation to FIGS. 2 to 6 , content that overlaps with what was described above with reference to FIG. 1 will not be described again, but will be described below focusing on the differences.

Referring to FIG. 2, the processor 110 may provide the first problem among a plurality of problems to the user (S1). Here, the first problem is a problem for diagnosing the user's problem-solving skills and may be one of a plurality of problems stored in the storage unit 120. The method of providing the first problem among a plurality of problems to the user will be described in more detail with reference to FIG. 3.

Referring to FIG. 3, the processor 110 may calculate a plurality of expected values related to the plurality of problems expected when each of the plurality of problems is provided to the user (S10).

In the present disclosure, each of the plurality of expected values can be calculated by Equation 1 below.

In equation 1 may be an expected value related to the second problem, which is one of the plurality of problems.

In the present disclosure, the processor 110 may calculate expected values for all of a plurality of problems sequentially or in parallel. Here, the second problem may be a problem of calculating a current expected value among a plurality of problems stored in the storage unit 120.

In Equation 1, c may be the probability that the user will answer the second problem correctly. A method of calculating the probability value of the user correcting the second problem may be determined based on the number of first units related to the second problem. The probability value of the user correcting the second problem provided to the user will be described in detail later with reference to FIGS. 7 to 9.

In equation 1 is the first average skill calculated using the expected first skill range related to the first unit related to the second problem when the second problem is answered correctly and the expected second skill range of the dependent unit that has a dependency relationship with the first unit. It can be a length value, If the second problem is incorrect, the second problem is calculated using the expected updated third skill range related to the first unit related to the second problem and the expected fourth skill range of the dependent unit that has a dependency relationship with the first unit. It may be the average skill length value.

In the present disclosure, the first skill range and the third skill range are ranges representing the user's skill for the first unit related to the second problem, and may mean a range that is greater than or equal to the minimum skill value and less than or equal to the maximum skill value. there is. However, it is not limited to this.

In the present disclosure, the second proficiency range and the fourth proficiency range are ranges representing the proficiency for the first dependent unit that has a dependency relationship with the first unit, and the second proficiency range may have the same range as the first proficiency range, The fourth skill range may have the same range as the third skill range.

Meanwhile, the 1st skill range, 2nd skill range, 3rd skill range, and 4th skill range are not ranges that represent the current skill level related to the unit, but are related to the unit expected when the user guesses the problem correctly or incorrectly. It may be a range that indicates skill.

Meanwhile, according to some embodiments of the present disclosure, when a user first diagnoses a problem-solving skill, the processor 110 determines an initial skill range in which the user's skill range for a plurality of units is all the same before calculating a plurality of expected values. It can be initialized to have.

For example, referring to (a) of FIG. 6, the processor 110 determines that each of the plurality of units 310, 320, and 330 is greater than or equal to a preset minimum skill value (e.g., 100) and a preset maximum skill value. The skill range of each of the plurality of units may be initialized to have an initial skill range (410, 420, 430) that is less than or equal to the skill value (for example, 600) (510).

In the present disclosure, the fifth skill range of the first unit related to the second problem selected to calculate the expected value may have a range that is greater than or equal to the first minimum skill value and less than or equal to the first maximum skill value. Here, the fifth skill range may mean the skill range of the first unit at the time of calculating the expected value.

According to some embodiments of the present disclosure, assuming that the user guesses the second problem, any of the difficulty value assigned to the second problem and the first minimum skill value constituting the fifth skill range before the update of the first unit Depending on whether the size of is larger, it can be determined whether the second minimum skill value constituting the first skill range of the first unit (expected skill range assuming that the question is answered correctly) will have a difficulty value. And, the second skill range of the dependent unit (player unit) that has a dependency relationship with the first unit related to the second problem may have the same range as the first skill range.

For example, assuming that the user solves the second problem correctly, the difficulty value assigned to the second problem is in the 5th skill range before the update of the first unit related to the second problem (the skill level of the first unit at the time of calculating the expected value). If it is greater than the first minimum skill value constituting the first skill range (the expected skill range assuming that the problem is answered correctly) of the first unit, the second minimum skill value constituting the difficulty value of the second problem is You can have In this case, the first skill range may be greater than or equal to the difficulty value of the second problem and less than or equal to the first maximum skill value constituting the fifth skill range. And, the second skill range of the dependent member (player member) that has a dependency relationship with the first member may have the same range as the first skill range of the first member related to the second problem.

Referring to (a) of FIG. 6, when the first unit related to the user's second problem is unit 1 (320), the fifth skill range 420 before the update of the first unit related to the second problem is 100. It can range from greater than or equal to 600 to less than or equal to 600. Referring to (b) of FIG. 6, assuming that the user answers the second problem correctly, if the difficulty value is 400, the fifth skill range (420 in (a) of FIG. 6) of unit 1 (320) is configured. Since the minimum skill value of 100 is less than the difficulty value of 400, the minimum skill value of the first skill range (expected skill range (421) of Unit 1 (320) assuming the user gets the problem correct) can be 400. there is. In this case, the first skill range 421 for unit 1 320 may range from 400 to 600. Referring to (d) of FIG. 6, since it is assumed that the user has guessed the second problem, unit 0 (320), which is a player unit, becomes a dependent unit with a dependency relationship, and unit 1 (320) has a dependency relationship. The second skill range 413 of unit 0 (310) may have the same range as the first skill range 423 of unit 1 (320). In this case, the second skill range 413 of unit 0 (310) may range from 400 to 600.

As another example, assuming that the user guesses the second problem correctly, the difficulty value assigned to the second problem is the 5th skill range before the update of the first unit related to the second problem (the level of the first unit at the time of calculating the expected value). If it is less than or equal to the first minimum skill value constituting the first skill range (skill range), the second minimum skill value constituting the first skill range of the first unit may have the first minimum skill value constituting the fifth skill range. . In this case, the first skill range may be greater than or equal to the first minimum skill value and less than or equal to the first maximum skill value. And, the second skill range of the dependent member (player member) that has a dependency relationship with the first member may have the same range as the first skill range of the first member related to the second problem.

Referring to (a) of FIG. 6, when the first unit related to the user's second problem is unit 1 (320), the fifth skill range 420 before the update of the first unit related to the second problem is 100. It can range from greater than or equal to 600 to less than or equal to 600. Assuming that the user gets the second problem right, if the difficulty value assigned to the second problem is 50, the minimum skill value constituting the fifth skill range of unit 1 (320), the first unit related to the second problem, is 100. Since this difficulty value is greater than 50, the minimum skill value of the first skill range (the expected skill range of unit 1 (320) assuming the user gets the problem correct) can be 100. In this case, the first skill range 420 for unit 1 320 may range from 100 to 600. And, since it is assumed that the user got the second problem right, unit 0 (320), which is a player unit, becomes a dependent unit with a dependency relationship, and the second unit for unit 0 (310), which has a dependency relationship with unit 1 (320), is 2 The skill range (410) can also range from 100 to 600.

According to some embodiments of the present disclosure, assuming that the user gets the second problem wrong, one of the difficulty value assigned to the second problem and the first maximum skill value constituting the fifth skill range before the update of the first unit Depending on whether the size of is larger, it can be determined whether the second maximum skill value constituting the third skill range of the first unit (expected skill range assuming that the problem is incorrect) will have a difficulty value. Additionally, the fourth skill range of the dependent unit (subsequent unit) that has a dependency relationship with the first unit related to the second problem may have the same range as the third skill range.

For example, assuming that the user gets the second problem wrong, the difficulty value assigned to the second problem is in the 5th skill range before the update of the first unit related to the second problem (the skill level of the first unit at the time of calculating the expected value). If it is less than or equal to the first maximum skill value constituting the first unit's third skill range (the expected skill range assuming you get the problem wrong), the second maximum skill value constituting the third skill range of the first unit (the expected skill range assuming you get the problem wrong) is the second maximum skill value of the second problem. It can have a difficulty value. In this case, the third skill range may be greater than or equal to the first minimum skill value and less than or equal to the difficulty value of the second problem. And, the fourth skill range of the dependent unit (subsequent unit) that has a dependency relationship with the first unit may have the same range as the third skill range of the first unit related to the second problem.

Referring to (a) of FIG. 6, when the first unit related to the user's second problem is unit 1 (320), the fifth skill range 420 before the update of the first unit related to the second problem is 100. It can range from greater than or equal to 600 to less than or equal to 600. Referring to (c) of FIG. 6, assuming that the user gets the second problem wrong and the difficulty value is 400, the fifth skill range (420 in (a) of FIG. 6) of unit 1 (320) is configured. Since the maximum skill value of 600 is greater than the difficulty value of 400, the maximum skill value of the third skill range (expected skill range (422) of unit 1 (320) assuming the user gets the problem wrong) can be 400. . In this case, the third skill range 422 for unit 1 320 may range from 100 to 400. Referring to (e) of FIG. 6, since the user assumed that the problem was incorrect, unit 2 (330), which is a subsequent unit, becomes a dependent unit with a dependency relationship, and unit 2 (330) has a dependency relationship with unit 1 (320). )'s fourth skill range 434 may have the same range as the third skill range 424 of unit 1 (320). In this case, the fourth skill range 434 of unit 2 330 may range from 100 to 400.

As another example, assuming that the user gets the second problem wrong, the difficulty value assigned to the second problem is the 5th skill range before the update of the first unit related to the second problem (the level of the first unit at the time of calculating the expected value). If it is greater than the first maximum skill value constituting the third skill range of the first unit, the second maximum skill value constituting the third skill range of the first unit may have the first maximum skill value constituting the fifth skill range. In this case, the third skill range may be greater than or equal to the first minimum skill value and less than or equal to the first maximum skill value. And, the fourth skill range of the dependent unit (subsequent unit) that has a dependency relationship with the first unit may have the same range as the third skill range of the first unit related to the second problem.

Referring to (a) of FIG. 6, when the first unit related to the user's second problem is unit 1 (320), the fifth skill range 420 before the update of the first unit related to the second problem is 100. It can range from greater than or equal to 600 to less than or equal to 600. Assuming that the user gets the second problem wrong, if the difficulty value assigned to the second problem is 700, 600 is the maximum skill value that constitutes the fifth skill range of Unit 1 (320), the first unit related to the second problem. Since this difficulty value is less than 700, the maximum skill value of the third skill range (the expected skill range of Unit 1 (320) assuming the user gets the problem wrong) can be 600. In this case, the third skill range 421 for unit 1 320 may range from 100 to 600. And, since it was assumed that the user got the problem wrong, Unit 2 (330), which is a subsequent unit, becomes a dependent unit with a dependency relationship, and the second skill range for Unit 2 (330), which has a dependency relationship with Unit 1 (320), is ( 430) may also range from 100 to 600.

In the present disclosure, the average skill length value may be defined as the average of the skill length values of all units. Additionally, the skill length value may be defined as the value obtained by subtracting the minimum skill value from the maximum skill value constituting the skill range of the unit.

For example, as shown in (a) of Figure 6, when the skill ranges (410, 420, 430) of each of the plurality of units (310, 320, 330) have a range of 100 to 600, the plurality of units (310, 320, 330), the skill length value of each may be 500, and the average value of the skill length values of each of the plurality of units (310, 320, 330) may also be 500.

In equation 1 The method for calculating is explained as follows. here, is the first average skill calculated using the expected first skill range related to the first unit related to the second problem when the second problem is answered correctly and the expected second skill range of the dependent unit that has a dependency relationship with the first unit. It can be a length value. Hereinafter, for convenience of explanation, it is assumed that the difficulty value of the second problem is 400.

Referring to (d) of FIG. 6, when the first unit related to the second problem is unit 1 (320), when the first problem is answered correctly, the expected first skill range 423 related to unit 1 (320) and The first average skill length value can be calculated using the expected second skill range 413 of unit 0 (310), which is a dependent unit that has a dependency relationship with unit 1 (320). Specifically, the skill length value calculated based on the second skill range (413) of unit 0 (310), which is a dependent unit, and the first skill range (423) of unit 1 (320) related to the second problem. It can be seen that the calculated skill length value is 200, and the skill length value calculated based on the skill range 433 of unit 2 330, which is at least one remaining unit among the plurality of units, is 500. In this case, it can be seen that the first average skill length value, which is the average of the skill length values of all units, is 300. In this disclosure It can be confirmed that is 300.

In equation 1 The method for calculating is explained as follows. here, If the second problem is incorrect, the second problem is calculated using the expected updated third skill range related to the first unit related to the second problem and the expected fourth skill range of the dependent unit that has a dependency relationship with the first unit. It may be the average skill length value.

Referring to (e) of FIG. 6, when the first unit related to the second problem is unit 1 (320), if the first problem is incorrect, the expected third skill range 424 related to unit 1 (320) and the unit The second average skill length value can be calculated using the expected fourth skill range 434 of unit 2 (330), which is a dependent unit that has a dependency relationship with unit 1 (320). Specifically, the skill length value calculated based on the fourth skill range (434) of unit 2 (330), which is a dependent unit, and the third skill range (424) of unit 1 (320) related to the second problem. It can be seen that the calculated skill length value is 300, and the skill length value calculated based on the skill range 414 of unit 0 (310), which is at least one remaining unit among the plurality of units, is 500. In this case, it can be confirmed that the second average skill length value, which is the average of the skill length values of all units, is 366 (values below the decimal point are rounded off). In this disclosure It can be confirmed that is 366.

As a result, in Equation 1, the first average skill length value and the second average skill length value are the expected updated skill range of the entire plurality of units, assuming that the second problem is provided to the user. It can be calculated by calculating the average of a plurality of skill length values calculated using . That is, the processor 110 can assume provision of the second problem, estimate the updated skill range, calculate a plurality of skill length values using the skill range of each unit, and calculate the average of the plurality of skill length values. By obtaining this, the first average skill length value and the second average length value of Equation 1 can be calculated.

As a result, the processor 110 can use Equation 1 described above to calculate the expected value associated with each of the plurality of problems expected when each of the plurality of problems is provided to the user.

Referring again to FIG. 3, when the processor 110 calculates the expected value associated with each of the plurality of problems in step S10, the problem with the smallest expected value among the plurality of expected values may be provided to the user ( S20). Here, when there are multiple problems with the lowest expected value, the processor 110 may randomly select one problem from among the plurality of problems and provide it to the user.

Referring again to FIG. 2, the processor 110 may receive solution data for the first problem from the user's user terminal (S2). Here, the user may refer to a user who diagnoses problem-solving skills (for example, a high school student, a middle school student, an elementary school student, etc.) and a user of a user terminal that is connected to the communication unit 130 of the device 100. However, the present disclosure is not limited to this.

When the processor 110 receives the solution data in step S2, the processor 110 may select one of the minimum skill value and the maximum skill value constituting the skill range of the unit related to the first problem based on whether the solution data is correct. (S3). In addition, the processor 110 may determine whether to change the selected value to the difficulty value based on whether the difficulty value of the first problem is greater than the selected value among the minimum skill value and the maximum skill value (S4). This will be looked at in more detail with reference to Figure 4.

Referring to FIG. 4, when the processor 110 receives solving data, it can analyze the solving data to recognize whether the answer is correct (S31).

Specifically, correct answer data may be stored in the storage unit 120, and the processor 110 may use the correct answer data and solution data stored in the storage unit 120 to determine whether the solution data is the correct answer.

For example, the correct answer data may include a preset number if the question is a multiple choice question. The processor 110 may determine that the correct answer is when the numbers included in the solution data and the numbers included in the correct answer data are the same.

As another example, if the problem is a subjective question, the correct answer can be entered in various forms, so various types of text data may be stored as answer data. In this case, the processor 110 may compare the solution data and text data and recognize the correct answer as the correct answer if text data that is the same or similar to the solution data exists in the correct answer data. Here, whether the solution data and the text data are similar can be recognized using various algorithms that calculate the similarity of the text, such as the Jaccard similarity algorithm, the Euclidean similarity algorithm, the cosine similarity algorithm, and the Manhattan similarity algorithm. However, the present disclosure is not limited to this.

If the processor 110 recognizes that the solution data is the correct answer in step S31, the processor 110 may select a minimum skill value constituting the skill range for the unit related to the first problem (S32). The processor 110 may check whether the difficulty value of the first problem is greater than the minimum skill value selected in step S32 (S41). Additionally, the processor 110 may determine whether to change the minimum skill value to the difficulty value based on whether the difficulty value of the first problem is greater than the minimum skill value. In the present disclosure, it is explained that the processor 110 checks whether the difficulty value of the first problem is greater than the minimum skill value, but the limitation is not limited to this, and the processor 110 determines whether the difficulty value of the first problem is less than the minimum skill value. Various implementation aspects may exist, such as checking whether or not the difficulty value of the first problem is less than or equal to the minimum skill value.

For example, when the processor 110 recognizes that the difficulty value of the first problem is greater than the minimum skill value constituting the skill range for the unit related to the first problem (S41, Yes), it changes the minimum skill value to the difficulty value. You can decide to do it (S42).

As another example, when the processor 110 recognizes that the difficulty value of the first problem is less than or equal to the minimum skill value constituting the skill range for the unit related to the first problem (S41, No), the minimum skill value is set to the difficulty level. You can decide to keep the value unchanged.

Meanwhile, if the processor 110 recognizes in step S31 that the solution data is not the correct answer, that is, if it recognizes that the solution data is an incorrect answer, it selects the maximum skill value constituting the skill range for the unit related to the first problem. (S33). The processor 110 may check whether the difficulty value of the first problem is greater than the maximum skill value selected in step S33 (S43). Additionally, the processor 110 may determine whether to change the maximum skill value to the difficulty value based on whether the difficulty value of the first problem is greater than the maximum skill value. In the present disclosure, it is explained that the processor 110 checks whether the difficulty value of the first problem is greater than the maximum skill value, but the limit is not limited to this, and the processor 110 determines whether the difficulty value of the first problem is less than the maximum skill value. There may be various implementation embodiments, such as checking whether or not the difficulty value of the first problem is less than or equal to the maximum skill value.

For example, when the processor 110 recognizes that the difficulty value of the first problem is greater than the maximum skill value constituting the skill range for the unit related to the first problem (S43, No), it changes the maximum skill value to the difficulty value. You can decide not to do it and keep it.

As another example, when the processor 110 recognizes that the difficulty value of the first problem is less than or equal to the maximum skill value constituting the skill range for the unit related to the first problem (S43, No), the maximum skill value is set to the difficulty value. You can decide to change it to (S44).

Looking at the above-described examples in more detail with reference to FIG. 6, the examples are as follows.

In (a) of Figure 6, when the unit related to the first problem is unit 1 (320), the processor 110 determines that the skill range of unit 1 (320) is greater than or equal to 100 and less than or equal to 600. You can check it. And, let's assume that the difficulty value of the first problem is 400 and look at it below.

Referring to (b) of FIG. 6, when the processor 110 recognizes that the solution data is the correct answer, it can check whether the difficulty value of 400 of the first problem is greater than 100, the minimum skill value of unit 1 (320). Since the difficulty value of the first problem is greater than the minimum skill value of unit 1 (320), the processor 110 may determine to change the minimum skill value of unit 1 (320) to 400, which is the difficulty value of the first problem.

Meanwhile, although not shown in the drawing, when the processor 110 recognizes that the solution data is the correct answer and confirms that the difficulty value of the first problem is 50, the difficulty value of the first problem is not greater than the minimum skill value of 100, so Unit 1 It may be decided to keep the minimum skill value of (320) unchanged at 50, which is the difficulty value of the first problem.

Referring to (c) of FIG. 6, when the processor 110 recognizes that the solution data is an incorrect answer, it can check whether the difficulty value of 400 of the first problem is greater than 600, the maximum skill value of unit 1 (320). Since the difficulty value of the first problem is not greater than the maximum skill value of unit 1 (320), the processor 110 may determine to change the maximum skill value of unit 1 (320) to 400, which is the difficulty value of the first problem.

Meanwhile, although not shown in the drawing, when the processor 110 recognizes that the solution data is an incorrect answer and confirms that the difficulty value of the first problem is 650, the difficulty value of the first problem is greater than the maximum skill value of 600, so Unit 1 ( It may be decided to maintain the maximum skill value of 320) without changing it to 650, which is the difficulty value of the first problem.

Referring again to FIG. 2, when the selected value (minimum skill value or maximum skill value of the unit related to the first problem) is changed to the difficulty value, the processor 110 selects a dependent unit that has a dependency relationship with the unit related to the first problem. The skill range of can be changed to be the same as the changed skill range of the unit related to the first problem (S5).

Specifically, the processor 110 may define a dependent unit with a dependency relationship based on whether the user answered the first question correctly. And, when the processor 110 changes the maximum skill value or minimum skill value of the skill range for the unit related to the first problem to the difficulty value of the first problem, the processor 110 changes the dependent unit that has a dependency relationship with the unit related to the first problem. The maximum skill value or minimum skill value of the skill range for can be changed to the difficulty value of the first problem.

In the present disclosure, the dependent unit that has a dependency relationship with the unit related to the first problem is a player unit that is learned before the unit related to the first problem or a follower unit that is learned after the unit related to the first problem, depending on whether the user answered the first problem correctly. It can be defined as a unit.

For example, when the user answers the first problem correctly, the dependent unit may be defined as a prerequisite unit learned before the unit related to the problem. Here, the prerequisite unit is a unit learned before the unit related to the first problem in the learning process, and the user must understand the contents of the dependent unit to correctly answer the unit related to the first problem.

As another example, if the user answers the first problem incorrectly, the dependent unit may be defined as a subsequent unit learned after the unit related to the problem. Here, the subsequent unit is a unit learned later than the unit related to the first problem in the learning process, and the user must understand the contents of the unit related to the first problem to answer the problem related to the subsequent unit.

In the present disclosure, the storage unit 120 may store a precedence relationship between a plurality of units.

For example, referring to Figure 5, the plurality of units include a first unit 210, a second unit 220, a third unit 230, a fourth unit 240, and a fifth unit 250. can do. Here, the first unit 210 is the first unit learned in the curriculum, and can be learned in that order, the second unit 220, the third unit 230, the fourth unit 240, and the fifth unit 250. .

In the present disclosure, the user must understand the contents of the first unit 210 to solve problems related to the second unit 220, and the user must understand the contents of the first unit 210 to answer the questions related to the third unit 230 and the third unit 230. You can answer related questions correctly. The user must understand the contents of the first unit 210 and the third unit 230 to answer the questions of the fourth unit 240, and the user must understand the contents of the first unit 210, the second unit 220, and the third unit. You must understand the contents of (230) and the fourth unit (240) to answer the questions related to the fifth unit (250). However, even if the user does not understand the contents of the second unit 220 and only understands the contents of the first unit 210, the user can answer the questions related to the third unit 230, and the contents of the third unit 230 Even if you do not understand and only understand the contents of the first unit (210), you can answer the questions related to the second unit (220). In addition, even if the user does not understand the contents of the second unit 220 and only understands the contents of the first unit 210 and the third unit 230, he or she can answer the questions related to the fourth unit 240.

In this case, the player members of the fifth unit 250 may be the first unit 210, the second unit 220, the third unit 230, and the fourth unit 240, and the fourth unit 240 ) may be the first unit 210 and the third unit 230, and the player members of the third unit 230 may be the first unit 210, and the second unit 220 The player member may be the first member 210.

According to some embodiments of the present disclosure, if the first problem solved by the user is a problem related to the fifth unit 250 and the user answers the first problem correctly, the processor 110 determines the user's response to the fifth unit 250. The first unit 210, the second unit 220, the third unit 230, and the fourth unit are dependent units (player units) that have a dependency relationship with the fifth unit 250 in conjunction with changing the skill range. The user's skill range for unit 240 can also be changed. However, if the first problem solved by the user is a problem related to the fifth unit 250 and the user answers the first problem incorrectly, the processor 110 determines the dependent unit (subsequent unit) that has a dependency relationship with the fifth unit 250. ) can be recognized as not existing.

According to some other embodiments of the present disclosure, if the first problem solved by the user is a problem related to the fourth unit 240 and the user answers the first problem correctly, the processor 110 provides information about the fourth unit 240. In conjunction with changing the user's skill range, the user's skill range for the first unit 210 and the third unit 230, which are dependent units (player units) that have a dependency relationship with the fourth unit 240, can also be changed. there is. However, if the first problem solved by the user is a problem related to the fourth unit 240 and the user answers the first problem incorrectly, the processor 110 changes the user's skill range for the fourth unit 240 and By linking, the user's skill range for the fifth unit 250, which is a dependent unit (successor unit) that has a dependency relationship with the fourth unit 240, can also be changed.

According to some other embodiments of the present disclosure, if the first problem solved by the user is a problem related to the third unit 230 and the user answers the first problem correctly, the processor 110 In conjunction with changing the user's skill range, the user's skill range for the first unit 210, which is a dependent unit (player unit) that has a dependency relationship with the third unit 230, can also be changed. However, if the first problem solved by the user is a problem related to the third unit 230 and the user answers the first problem incorrectly, the processor 110 changes the user's skill range for the third unit 230 and By linking, the user's skill range for the fourth unit 240 and the fifth unit 250, which are dependent units (subsequent units) that have a dependency relationship with the third unit 230, can also be changed.

According to some other embodiments of the present disclosure, if the first problem solved by the user is a problem related to the second unit 220 and the user answers the first problem correctly, the processor 110 In conjunction with changing the user's skill range, the user's skill range for the first unit 210, which is a dependent unit that has a dependency relationship with the second unit 220, can also be changed. However, if the first problem solved by the user is a problem related to the second unit 220 and the user answers the first problem incorrectly, the processor 110 changes the user's skill range for the second unit 220 and By linking, the user's skill range for the fifth unit 250, which is a dependent unit (successor unit) that has a dependency relationship with the second unit 220, can also be changed.

According to some other embodiments of the present disclosure, if the first problem solved by the user is a problem related to the first unit 210 and the user answers the first problem correctly, the processor 110 determines the first unit 210 and the first unit 210. It can be recognized that a dependent unit with a dependency relationship does not exist. However, if the first problem solved by the user is a problem related to the first unit 210 and the user answers the first problem incorrectly, the processor 110 changes the user's skill range for the first unit 210 and Users for the second unit 220, third unit 230, fourth unit 240, and fifth unit 250 are dependent units (subsequent units) that are linked and have a dependency relationship with the first unit 210. The skill range can also be changed.

Meanwhile, according to some embodiments of the present disclosure, the processor 110 determines that when the user answers a problem correctly, the minimum skill value constituting the skill range of the dependent unit (player unit) constitutes the changed skill range of the unit related to the first problem. If it is greater than the changed minimum skill value, the minimum skill value constituting the skill range of the dependent unit may not be changed even if the minimum skill value constituting the skill range of the unit related to the first problem is changed. In addition, if the user gets the problem wrong and the maximum skill value constituting the skill range of the dependent unit (following unit) is smaller than the changed maximum skill value constituting the changed skill range of the first problem, the processor 110 Even if the maximum skill value constituting the skill range of the unit related to is changed, the maximum skill value constituting the skill range of the dependent unit may not be changed.

Meanwhile, according to some embodiments of the present disclosure, when providing the user with a problem for diagnosing the user's problem-solving skills, the processor 110 calculates a probability value of the user correcting each of the plurality of problems stored in the storage unit. You can. The method of calculating the probability value will be described in more detail with reference to FIGS. 7 to 9.

FIG. 7 is a flowchart illustrating an example of a method for calculating a probability value of correcting a problem related to one or more units according to some embodiments of the present disclosure. FIG. 8 is a diagram illustrating an example of a mathematical equation used when calculating a probability value of correcting a problem according to some embodiments of the present disclosure. FIG. 9 is a diagram illustrating an example of a mathematical equation for calculating a difficulty value when the problem is a question asked by a preset institution according to some embodiments of the present disclosure. The content described above with respect to FIGS. 1 to 6 in relation to FIGS. 7 to 9 will not be described again, and will be described below focusing on differences.

Referring to FIG. 7, when calculating the expected value for each of a plurality of problems, the processor 110 may check whether there are a plurality of first units related to the second problem for which the current expected value is to be calculated (S111). However, the problem is not limited to this, and the processor 110 may check whether there is only one unit related to the problem.

The processor 110 selects one of the methods for calculating the probability value of correcting the second problem based on the number of first units related to the second problem for which the current expected value is to be calculated, and allows the user to calculate the probability value of correcting the second problem by the selected method. 2 You can determine the probability of getting the question correct. Here, the methods for calculating the probability value are a first method selected when there is only one first unit related to the second problem to calculate the expected value, and a first method selected when there are multiple first units related to the second problem to calculate the expected value. A second method may be included. However, the present disclosure is not limited to this.

Specifically, when the processor 110 determines that there are not multiple first units related to the second problem (S111, No), the processor 110 may calculate the probability value of correcting the problem for calculating the expected value based on the first method. The first method is described in more detail below.

Since the processor 110 has confirmed that there is one unit related to the problem for which the expected value is to be calculated, the average skill value can be calculated based on the user's skill range for one unit stored in the storage unit 120. Here, the user may refer to a user (e.g., high school student, middle school student, elementary school student, etc.) who diagnoses problem-solving skills and may refer to a user of a user terminal connected to communication with the communication unit 130 of the device 100. However, the present disclosure is not limited to this.

In the present disclosure, the user's skill range for a unit may be initially initialized to have a preset initial skill range and pre-stored in the storage unit 120, and may be updated each time the user solves a problem for diagnosing problem-solving skill. You can. Therefore, each time the user calculates the probability value of answering a question correctly, the processor 110 must check the user's skill range for the corresponding unit stored in the storage unit 120. However, the present disclosure is not limited to this.

In the present disclosure, the skill range refers to the skill range for the first unit related to the second problem for calculating the user's expected value, and may be composed of a minimum skill value and a maximum skill value. Specifically, the skill range for the first unit related to the second problem may be greater than or equal to the minimum skill value and less than or equal to the maximum skill value.

In the present disclosure, the processor 110 may calculate the first average skill value by calculating the average of the minimum skill value and maximum skill value constituting the skill range of the first unit related to the second problem for which the expected value is to be calculated (S121 ). For example, if the first minimum skill value is 100 and the first maximum skill value is 600, the first average skill value of the unit may be 350. However, the present disclosure is not limited to this.

Referring again to FIG. 7, the processor 110 calculates a probability value of correcting a problem related to one first unit using the first average skill value calculated in step S121 and the difficulty value assigned to the second problem. You can do it (S122). Here, the second problem may mean a problem of calculating a probability value to calculate an expected value among a plurality of problems stored in the storage unit 120. For convenience of explanation, the second problem will be described below without distinguishing it from the problem. do.

Specifically, the processor 110 substitutes the first average skill value for the unit related to the user's problem and the difficulty value assigned to the problem into a mathematical equation that calculates the probability value of correcting the problem related to one unit to determine one unit. You can calculate the probability of correcting a problem related to . The equation for calculating the probability of correcting a problem related to one unit is explained in more detail with reference to FIG. 8.

In Figure 8 is the probability of getting the question correct, is a preset first parameter value that is corrected to minimize the difficulty error of problems related to one unit, is a second parameter value whose value changes depending on the problem type to correct the probability of the user guessing a problem related to one unit and correcting it, is the difficulty value assigned to a problem related to one unit, is the first average skill value for the unit related to the user's problem, may be a preset constant value.

The mathematical equation in FIG. 8 borrows some of the contents of the elo rating system. However, rather than using the same mathematical formula used in the Elo rating system, the mathematical formula used in the Elo rating system was changed so that the probability value of a user correcting a problem related to one unit can be accurately calculated.

First, in order to minimize difficulty errors that may occur when setting the problem difficulty level, the preset first parameter value is A clause has been added. The role of is a value that defines the probability of knowing how to solve the problem if the user's skill in the unit related to the problem and the problem difficulty are the same value, The reason why is added to the equation in FIG. 8 is to perform problem difficulty assignment more intuitively. When the difficulty of the problem is the same as the user's skill in the unit related to the problem, the probability of knowing how to solve the problem is 75%. Is It can be. go In this case, the probability value of the user correcting the problem related to one unit can be calculated more accurately. For example, when a difficulty setter sets the difficulty of a problem, it is better to label a problem with a 75% chance of getting it right as 100 rather than labeling a question with a 50% chance of getting it right as 100. Because the difficulty error can be greatly reduced, the first parameter value is added to the section.

is a parameter that corrects the probability of a user solving a problem related to one unit without knowing how to solve it, that is, the probability of guessing the problem correctly. The probability of winning between users in the Elo rating system can be considered to be the same as the probability of a user guessing a subjective question correctly in this disclosure. However, unlike when users compete against each other in the Elo rating system, when solving a multiple-choice question, you can be guaranteed at least a 20% chance of getting the question correct even if you have no idea how to solve the question because you have never studied the section on the question. . Therefore, in the mathematical equation that calculates the probability value of a user correcting a problem related to one unit of the present disclosure, the probability of correcting the problem and the probability of knowing how to solve the problem must be considered separately.

Based on the law of total probability, the probability of getting the problem correct can be calculated from the probability of knowing how to solve the problem.

First, the probability of knowing how to solve a problem can be expressed as Equation 2 below.

Meanwhile, if the probability of getting the problem correct is defined as P(A) and the probability of knowing how to solve the problem is defined as P(B), P(A) can be expressed as Equation 3 below.

And, Equation 3 can be expressed as Equation 4 below.

In equation 4: is the probability of getting it right when you know how to solve the problem, which is 1, is the probability of getting it right when you don't know how to solve the problem. It can be. Therefore, Equation 4 can be expressed as Equation 5 below.

And, Equation 5 can be expressed as Equation 6 below.

Also, by substituting Equation 2, which is related to the probability of knowing how to solve the problem, into P(B) in Equation 6, an equation that calculates the probability of solving the problem correctly can be obtained.

And, in Equation 2 exists, but this means a deviation in the difficulty of the problem, and since each of the plurality of problems is given a preset difficulty value, there is no difficulty deviation. is 0. Therefore, in the equation obtained after substituting equation 2 into equation 6, Hang is This can be.

Accordingly, the mathematical equation of FIG. 8 can finally be derived.

Meanwhile, can correct the probability of a user answering a question related to one unit correctly. Specifically, depending on the problem type, the second parameter value The value of can be changed. Here, the problem type may include a first type representing a multiple-choice question and a second type representing a subjective question.

For example, if the problem type is type 2 (subjective problem), the probability of knowing how to solve the problem may be the probability of getting the problem correct. Even in the case of subjective questions, there may be a probability of answering the question, but it has been experimentally confirmed that this can be ignored.

As another example, if the problem type is the first type (multiple choice problem), the probability of getting the problem correct can be calculated by considering the 20% probability of guessing correctly from the probability of knowing how to solve the problem. In the case of multiple-choice questions, the probability is not necessarily 20%, but it was experimentally confirmed that it is safe to assume 20%.

In the present disclosure, in the case of a subjective question, if the probability of knowing the solution method is 0%, the probability of getting the problem correct is 0%, but in the case of a multiple-choice question, the probability of getting the problem correct is 20% even if the probability of knowing the solution method is 0%. It can be. Therefore, the second parameter value whose value changes depending on the problem type to correct the probability of the user correcting the problem related to one unit by taking a picture A term has been added to the equation in Figure 8.

In the equation of Figure 8 may be a difficulty value assigned to a problem related to one unit.

In the present disclosure, the difficulty value assigned to a problem is a fixed value, and when a plurality of problems are stored in the storage unit 120, the difficulty value may be assigned to each of the plurality of problems and stored together with the plurality of problems. However, the present disclosure is not limited to this.

In the present disclosure, when the problem is a self-produced problem, the method of calculating the difficulty value assigned to the problem may be different from the method of calculating the difficulty value assigned to the problem when the problem is a question from a pre-set organization.

For example, if the problem is a question from a pre-set institution, the difficulty value may be a value calculated by analyzing a data set provided from the server of the pre-set institution. Here, the preset server may mean an education platform server, and the data set may include information on the correct answer rate indicating the degree to which a plurality of students answered correctly to the problem.

As another example, if the problem is a self-produced problem, the difficulty value may be a value calculated by calculating the average of the difficulty values input from a preset number (for example, 3) of difficulty setters. Here, since the difficulty value is a value input by a plurality of difficulty setters, there may be differences in the difficulty value for each difficulty setter. Therefore, the difficulty setters must input the difficulty value based on the difficulty setting guide, and the processor 110 can calculate the difficulty value of the corresponding problem by calculating the average of the difficulty values input by the difficulty setters.

In the present disclosure, when the problem is a question asked by a pre-set institution, the method of calculating the difficulty value will be described in more detail with reference to FIG. 9.

In the equation of Figure 9 may mean the percentage of correct answers to the problem. Here, the percentage of correct answers to the problem may be included in a data set received from a preset server.

Meanwhile, it was experimentally proven that the average value of the probability of answering a question correctly is the correct answer rate. Specifically, Assuming that the average probability of students getting the problem correct is 0.45, the processor 110 creates a list with a length of 100 consisting of 45 1s and 55 0s, randomly shuffles the elements in the list, and then randomly shuffles the elements in the list. You can select one element. Additionally, the processor 110 considered the selected element to be incorrect if it was 0, and considered it to be correct if it was 1. About 10,000 people were sampled for one problem, and using the above method, it was possible to check the probability value of 10,000 people getting the problem right and whether 10,000 people answered the problem correctly. The average of the probability values of 10,000 people getting the problem right was 10,000 people. It was experimentally proven that the percentage of correct answers obtained through whether or not the question was answered correctly was almost identical.

Meanwhile, in Figure 9 may mean the preset number of students, may be a preset parameter value corrected to minimize the difficulty error of the problem, may be a parameter value whose value changes depending on the problem type to correct the probability of the user guessing the problem correctly, may be a value that must be calculated by the processor 110 as the difficulty value of the problem, may be the proficiency value for the unit related to the problem for each preset number of students, may be a preset constant value. Here, the proficiency value for the unit related to each problem of a preset number of students may be stored in the storage unit 120.

In this disclosure Is It can be. may be a value greater than 0 (e.g., 0.2) if the question is a multiple-choice question, and may be 0 if the question is a subjective question. can be 25. and, may be 10,000. here, When this is 10,000, it has been experimentally confirmed that the error converges to 0. was set to 10,000.

In the present disclosure, the processor 110 can check the percentage of correct answers to a problem. And, because the skill data of 10,000 students is stored in the storage unit 120, the processor 110 can check the skill value for the unit related to the problem for each of the 10,000 students. Then, the processor 110 substitutes the percentage correct for the problem and the skill value of the unit related to the problem for each of the 10,000 students into the mathematical equation of FIG. 9 to obtain the average value of the percentage correct for the problem and the probability of 10,000 students getting the problem correct. The problem difficulty value at which the error is minimized is The problem difficulty value can be calculated by finding . However, the present disclosure is not limited to this.

Meanwhile, the mathematical equation shown in FIG. 9 can be derived through the following experimental process.

First, in relation to the problem for which you want to calculate the difficulty value, from the normal distribution curve of student skill related to the unit in question, Sample the skills of 10 students. Then, the probability of getting the problem correct is calculated using each student's skill level for the unit. In addition, the difference between the average value of the probability values of getting the problem correct and the correct answer rate of the problem when actually solving the problem with the probability of getting the problem correct was compared. here, It was confirmed that the error decreased as this increased. It was confirmed that if it was over 10,000, the error was close to 0. thus, was set to 10,000, and using this experimental process, a mathematical equation was derived to calculate the difficulty value of the problem.

As a result, the difficulty value may be a value calculated by analyzing a data set provided from a preset server (e.g., an education platform server) if the problem is a question from a preset institution (e.g., Korea Institute of Educational Evaluation). Also, if the problem is a self-produced problem, it may be a value calculated by calculating the average of the difficulty values input from a preset number of difficulty setters.

Meanwhile, in the equation of Figure 9 may be the skill value of each of the N students stored in the storage unit 120, which is different from the first average skill value for the unit related to the user's problem calculated in step S121 of FIG.

In the equation of Figure 9 may be a preset constant value. here, may mean the deviation of users' skills and may generally have a unique value for each student, but in this disclosure, it is defined as a constant value. In other words, assuming that all students have the same skill deviation, the constant value calculated through a preset experiment is used. It can be used as

The preset experiment that calculates is a plurality of After creating , we proceeded with finding the most appropriate value. Then, an experiment was conducted using data sets received from a preset server. Here, the data set includes multiple questions provided by a preset organization (e.g., Korea Institute of Educational Evaluation), points assigned to each multiple questions, problem type of the multiple questions, percent correct for each of the multiple questions, multiple questions Raw score by grade of multiple users who solved multiple problems, standard score by grade of multiple users who solved multiple problems, cumulative ratio by grade of multiple users who solved multiple problems, multiple users who solved multiple problems It may include the average value of the scores of users and the standard deviation of the scores of multiple users who solved multiple problems. However, the present disclosure is not limited to this.

First, in order to conduct a preset experiment, a plurality of must be created. Here, plural can contain 41 constant values. Specifically, plural can be created by increasing the value by 5 between constant values from 0 to 200. For example, 0, 5, 10, ..., 195, 200 are 41 types. It can be.

Next, the difficulty value for each of the plurality of problems is It can be calculated using . In this regard, as it was described in detail with reference to FIG. 9, detailed description will be omitted.

Next, you can check the data set and calculate the skill value of students in each grade using the cumulative ratio for each grade.

Next, the predicted raw score for each grade can be calculated using the difficulty value for each of the plurality of problems and the students' skill value for each grade. The predicted raw score for each grade can be calculated using Equation 7.

Finally, by comparing the predicted raw score for each grade calculated through Equation 7 and the raw score for each grade included in the data set, plural You can explore here. In this case, the error can be checked using the MSE error function.

Through the above-described preset experiments, the most suitable was confirmed to be 25.

As a result, in this disclosure can be 25.

In the present disclosure, when substituting the above-described values into the equation shown in FIG. 9, the probability value of the user correcting the problem related to one unit can be calculated by Equation 8 and Equation 9. Here, Equation 7 is an equation that calculates the probability that the user will answer the question correctly when the problem is a subjective question, and Equation 8 is an equation that calculates the probability that the user will answer the question correctly if the question is a multiple-choice question. .

In the present disclosure, when the problem related to one unit is a subjective problem, the processor 110 calculates the user's first average skill value for the unit in Equation 8: Substitute into and calculate the difficulty value of the problem in Equation 8. By substituting into p , the probability value of the user getting the problem correct is calculated. It can be calculated. And, if the problem related to one unit is a multiple-choice problem, the processor 110 calculates the user's first average skill value for the unit in Equation 9: Substitute into and calculate the difficulty value of the problem in Equation 9. By substituting into p , the probability value of the user getting the problem correct is calculated. It can be calculated.

Referring again to FIG. 7, when the processor 110 determines that there are multiple units related to the problem (S111, Yes), the processor 110 may calculate the probability of correcting the problem based on the second method. Contents that overlap with the above-described content in the second method will not be explained in detail, and the differences will be explained below with respect to the second method.

Since the processor 110 has confirmed that there are a plurality of first units related to the second problem, it is possible to check a plurality of skill ranges for the plurality of first units of the user stored in the storage unit 120. Additionally, the processor 110 may calculate a plurality of second average skill values based on a plurality of skill ranges for the plurality of first units (S123). Here, the plurality of skill ranges may be the skill ranges of the plurality of first units before they are updated.

The processor 110 uses the plurality of second average skill values for the plurality of first units related to the user's second problem and the difficulty value assigned to the second problem to determine a problem in relation to each of the plurality of second average skill values. Multiple probability values for guessing can be calculated (S124).

Specifically, the processor 110 inputs a plurality of second average skill values for a plurality of units related to the user's problem and a difficulty value assigned to the problem into a mathematical equation that calculates a probability value of correcting the problem, thereby generating a plurality of second average skill values for the plurality of units related to the user's problem. In relation to each average skill value, multiple probability values of answering a question correctly can be calculated.

For example, if the problem is related to the first unit and the second unit, the processor 110 may identify a first skill range for the first unit and a second skill range for the second unit. The processor 110 may calculate a third average skill value and a fourth average skill value using the first skill range and the second skill range. The processor 110 may check the difficulty value assigned to the problem stored in the storage unit 120. Then, the processor 110 calculates the first probability value by inputting the third average skill value and the difficulty value into an equation for calculating the probability value of correcting the problem, and the fourth average skill value and difficulty value are used to calculate the probability of correcting the problem. The second probability value can be calculated by entering it into a mathematical equation that calculates the value. Here, the plurality of second average skill values may include a third average skill value and a fourth average skill value.

The equation for calculating the probability of correcting the problem based on the second method will be described in more detail with reference to FIG. 9 again. However, the content that overlaps with the above-mentioned content in relation to the first method will not be explained in detail, but will be explained focusing on the differences.

In Figure 9 may be the average skill value for one unit among a plurality of units related to the problem. in other words, may be one of a plurality of average skill values of the user for a plurality of units.

In the equation of Figure 9 may mean a probability value calculated using the average skill value for one unit among a plurality of units related to the problem.

Specifically, if it is assumed that the units related to the problem include the first unit and the second unit, the processor 110 calculates the third average proficiency value for the first unit and the fourth average proficiency value for the second unit. can do. here, If is the third average skill value may be the first probability value calculated using the third average skill value, If is the fourth average skill value may be a second probability value calculated using the fourth average skill value.

In Figure 9 is a preset first parameter value that is corrected to minimize the difficulty error of the problem, is a second parameter value whose value changes depending on the problem type to correct the probability of the user guessing the problem correctly, is the difficulty value of the problem may be a preset constant value. This has been described in detail in relation to the first method, so detailed description will be omitted.

According to some embodiments of the present disclosure, when the problem for which the probability of answering the question is to be calculated is an subjective problem, and the unit related to the subjective problem includes a first unit and a second unit, the processor 110 may determine the user's first unit. The third average skill value for the unit is calculated as Equation 8 described above in relation to the first method. Substitute into , and calculate the difficulty value of the problem in Equation 8 described above in relation to the first method. By substituting, the first probability value that the user will answer the problem correctly in relation to the first unit can be calculated. Additionally, the processor 110 calculates the fourth average skill value for the user's second unit as Equation 8 described above in relation to the first method. Substitute into and calculate the difficulty value of the problem in Equation 8 described above in relation to the first method. By substituting, a second probability value that the user will answer the problem correctly in relation to the second unit can be calculated.

According to some other embodiments of the present disclosure, when the problem for which the probability of answering the problem is to be calculated is a multiple-choice problem, and the unit related to the multiple-choice problem includes the first unit and the second unit, the processor 110 The third average skill value for unit 1 is calculated from Equation 9 described above in relation to the first method. Substitute into and calculate the difficulty value of the problem in Equation 9 described above in relation to the first method. By substituting, the first probability value that the user will answer the problem correctly in relation to the first unit can be calculated. In addition, the processor 110 calculates the fourth average skill value for the user's second unit as Equation 9 described above in relation to the first method. Substitute into and calculate the difficulty value of the problem in Equation 9 described above in relation to the first method. By substituting, a second probability value that the user will answer the problem correctly in relation to the second unit can be calculated.

Meanwhile, in the present disclosure, when a plurality of probability values (e.g., a first probability value and a second probability value) are calculated, the processor 110 may calculate a plurality of probability values (e.g., a first probability value and a second probability value). One of the probability values) can be determined as the probability value of the user correcting a problem related to a plurality of units (S125 in FIG. 7).

According to some embodiments of the present disclosure, the processor 110 may determine the probability value having the smallest value among the plurality of probability values as the probability value of correcting a problem related to a plurality of units. However, it is not limited to this.

In the present disclosure, when a problem is related to a plurality of concepts, it is intuitive that whether or not an incorrect answer to the problem is determined by the skill of the concept with the least skill among the plurality of concepts is the probability value that has the smallest value among the plurality of probability values. It is most appropriate to determine the probability of correcting problems related to multiple units.

According to at least one of the embodiments of the present invention described above with reference to FIGS. 7 to 9, there is an advantage that the accuracy of the probability value of the user correcting the problem is improved.

Meanwhile, according to some embodiments of the present disclosure described above, the user's problem-solving skills can be quickly diagnosed.

In the present disclosure, the device 100 is not limited to the configuration and method of some of the embodiments described above, but all or part of the embodiments are selectively combined so that various modifications can be made. It may be configured.

Various embodiments described in this disclosure may be implemented, for example, in a recording medium readable by a computer or similar device using software, hardware, or a combination thereof.

According to hardware implementation, some embodiments described herein include application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), and field programmable gate arrays (FPGAs). , may be implemented using at least one of processors, controllers, micro-controllers, microprocessors, and other electrical units for performing functions. In some cases, as described in the present disclosure, Some embodiments may be implemented in a processor.

According to software implementation, some embodiments, such as procedures and functions described in this disclosure, may be implemented as separate software modules. Each of the software modules may perform one or more functions, tasks, and operations described in this disclosure. Software code can be implemented as a software application written in an appropriate programming language. Here, the software code may be stored in the storage unit 120 and executed by the processor 110. That is, at least one program command is stored in the storage unit 120 and at least one program command can be executed by the processor 110.

A method of diagnosing a user's problem-solving skills performed by a processor of a device according to some embodiments of the present disclosure is implemented as code readable by at least one processor on a recording medium readable by at least one processor provided in the device. It is possible. A recording medium readable by at least one processor includes all types of recording devices storing data that can be read by at least one processor. Examples of recording media that can be read by at least one processor include Read Only Memory (ROM), Random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage devices.

Meanwhile, although the present disclosure has been described with reference to the accompanying drawings, these are only examples and are not limited to specific embodiments, and various modifications that can be made by those skilled in the art in the technical field to which the invention pertains are also included in the claims. falls within the scope of rights. Additionally, such modified implementations should not be understood individually from the technical spirit of the present invention.

Claims (15)

In the method of diagnosing a user's problem-solving skills by a processor of a device, the method includes:
providing a first problem among a plurality of problems to the user;
Receiving solution data for the first problem from the user's user terminal;
selecting one of a minimum skill value and a maximum skill value constituting a skill range of a unit related to the first problem based on whether the solution data is correct;
determining whether to change the selected value to the difficulty value of the first problem based on whether the difficulty value of the first problem is greater than a selected value among the minimum skill value and the maximum skill value; and
When the selected value is changed to the difficulty value of the first problem, changing the skill range of a dependent unit that has a dependency relationship with the unit to be the same as the changed skill range of the unit;
Including,
method. According to paragraph 1,
The step of selecting one of the minimum and maximum skill values constituting the skill range of the unit related to the first problem based on whether the solution data is correct is:
If the solution data is correct, selecting the minimum skill value; or
If the solution data is an incorrect answer, selecting the maximum skill value;
Including,
method. According to paragraph 2,
The step of determining whether to change the selected value to the difficulty value of the first problem based on whether the difficulty value of the first problem is greater than the selected value of the minimum skill value and the maximum skill value is:
When the selected value is the maximum skill value, determining to change the maximum skill value to the difficulty value of the first problem when the difficulty value of the first problem is less than the maximum skill value; or
When the selected value is the minimum skill value, determining to change the minimum skill value to the difficulty value of the first problem when the difficulty value of the first problem is greater than the minimum skill value;
Including,
method. According to paragraph 1,
The step of providing a first problem among the plurality of problems to the user is:
calculating a plurality of expected values related to the plurality of problems expected when each of the plurality of problems is provided to a user; and
providing the user with a problem having a smallest expected value among the plurality of expected values as the first problem;
Including,
Each of the plurality of expected values is:
math equation Calculated by,
remind is an expected value related to a second problem, which is one of the plurality of problems, c is a probability value of the user correcting the second problem, and is the expected first skill range associated with the first unit related to the second problem when the user correctly guesses the second problem, and the expected second skill range associated with the first dependent unit that is dependent on the first unit. It is the first average skill length value calculated using is a second average skill length value calculated using the expected third skill range associated with the first unit and the expected fourth skill range associated with the first dependent unit when the user answers the second problem incorrectly,
method. According to clause 4,
The 5th skill range of the 1st unit before being updated is,
Has a range greater than or equal to the first minimum skill value and less than or equal to the first maximum skill value,
The first skill range is,
It has a range that is greater than or equal to the second minimum skill value and is less than or equal to the first maximum skill value, and the second minimum skill value is greater than the difficulty value assigned to the second problem. 1 has the same value as the minimum skill value, and if the first minimum skill value is less than the difficulty value assigned to the second problem, has the same value as the difficulty value assigned to the second problem,
The second skill range is,
Has a range greater than or equal to the second minimum skill value and less than or equal to the first maximum skill value,
The third skill range is,
It has a range that is greater than or equal to the first minimum skill value and is less than or equal to the second maximum skill value, and the second maximum skill value is less than the difficulty value assigned to the second problem. It has the same value as the first maximum skill value, and if the first maximum skill value is greater than the difficulty value assigned to the second problem, it has the same value as the difficulty value assigned to the second problem,
The fourth skill range is,
Having a range greater than or equal to the first minimum skill value and less than or equal to the second maximum skill value,
method. According to clause 5,
The first average skill length value is,
A plurality of first skill length values calculated using each of the first skill range and the second skill range, and at least one for at least one remaining unit excluding the first unit and the first dependent unit among the plurality of units. It is a value calculated by calculating the average of at least one skill length value calculated using the skill range of,
The second average skill length value is,
A value calculated by calculating the average of a plurality of second skill length values calculated using each of the third skill range and the fourth skill range and the at least one skill length value,
method. According to clause 6,
Each of the plurality of first ability length values is,
It is a value obtained by subtracting the second minimum skill value from the first maximum skill value,
Each of the plurality of second ability length values is,
A value obtained by subtracting the first minimum skill value from the second maximum skill value,
method. According to paragraph 4,
The step of providing the problem with the smallest expected value among the plurality of expected values to the user as the first problem is:
When there are a plurality of problems with the smallest expected value, randomly selecting one problem among the problems with the smallest expected value as the first problem and providing it to the user;
Including,
method. According to paragraph 4,
The above method is:
When the user first diagnoses the problem-solving skill, before calculating the plurality of expected values, each of the plurality of units has an initial skill range that is greater than or equal to the preset minimum skill value and less than or equal to the preset maximum skill value. Initializing the skill range of each of a plurality of units;
Containing more,
method. According to clause 5,
The probability value is,
Among the methods for calculating the probability value, it is determined by one method selected based on the number of first units related to the second problem,
The above methods are:
a first method selected when there is only one first unit related to the second problem; and
a second method different from the first method selected when there are a plurality of first units related to the second problem;
Including,
method. According to clause 10,
The first method is,
calculating a first average skill value for the unit using the first minimum skill value and the first maximum skill value; and
calculating the probability value using the difficulty value assigned to the second problem and the first average skill value;
Including,
The probability value is,
math equation Calculated by,
remind is the probability value, and is a preset first parameter value corrected to minimize the difficulty error of the second problem, is a second parameter value whose value changes depending on the problem type to correct the probability of the user guessing the second problem correctly, and is the difficulty value assigned to the second problem, and is the first average skill value, and is a preset constant value,
method. According to clause 10,
The second method is:
calculating a plurality of second average skill values for the plurality of first units using the minimum skill value and maximum skill value included in the skill range before the update of the plurality of first units related to the second problem;
calculating a plurality of probability values using the difficulty value assigned to the second problem and the plurality of second average skill values; and
determining a probability value having the smallest value among the plurality of probability values as the probability value of correcting the second problem;
Including,
Each of the plurality of probability values is,
math equation Calculated by,
remind is a preset first parameter value corrected to minimize the difficulty error of the second problem, is a second parameter value whose value changes depending on the problem type to correct the probability of the user guessing the second problem correctly, and is the difficulty value assigned to the second problem, and is the average skill value for one of the plurality of first units and is one of the plurality of second skill values, above is a probability value calculated by substituting into the above equation, and is a preset constant value,
method. According to claim 11 or 12,
The problem type is,
A first type representing a multiple-choice question and a second type representing a subjective question,
The second parameter value is,
If the problem is of the first type, it has a value greater than 0,
If the problem is of the second type, 0,
method. A computer program stored on a computer-readable storage medium, the computer program, when executed on a processor of a device, performing steps for diagnosing a user's problem-solving skills, the steps comprising:
providing a first problem among a plurality of problems to the user;
Receiving solution data for the first problem from the user's user terminal;
selecting one of a minimum skill value and a maximum skill value constituting a skill range of a unit related to the first problem based on whether the solution data is correct;
determining whether to change the selected value to the difficulty value of the first problem based on whether the difficulty value of the first problem is greater than a selected value among the minimum skill value and the maximum skill value; and
When the selected value is changed to the difficulty value of the first problem, changing the skill range of a dependent unit that has a dependency relationship with the unit to be the same as the changed skill range of the unit;
Including,
A computer program stored on a computer-readable storage medium. In a device that provides problems for diagnosing a user's problem-solving skills, the device:
a storage unit storing at least one program command;
a processor executing the at least one program instruction; and
Ministry of Communications;
Including,
The processor,
Providing a first problem among a plurality of problems to the user,
Receiving solution data for the first problem from the user's user terminal through the communication unit,
Based on whether the solution data is correct, one of the minimum skill value and the maximum skill value constituting the skill range of the unit related to the first problem is selected,
Determining whether to change the selected value to the difficulty value of the first problem based on whether the difficulty value of the first problem is greater than the selected value of the minimum skill value and the maximum skill value,
Device.

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