WO2023159754A1

WO2023159754A1 - Ability level analysis method and apparatus, electronic device and storage medium

Info

Publication number: WO2023159754A1
Application number: PCT/CN2022/090430
Authority: WO
Inventors: 舒畅; 陈又新
Original assignee: 平安科技（深圳）有限公司
Priority date: 2022-02-23
Filing date: 2022-04-29
Publication date: 2023-08-31
Also published as: CN114519534A

Abstract

The present application relates to an intelligent decision technology, and discloses an ability level analysis method, which comprises: when monitoring that a test participant completes one question, obtaining an answer score of a tested question of the test participant, and updating the ability value of the test participant according to the response level and the answer score of each tested question; determining whether the absolute difference value between the ability values before and after the update meets a second preset condition; if the absolute difference value does not meet the second preset condition, selecting, according to the response level of each question and the ability value of the test participant, from a preset question bank a question that meets a first preset condition, and sending the question to the test participant; and if the absolute difference value meets the second preset condition, using the recently updated ability value of the test participant as the final ability level of the test participant. The present application further provides an ability level analysis apparatus, a device and a medium. The present application can improve the accuracy of ability level analysis.

Description

Capability level analysis method, device, electronic equipment and storage medium

This application claims the priority of the Chinese patent application with the application number 202210166713.X submitted to the China Patent Office on February 23, 2022. Incorporated in this application by reference.

technical field

The present application relates to the technical field of intelligent decision-making, and in particular to a capability level analysis method, device, electronic equipment and computer-readable storage medium.

Background technique

It is a very common practice in the field of online or offline education to test the testees based on the preset question bank, and then to evaluate the relevant abilities of the testees according to the answers of the testees, especially in the field of language education. Most common in the field of education. For example, English vocabulary level assessment, English oral ability level assessment. Usually, according to the testee's ability rating level, suitable courses can be selected, or corresponding learning products can be recommended.

Most current ability assessments are based on IRT (Item Response Theory, one-dimensional item response theory), setting test questions reflecting different ability levels, and making an initial prediction of the ability level of the testee based on the collected basic information of the testee. The ability level is obtained to determine the corresponding test items, and the final test item set is obtained for the testee to perform the test.

The inventor realizes that usually after the test item set is determined at one time, the scope and number of test items will not be adjusted according to the actual answering conditions of the testees during the evaluation process. Therefore, this evaluation method may have the situation that the test questions do not match the real ability level of the testee, especially for the testees with strong abilities, their real ability level has not been detected. At the same time, there will be too many test questions, and the repetition of test questions with the same ability level will cause the resentment of the testees and affect the real ability level of the testees. The above-mentioned evaluation method ignores the relationship between the ability reflected by the testee in the process of leveling in real time and the characteristics of the test topic, which may lead to a decline in the accuracy of the ability analysis of the testee.

Contents of the invention

A capability level analysis method provided by this application includes:

Obtain the information data of the subject, and calculate the ability value of the subject according to the information data;

Obtaining the response level of each question in the preset question bank, and according to the reaction level and the ability value, selecting a question from the preset question bank that meets the first preset condition and sending it to the subject;

When it is detected that the subject has completed a question, obtain the testee's answer score of the tested question, and update the testee's ability value according to the response level and answer score of each of the tested questions ;

Calculate the absolute difference between the updated ability value and the ability value before the update;

If the absolute difference does not meet the second preset condition, return to the above-mentioned question according to the reaction level and the ability value, select a question from the preset question bank that meets the first preset condition and send it to the the subject's steps;

If the absolute difference satisfies the second preset condition, the latest updated capability value of the subject is taken as the final capability level of the subject.

The present application also provides a capability level analysis device, which includes:

Ability preliminary evaluation module, used to obtain the information data of the subject, and calculate the ability value of the subject according to the information data;

The question bank topic selection module is used to obtain the response level of each question in the preset question bank, and select a question from the preset question bank that meets the first preset condition according to the reaction level and the ability value and send it to all Describe the subject;

An ability update module, configured to obtain the testee's answer scores of the tested questions when it is detected that the testee completes a question, and update the said testee according to the response level and answer score of each said tested question. The ability value of the testee;

A level determination module, configured to calculate the absolute difference between the updated capability value and the pre-updated capability value, and if the absolute difference does not meet the second preset condition, return to the above-mentioned The ability value of the subject is selected, and a question satisfying the first preset condition is selected from the preset question bank and sent to the subject, if the absolute difference satisfies the second preset condition, Then, the latest updated capability value of the subject is taken as the final capability level of the subject.

The present application also provides an electronic device, the electronic device comprising:

a memory storing at least one computer program; and

A processor, executing the program stored in the memory to implement the capability level analysis method as follows:

The present application also provides a computer-readable storage medium, wherein at least one computer program is stored in the computer-readable storage medium, and the at least one computer program is executed by a processor in an electronic device to implement capability level analysis as described below method:

Description of drawings

FIG. 1 is a schematic flow diagram of a capability level analysis method provided by an embodiment of the present application;

FIG. 2 is a schematic diagram of a detailed implementation process of one of the steps in the capability level analysis method shown in FIG. 1;

FIG. 3 is a functional block diagram of a capability level analysis device provided by an embodiment of the present application;

Fig. 4 is a schematic structural diagram of an electronic device implementing the capability level analysis method provided by an embodiment of the present application.

The realization, functional features and advantages of the present application will be further described in conjunction with the embodiments and with reference to the accompanying drawings.

Detailed ways

It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

An embodiment of the present application provides a capability level analysis method. The subject of execution of the capability level analysis method includes, but is not limited to, at least one of electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the capability level analysis method can be executed by software or hardware installed on the terminal device or server device, and the software can be a block chain platform. The server can be an independent server, or provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery network (ContentDeliveryNetwork , CDN), and cloud servers for basic cloud computing services such as big data and artificial intelligence platforms.

Referring to FIG. 1 , it is a schematic flowchart of a capability level analysis method provided by an embodiment of the present application. In this embodiment, the capability level analysis method includes:

S1. Obtain the information data of the subject, and calculate the ability value of the subject according to the information data;

In this embodiment of the present application, the information data refers to information data that can directly or indirectly reflect the ability level of the subject in the field that needs to be evaluated. For example, in the oral English test, the information data includes but not limited to the testee's education background, major, age, job nature, whether he often browses English news or watches English programs, movies, etc.

In the embodiment of the present application, the ability value of the subject refers to a quantification of the skill level of the subject in the field that needs to be evaluated. For example, in the oral English test, the testee's ability value ranges from 1 to 6.

Specifically, the calculation of the ability value of the subject according to the information data includes: extracting the text features contained in the information data to obtain a text feature set; calculating the relationship between each of the text features in the text feature set and Relative probability values among preset multiple assessment levels; calculating the score of each assessment level according to the relative probability values, and determining the assessment level with the highest score as the ability value of the subject.

In the embodiment of the present application, methods such as Glove (GlobalVectorsforWordRepresentation, global word vector) and EmbeddingLayer may be used to convert the information data into a text vector matrix.

Further, after converting the information data into a text vector matrix, feature extraction can be performed on the text vector matrix to obtain the text features of the information data, the text features include but not limited to text scenes, text topics , Text keywords.

In one embodiment of the present application, a pre-trained LSTM (LongShort-TermMemory, long-short-term memory network) model can be used to perform feature extraction on the text vector matrix of the information data, so as to obtain text features in the text vector matrix.

In the embodiment of the present application, a preset activation function can be used to calculate each of the text features in the text feature set, so as to calculate the relative probability between each of the text features and a plurality of preset evaluation levels, Wherein, the relative probability refers to the probability value that each text feature is a certain evaluation level. When the relative probability between a certain text feature and a certain evaluation level is higher, the text feature is used to express the evaluation level. The higher the probability of rank.

In the embodiment of the present application, the activation function includes, but is not limited to, a softmax activation function, a sigmoid activation function, and a relu activation function.

In the embodiment of the present application, the multiple preset evaluation levels include but are not limited to poor, average, proficient, and proficient.

S2. Obtain the response level of each question in the preset question bank, and select a question from the preset question bank that satisfies the first preset condition according to the reaction level and the ability value, and send it to the subject;

In the embodiment of the present application, the preset question bank refers to a pre-designed set of questions for evaluating the ability level of the testee, which is usually set according to the difficulty level and knowledge composition of each question in the preset question bank. The evaluation level corresponding to each of the questions, that is, the reaction level, for example, the reaction level includes but not limited to level 1, level 2, level 3, etc.

Specifically, according to the reaction level and the ability value, selecting a question from the preset question bank that satisfies the first preset condition and sending it to the subject includes: according to the reaction level and the Calculate the difficulty value of each of the questions based on the ability value; select a question whose difficulty value satisfies the first preset condition as an optional question; randomly select a question from the optional questions and send it to the tested subject By.

Specifically, the calculation of the difficulty value of each of the questions based on the reaction level of each of the questions and the ability value includes:

Use the following preset difficulty evaluation function to calculate the difficulty value corresponding to each said question:

p _ui (θ) represents the difficulty value corresponding to the i-th question in the preset question bank when the testee's ability value is equal to θ, and ui represents the response level corresponding to the i-th question in the preset question bank , b _ui represents the degree of difficulty for the subject to complete the i-th question in the preset question bank to reach the response level corresponding to ui, D represents a constant, a _i represents the i-th question in the preset question bank distinction.

In the embodiment of the present application, the first preset condition may be a pre-designated maximum difficulty interval, for example, the maximum difficulty interval is 50% to 60%, and when the testee's ability value is θ, question 1 is relatively The difficulty value of the subject being tested is 75%, the difficulty value of topic 2 is 52% relative to the subject being tested, and the difficulty value of topic 3 is 40% relative to the subject being tested, then the difficulty value of topic 2 is If the value is within the maximum difficulty range, the corresponding topic 2 can be included in the optional topics.

In the embodiment of the present application, according to the response level of each question and the ability value of the testee, a question that meets the first preset condition is selected from the preset question bank and sent to the testee. The degree of correlation between the test questions and the testee's ability value can be improved, so that each question sent to the testee can more effectively reflect the real ability level of the testee.

S3. When it is detected that the subject has completed a question, obtain the testee's answer score of the tested question, and update the testee's score according to the response level and answer score of each of the tested questions. Ability value;

In the embodiment of the present application, each question in the preset question bank can be a binary question, and the binary question is mostly an objective question. Usually, the answer to the binary question is unique, and the corresponding question score is only 0 or full score in two cases. Each question can also be a multi-point system question. The multi-point system questions are mostly subjective questions. Usually, the answers to the multi-point system questions are not unique. According to the preset answer standard, the corresponding reaction levels of different scores are divided.

In detail, as shown in FIG. 2, in the S2, updating the ability value of the subject according to the response level and answer score of each of the tested questions includes:

S31. According to the preset mapping relationship between the item score and the response level, determine whether the answer score of each of the tested items matches the response level of the tested item;

If the answer score of each of the tested questions matches the response level of the tested question, execute S32, and set the answer result of the tested question to 1;

If the answer score of each of the tested questions does not match the response level of the tested question, execute S33, and set the answer result of the tested question to 0;

S34. Using the preset maximum likelihood function, according to the answer results of each of the tested questions, calculate the predictive ability value of the subject, and use the predictive ability value as the updated value of the subject ability value.

In the embodiment of the present application, the preset mapping relationship between the score of a question and the reaction level refers to a one-to-one correspondence between different scores of each question and the reaction level of the question. For example, if the testee's score for a certain binary question is full, then the testee's ability value conforms to the response level of the binary question, and the testee's score for a certain binary question is zero. points, the ability value of the subject does not meet the response level of the binary question.

In the embodiment of the present application, compared with the two-point system topic, the relationship between the score of the multi-point system topic and the response level of the multi-point system topic is more complicated. Through the relationship between the preset topic score and the response level The mapping relationship can define the response levels corresponding to different score intervals. For example, the score range of a certain multi-point system topic is 0 to 5 points, and the response level corresponding to the multi-point system topic is level 3. If the score of the above multi-point system is less than 3 points, the corresponding response level is 1, and the respondent's score is 3 to 4 points, and the corresponding response level is 2, and the respondent's score is 5 points, and the corresponding response The level is 3.

In the embodiment of the present application, the preset maximum likelihood function is as follows:

Among them, L(θ|V) represents the answering result of the testee when completing the V-th question, θ represents the corresponding predictive ability value of the testee when completing the V-th question, and ui represents the i-th question in the preset question bank. ki represents the testee’s score when answering the i-th question, and record _uik represents the answer result of the i-th question in the preset question bank.

In this embodiment of the application, when the score of the topic matches the reaction level of the topic, record _uik =1, and when the score of the topic does not match the reaction level of the topic, record _uik =0.

In the embodiment of the present application, the maximum likelihood function may be used to solve the corresponding predictive ability value of the subject when completing the V-th track question through the Newton-Raphson iterative method.

In the embodiment of the present application, each time the subject completes a question, the ability value of the subject can be updated in real time according to the reaction level and score of each tested question.

S4. Calculate the absolute difference between the updated ability value and the ability value before the update

In this embodiment of the present application, the second preset condition may be a pre-specified maximum capability difference, for example, 0.2 or 0.3.

It can be understood that if the absolute difference between the updated capability value and the pre-updated capability value is relatively small, it means that the measured person's capability value is relatively stable during the pre- and post-evaluation processes. If the absolute difference between the ability value after the update and the ability value before the update is relatively large, it means that the response levels of the questions sent to the subject before and after the difference are relatively large, and the corresponding ability value of the subject is still relatively large. Unstable, it is necessary to continue to send questions to the subject for further evaluation until the ability value of the subject tends to be stable.

If the absolute difference does not meet the second preset condition, return to S2;

In the embodiment of the present application, if the absolute difference does not satisfy the second preset condition, it means that the ability value of the subject is in an unstable state, and further evaluation of the subject is required.

In another optional embodiment of the present application, in order to prevent the testee from reducing the accuracy rate of the test due to the excessive amount of test questions, the number of test questions can be controlled. In detail, if the absolute difference does not meet the For the second preset condition, return to the above-mentioned step of selecting a question satisfying the first preset condition from the preset question bank and sending it to the subject according to the reaction level and the ability value, and replace it with: Judging whether the number of tested questions is greater than the preset threshold of evaluation questions; if the number of tested questions is not greater than the threshold of the number of evaluation questions, return to S2, if the number of tested questions is greater than the number of evaluation questions threshold value, the latest updated ability value of the person under test is used as the final ability level of the person under test;

In this embodiment of the present application, the preset threshold for the amount of evaluation questions may be set according to actual conditions.

If the absolute difference satisfies the second preset condition, perform S5, and use the latest updated capability value of the subject as the final capability level of the subject.

In the embodiment of the present application, if the absolute difference satisfies the second preset condition, it means that the testee's ability value tends to be stable, and the evaluation can be ended, and the testee's latest updated ability value is used as The testee's final ability level.

This application adjusts the questions sent to the testee according to the ability value of the testee updated in real time during the testee's answering process, and strengthens the relationship between the questions and the testee's ability, so that the questions sent to the testee The tester's questions can more effectively reflect the real ability level of the testee, which improves the accuracy of ability level analysis. At the same time, by controlling the absolute value between the ability values before and after the update, it prevents the questions sent to the testee from appearing before and after Large jumps, thus ensuring the accuracy of ability level analysis.

As shown in FIG. 3 , it is a functional block diagram of a capability level analysis device provided by an embodiment of the present application.

The capability level analysis device 100 described in this application can be installed in electronic equipment. According to the functions realized, the ability level analysis device 100 may include an ability preliminary evaluation module 101, a question bank topic selection module 102, an ability update module 103 and a level determination module 104. The module described in this application can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of the electronic device and can complete fixed functions, and are stored in the memory of the electronic device.

In this embodiment, the functions of each module/unit are as follows:

The ability preliminary evaluation module 101 is used to obtain the information data of the subject, and calculate the ability value of the subject according to the information data;

The question bank topic selection module 102 is used to obtain the response level of each topic in the preset question bank, and select one from the preset question bank that satisfies the first preset requirement according to the reaction level and the ability value of the subject. Conditional questions are sent to the subject;

The ability update module 103 is used to obtain the answer score of the tested subject when it is detected that the subject has completed a question, and according to the response level and answer score of each of the tested questions, updating the ability value of the subject;

The level determination module 104 is configured to calculate the absolute difference between the updated capability value and the pre-updated capability value, and if the absolute difference does not meet the second preset condition, return to the above-mentioned response based on the level and the ability value of the testee, select a question from the preset question bank that meets the first preset condition and send it to the testee, if the absolute difference satisfies the second preset If the condition is set, the latest updated capability value of the subject is taken as the final capability level of the subject.

In detail, each module in the capability level analysis device 100 described in the embodiment of the present application adopts the same technical means as the capability level analysis method described in the above-mentioned Figures 1 to 2 when used, and can generate the same technical effect, which will not be repeated here.

As shown in FIG. 4 , it is a schematic structural diagram of an electronic device implementing a capability level analysis method provided by an embodiment of the present application.

The electronic device 1 may include a processor 10, a memory 11 and a bus, and may also include a computer program stored in the memory 11 and operable on the processor 10, such as a capability level analysis program.

Wherein, the memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card type memory (for example: SD or DX memory, etc.), magnetic memory, magnetic disk, CD etc. The storage 11 may be an internal storage unit of the electronic device 1 in some embodiments, such as a mobile hard disk of the electronic device 1 . The memory 11 can also be an external storage device of the electronic device 1 in other embodiments, such as a plug-in mobile hard disk equipped on the electronic device 1, a smart memory card (SmartMediaCard, SMC), a secure digital (SecureDigital, SD) card, flash memory card (FlashCard), etc. Further, the memory 11 may also include both an internal storage unit of the electronic device 1 and an external storage device. The memory 11 can not only be used to store application software and various data installed in the electronic device 1 , such as codes of capability level analysis programs, but also can be used to temporarily store outputted or to-be-outputted data.

In some embodiments, the processor 10 may be composed of integrated circuits, for example, may be composed of a single packaged integrated circuit, or may be composed of multiple integrated circuits with the same function or different functions, including one or more A combination of central processing unit (Central Processing unit, CPU), microprocessor, digital processing chip, graphics processor and various control chips, etc. The processor 10 is the control core (ControlUnit) of the electronic device, and uses various interfaces and lines to connect the various components of the entire electronic device, and runs or executes programs or modules stored in the memory 11 (such as capability level analysis program, etc.), and call the data stored in the memory 11 to execute various functions of the electronic device 1 and process data.

The bus may be a peripheral component interconnect (PCI for short) bus or an extended industry standard architecture (EISA for short) bus or the like. The bus can be divided into address bus, data bus, control bus and so on. The bus is configured to realize connection and communication between the memory 11 and at least one processor 10 and the like.

FIG. 4 only shows an electronic device with components. Those skilled in the art can understand that the structure shown in FIG. 4 does not constitute a limitation to the electronic device 1, and may include fewer or more components, or combinations of certain components, or different arrangements of components.

For example, although not shown, the electronic device 1 can also include a power supply (such as a battery) for supplying power to various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, so that the power supply can be controlled by power management. The device implements functions such as charge management, discharge management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power failure detection circuits, power converters or inverters, power status indicators and other arbitrary components. The electronic device 1 may also include various sensors, bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

Further, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and/or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which are usually used in the electronic device 1 Establish a communication connection with other electronic devices.

Optionally, the electronic device 1 may further include a user interface, which may be a display (Display) or an input unit (such as a keyboard (Keyboard)). Optionally, the user interface may also be a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode, Organic Light Emitting Diode) touch device, and the like. Wherein, the display may also be appropriately called a display screen or a display unit, and is used for displaying information processed in the electronic device 1 and for displaying a visualized user interface.

It should be understood that the embodiments are only for illustration, and are not limited by the structure in the scope of the patent application.

The capability level analysis program stored in the memory 11 in the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can realize:

Specifically, for the specific implementation method of the above instruction by the processor 10, reference may be made to the description of the relevant steps in the embodiment corresponding to FIG. 1 , which will not be repeated here.

Further, if the integrated modules/units of the electronic device 1 are realized in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium may be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM, Read-Only Memory) ).

The present application also provides a computer-readable storage medium, the readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, it can realize:

Calculate the absolute difference between the updated ability value and the ability value before the update

In the several embodiments provided in this application, it should be understood that the disclosed devices, devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional module in each embodiment of the present application may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware, or in the form of hardware plus software function modules.

It will be apparent to those skilled in the art that the present application is not limited to the details of the exemplary embodiments described above, but that the present application can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application.

Therefore, the embodiments should be regarded as exemplary and not restrictive in all points of view, and the scope of the application is defined by the appended claims rather than the foregoing description, and it is intended that the scope of the present application be defined by the appended claims rather than by the foregoing description. All changes within the meaning and range of equivalents of the elements are embraced in this application. Any reference sign in a claim should not be construed as limiting the claim concerned.

The blockchain referred to in this application is a new application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, and encryption algorithm. Blockchain (Blockchain), essentially a decentralized database, is a series of data blocks associated with each other using cryptographic methods. Each data block contains a batch of network transaction information, which is used to verify its Validity of information (anti-counterfeiting) and generation of the next block. The blockchain can include the underlying platform of the blockchain, the platform product service layer, and the application service layer.

The embodiments of the present application may acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

In addition, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or devices stated in the system claims may also be realized by one unit or device through software or hardware. Secondary terms are used to denote names without implying any particular order.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application without limitation. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be Make modifications or equivalent replacements without departing from the spirit and scope of the technical solutions of the present application.

Claims

A capability level analysis method, wherein the method includes:

Obtain the information data of the subject, and calculate the ability value of the subject according to the information data;

Obtaining the response level of each question in the preset question bank, and according to the reaction level and the ability value, selecting a question from the preset question bank that meets the first preset condition and sending it to the subject;

When it is detected that the subject has completed a question, obtain the testee's answer score of the tested question, and update the testee's ability value according to the response level and answer score of each of the tested questions ;

Calculate the absolute difference between the updated ability value and the ability value before the update;

If the absolute difference does not meet the second preset condition, return to the above-mentioned question according to the reaction level and the ability value, select a question from the preset question bank that meets the first preset condition and send it to the the subject's steps;

If the absolute difference satisfies the second preset condition, the latest updated capability value of the subject is taken as the final capability level of the subject.
The ability level analysis method according to claim 1, wherein said calculating the ability value of said subject according to said information data comprises:

Extracting the text features included in the information data to obtain a text feature set;

calculating a relative probability value between each of the text features in the text feature set and a plurality of preset evaluation levels;

Calculate the score of each of the evaluation levels according to the relative probability value, and determine the evaluation level with the highest score as the ability value of the subject.
The ability level analysis method according to claim 1, wherein, according to the reaction level and the ability value, a question satisfying the first preset condition is selected from the preset question bank and sent to the tested subject who, including:

calculating the difficulty value of each said subject according to said reaction level and said ability value;

selecting a topic whose difficulty value satisfies the first preset condition as an optional topic;

A topic is randomly selected from the optional topics and sent to the subject.
The ability level analysis method according to claim 3, wherein said calculating the difficulty value of each said subject according to said reaction level and said ability value comprises:

Use the following preset difficulty evaluation function to calculate the difficulty value corresponding to each said question:

p ui (θ) represents the difficulty value corresponding to the i-th question in the preset question bank when the testee's ability value is equal to θ, and ui represents the response level corresponding to the i-th question in the preset question bank , b ui represents the degree of difficulty for the subject to complete the i-th question in the preset question bank to reach the response level corresponding to ui, D represents a constant, a i represents the i-th question in the preset question bank distinction.
The ability level analysis method according to claim 1, wherein, updating the ability value of the subject according to the response level and answer score of each of the tested questions includes:

judging whether the answer score of each of the tested questions matches the response level of the tested questions according to the preset mapping relationship between the topic score and the response level;

If the answer score of each of the tested questions matches the response level of the tested question, the answer result of the tested question is set to 1;

If the answer score of each of the tested questions does not match the response level of the tested question, the answer result of the tested question is set to 0;

Using the preset maximum likelihood function, according to the answer results of each of the tested questions, calculate the predictive ability value of the subject, and use the predictive ability value as the updated ability of the subject value.
The ability level analysis method according to claim 5, wherein said using the preset maximum likelihood function, according to the answer results of each of the tested questions, calculating the predictive ability value of the subject, including :

Using the following preset maximum likelihood function to calculate the predictive ability value of the subject:

Among them, L(θ|V) represents the answering result of the testee when completing the V-th question, θ represents the corresponding predictive ability value of the testee when completing the V-th question, and ui represents the i-th question in the preset question bank. The response level of the first question, ki represents the testee’s answer score in answering the i-th question, and record uik represents the answer result of the i-th question in the preset question bank.
The ability level analysis method according to any one of claims 1 to 6, wherein, if the absolute difference value does not meet the second preset condition, return to the above-mentioned response level and the ability value, The step of selecting a question satisfying the first preset condition from the preset question bank and sending it to the subject is replaced by:

Judging whether the number of tested questions is greater than the preset assessment question volume threshold;

If the number of the tested questions is not greater than the threshold of the number of evaluation questions, return to the above-mentioned response level and the ability value, select a question from the preset question bank that meets the first preset condition and send it steps for said subject;

If the number of the tested questions is greater than the threshold of the number of evaluation questions, the latest updated ability value of the tested person is taken as the final ability level of the tested person.
A capability level analysis device, wherein the device includes:

Ability preliminary evaluation module, used to obtain the information data of the subject, and calculate the ability value of the subject according to the information data;

The question bank topic selection module is used to obtain the response level of each question in the preset question bank, and select a question from the preset question bank that meets the first preset condition according to the reaction level and the ability value and send it to all Describe the subject;

An ability update module, configured to obtain the testee's answer scores of the tested questions when it is detected that the testee completes a question, and update the said testee according to the response level and answer score of each said tested question. The ability value of the testee;

A level determination module, configured to calculate the absolute difference between the updated capability value and the pre-updated capability value, and if the absolute difference does not meet the second preset condition, return to the above-mentioned The step of selecting a question satisfying the first preset condition from the preset question bank and sending it to the subject, if the absolute difference satisfies the second preset condition, the The latest updated capability value of the subject is used as the final capability level of the subject.
An electronic device, wherein the electronic device includes:

at least one processor; and,

a memory communicatively coupled to the at least one processor; wherein,

The memory stores a computer program executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can perform the capability level analysis method as follows:

Obtain the information data of the subject, and calculate the ability value of the subject according to the information data;

Obtaining the response level of each question in the preset question bank, and according to the reaction level and the ability value, selecting a question from the preset question bank that meets the first preset condition and sending it to the subject;

When it is detected that the subject has completed a question, obtain the testee's answer score of the tested question, and update the testee's ability value according to the response level and answer score of each of the tested questions ;

Calculate the absolute difference between the updated ability value and the ability value before the update;

If the absolute difference does not meet the second preset condition, return to the above-mentioned question according to the reaction level and the ability value, select a question from the preset question bank that meets the first preset condition and send it to the the subject's steps;

If the absolute difference satisfies the second preset condition, the latest updated capability value of the subject is taken as the final capability level of the subject.
The electronic device according to claim 9, wherein said calculating the ability value of said subject according to said information data comprises:

Extracting the text features included in the information data to obtain a text feature set;

calculating a relative probability value between each of the text features in the text feature set and a plurality of preset evaluation levels;

Calculate the score of each of the evaluation levels according to the relative probability value, and determine the evaluation level with the highest score as the ability value of the subject.
The electronic device according to claim 9, wherein, according to the reaction level and the ability value, a question satisfying the first preset condition is selected from the preset question bank and sent to the subject, include:

calculating the difficulty value of each said subject according to said reaction level and said ability value;

selecting a topic whose difficulty value satisfies the first preset condition as an optional topic;

A topic is randomly selected from the optional topics and sent to the subject.
The electronic device according to claim 11, wherein said calculating the difficulty value of each of said questions according to said reaction level and said ability value comprises:

Use the following preset difficulty evaluation function to calculate the difficulty value corresponding to each said question:

p ui (θ) represents the difficulty value corresponding to the i-th question in the preset question bank when the testee's ability value is equal to θ, and ui represents the response level corresponding to the i-th question in the preset question bank , b ui represents the degree of difficulty for the subject to complete the i-th question in the preset question bank to reach the response level corresponding to ui, D represents a constant, a i represents the i-th question in the preset question bank distinction.
The electronic device according to claim 9, wherein, updating the ability value of the subject according to the response level and answer score of each of the tested questions includes:

judging whether the answer score of each of the tested questions matches the response level of the tested questions according to the preset mapping relationship between the topic score and the response level;

If the answer score of each of the tested questions matches the response level of the tested question, the answer result of the tested question is set to 1;

If the answer score of each of the tested questions does not match the response level of the tested question, the answer result of the tested question is set to 0;

Using the preset maximum likelihood function, according to the answer results of each of the tested questions, calculate the predictive ability value of the subject, and use the predictive ability value as the updated ability of the subject value.
The electronic device according to claim 13, wherein said using a preset maximum likelihood function to calculate the predictive ability value of said subject according to the answer results of each of said tested questions comprises:

Using the following preset maximum likelihood function to calculate the predictive ability value of the subject:

Among them, L(θ|V) represents the answering result of the testee when completing the V-th question, θ represents the corresponding predictive ability value of the testee when completing the V-th question, and ui represents the i-th question in the preset question bank. The response level of the first question, ki represents the testee’s answer score in answering the i-th question, and record uik represents the answer result of the i-th question in the preset question bank.
A computer-readable storage medium, storing a computer program, wherein, when the computer program is executed by a processor, the following capability level analysis method is implemented:

Obtain the information data of the subject, and calculate the ability value of the subject according to the information data;

Obtaining the response level of each question in the preset question bank, and according to the reaction level and the ability value, selecting a question from the preset question bank that meets the first preset condition and sending it to the subject;

When it is detected that the subject has completed a question, obtain the testee's answer score of the tested question, and update the testee's ability value according to the response level and answer score of each of the tested questions ;

Calculate the absolute difference between the updated ability value and the ability value before the update;

If the absolute difference does not meet the second preset condition, return to the above-mentioned question according to the reaction level and the ability value, select a question from the preset question bank that meets the first preset condition and send it to the the subject's steps;

If the absolute difference satisfies the second preset condition, the latest updated capability value of the subject is taken as the final capability level of the subject.
The computer-readable storage medium according to claim 15, wherein the calculating the ability value of the subject according to the information data includes:

Extracting the text features included in the information data to obtain a text feature set;

calculating a relative probability value between each of the text features in the text feature set and a plurality of preset evaluation levels;

Calculate the score of each of the evaluation levels according to the relative probability value, and determine the evaluation level with the highest score as the ability value of the subject.
The computer-readable storage medium according to claim 15, wherein, according to the reaction level and the ability value, a question satisfying the first preset condition is selected from the preset question bank and sent to the subject testers, including:

calculating the difficulty value of each said subject according to said reaction level and said ability value;

selecting a topic whose difficulty value satisfies the first preset condition as an optional topic;

A topic is randomly selected from the optional topics and sent to the subject.
The computer-readable storage medium according to claim 17, wherein said calculating the difficulty value of each of said questions according to said reaction level and said ability value comprises:

Use the following preset difficulty evaluation function to calculate the difficulty value corresponding to each said question:

p ui (θ) represents the difficulty value corresponding to the i-th question in the preset question bank when the testee's ability value is equal to θ, and ui represents the response level corresponding to the i-th question in the preset question bank , b ui represents the degree of difficulty for the subject to complete the i-th question in the preset question bank to reach the response level corresponding to ui, D represents a constant, a i represents the i-th question in the preset question bank distinction.
The computer-readable storage medium according to claim 15, wherein, updating the ability value of the subject according to the response level and answer score of each of the tested questions includes:

judging whether the answer score of each of the tested questions matches the response level of the tested questions according to the preset mapping relationship between the topic score and the response level;

If the answer score of each of the tested questions matches the response level of the tested question, the answer result of the tested question is set to 1;

If the answer score of each of the tested questions does not match the response level of the tested question, the answer result of the tested question is set to 0;

Using the preset maximum likelihood function, according to the answer results of each of the tested questions, calculate the predictive ability value of the subject, and use the predictive ability value as the updated ability of the subject value.
The computer-readable storage medium as claimed in claim 19, wherein said use of a preset maximum likelihood function calculates the predictive ability value of said subject according to the answer results of each of said tested questions, include:

Using the following preset maximum likelihood function to calculate the predictive ability value of the subject:

Among them, L(θ|V) represents the answering result of the testee when completing the V-th question, θ represents the corresponding predictive ability value of the testee when completing the V-th question, and ui represents the i-th question in the preset question bank. The response level of the first question, ki represents the testee’s answer score in answering the i-th question, and record uik represents the answer result of the i-th question in the preset question bank.