CN111700611A - Epiphany assessment method and related equipment - Google Patents

Abstract

The embodiment of the present invention discloses an epiphany ability evaluation method and related equipment. According to the English word data and the graph database, the tester is respectively tested for the epiphany ability, and the first detection parameter and the second detection parameter are obtained, wherein the first detection parameter, the second detection parameter and the second detection parameter are obtained. The second detection parameter is associated with the epiphany ability; then the tester's first epiphany evaluation information and second epiphany evaluation information are obtained respectively according to the first detection parameter and the second detection parameter, so as to obtain the first epiphany evaluation information and the second epiphany evaluation information according to the first and second The epiphany evaluation information comprehensively evaluates the tester's epiphany ability. In particular, since there is a graph epiphany detection branch that is less affected by the test subject's vocabulary, age, cultural background, etc., the evaluation method of the embodiment of the present invention can adapt to the epiphany detection needs of test subjects of different ages and education levels , and combined with English word epiphany detection and graphic epiphany detection to evaluate epiphany, the evaluation accuracy is higher.

Description

Epiphany assessment method and related equipment

technical field

The present invention relates to the field of Internet technologies, and in particular, to a method for evaluating the ability of epiphany and related equipment.

Background technique

The existing solutions for detecting epiphany mainly include CRAT (Compound Remote Associates Task) and Anagram procedure. The CRAT scheme first presents the subjects with several unrelated words and asks the subjects to provide a new word that can link several unrelated words (Kizilirmak et al., 2019). The word guessing method is to show the subjects a string of English words that are scrambled in alphabetical order, and ask the subjects to give the correct English words. After solving a problem, subjects were asked to inform whether the solution to the problem emerged suddenly (“epiphant”) or was derived through analytical reasoning (“analytical”) (Oh et al., 2020). Both programs require the subjects to have a certain foundation of mastery of English or Chinese vocabulary, and the ability to understand and analyze is evaluated by testing the subjects' problem-solving time and correct rate.

The existing schemes are all based on word association and arrangement tasks, which require subjects to have a certain knowledge of Chinese and English vocabulary. The generalizability of subjects of different ages and cultural backgrounds is not strong, and the test results are too dependent on the subjects' ability to master words. If the subjects do not master certain English words, the accuracy of the test results will be greatly limited. .

SUMMARY OF THE INVENTION

The embodiments of the present invention provide a method and related equipment for evaluating the insight ability, which can effectively improve the accuracy of evaluating the insight ability.

In a first aspect, an embodiment of the present invention provides a method for evaluating insight ability, including:

According to the English word database, the tester's epiphany ability is detected, and the first detection parameter is obtained;

Perform epiphany ability detection on the tester according to the graph database, and obtain a second detection parameter, wherein the first detection parameter and the second detection parameter are associated with the epiphany ability;

The first epiphany evaluation information and the second epiphany evaluation information of the tester are obtained according to the first detection parameter and the second detection parameter, respectively.

Optionally, the first detection parameter includes a first EEG index, a first reaction time, a first subjective evaluation, a first correct rate, and a first percentage of epiphany;

According to the English word database, the tester is tested for the ability of epiphany, and the first test parameters are obtained, including:

Determine test words for ability detection according to the English word database;

outputting the scrambled test words to the tester;

Obtain the tester's first EEG index in the process of recovering the word, the first reaction time for recovering the word, and the tester's first subjective evaluation of the way to recover the word, the first EEG index and the epiphany Ability-related, the first subjective evaluation includes epiphany and analysis;

Obtain the first correct rate of the tester's recovery of the test words and the first proportion of the epiphany in the recovery of the words.

Optionally, perform epiphany ability detection on the tester according to the English word database, and obtain the first detection parameter, including:

According to the tester's age and education, the English word database for detecting the tester's epiphany ability is determined from the English word database of different difficulty levels.

Optionally, perform epiphany ability detection on the tester according to the English word database, and obtain the first detection parameter, including:

After the epiphany ability test, obtain the tester's recognition result of the test word;

The identification result is identification failure, and the first EEG index, the first reaction time and the first subjective evaluation of the test word are eliminated;

The first correct rate and the first proportion are obtained according to the eliminated data.

Optionally, the second detection parameter includes a second EEG index, a second reaction time, a second subjective evaluation, a second correct rate, and a second percentage of epiphany;

Test the tester's epiphany ability according to the graph database, and obtain the second test parameters, including:

determining a test image for capability detection according to the graphic database, the graphic database comprising a plurality of images, and the images are composed of a plurality of basic graphics;

outputting the test image after disturbing the position of the basic graphics to the tester;

Obtain the tester's second EEG index in the process of restoring the test image, the second reaction time for restoring the test image, and the tester's second subjective evaluation of the way to restore the test image, the second EEG The indicator is related to the ability of epiphany, and the second subjective evaluation includes epiphany and analysis;

Obtain the second correct rate of the tester in restoring the test image and the second proportion of epiphany in the way of restoring words.

Optionally, according to the first detection parameter and the second detection parameter, respectively obtain the first epiphany evaluation information and the second epiphany evaluation information of the tester, including:

Calculate the first detection parameter, the parameter of the first epiphany upper limit, and the parameter of the first epiphany lower limit according to the first detection parameter, the parameter of the first epiphany upper limit, and the parameter of the first epiphany lower limit The relative Euclidean distance between the two, the first epiphany evaluation information of the tester is determined according to the relative Euclidean distance;

Calculate the second detection parameter, the parameter of the second epiphany upper limit, and the parameter of the second epiphany lower limit according to the second detection parameter, the parameter of the second epiphany upper limit, and the parameter of the second epiphany lower limit The relative Euclidean distance between them is determined according to the relative Euclidean distance. The tester's second epiphany evaluation information is determined.

Optionally, according to the first detection parameter and the second detection parameter, respectively obtain the first epiphany evaluation information and the second epiphany evaluation information of the tester, including:

Clustering the first detection parameters and the second detection parameters of the multiple testers respectively to obtain multiple first sets and multiple second sets;

According to the cluster centers of the first set, the parameters of the upper limit of the first epiphany, the parameters of the lower limit of the first epiphany, the cluster centers of the first set and the parameters of the upper limit of the first epiphany are calculated. The relative Euclidean distance between the parameters of the lower limit of comprehension, according to the relative Euclidean distance, determine the first epiphany evaluation information of the testers in the first set;

According to the cluster centers of the second set, the parameters of the upper limit of the second epiphany, the parameters of the lower limit of the second epiphany, the cluster centers of the second set and the parameters of the upper limit of the second epiphany are calculated. The relative Euclidean distance between the parameters of the two lower limits of epiphany, and the second epiphany evaluation information of the testers in the second set is determined according to the relative Euclidean distance.

In a second aspect, an embodiment of the present invention provides an epiphany ability evaluation device, including:

The first detection module is used to perform epiphany ability detection on the tester according to the English word database, and obtain the first detection parameter;

A second detection module, configured to perform epiphany ability detection on the tester according to the graph database, and obtain a second detection parameter, wherein the first detection parameter and the second detection parameter are associated with the epiphany ability;

The evaluation module is configured to obtain the first epiphany evaluation information and the second epiphany evaluation information of the tester according to the first detection parameter and the second detection parameter, respectively.

In a third aspect, an embodiment of the present invention provides an epiphany ability evaluation device, including: a processor and a memory;

The processor is connected to a memory, wherein the memory is used to store program codes, and the processor is used to call the program codes to execute the insight ability evaluation method according to the first aspect.

In a fourth aspect, an embodiment of the present invention provides a computer storage medium, where the computer storage medium stores a computer program, and the computer program includes program instructions, and when executed by a processor, the program instructions are executed as in the first aspect The epiphany ability assessment method described.

In the embodiment of the present invention, the tester is respectively tested for the epiphany ability according to the English word data and the graph database, and the first detection parameter and the second detection parameter are obtained, wherein the first detection parameter and the second detection parameter are associated with the epiphany ability; The first detection parameter and the second detection parameter respectively obtain the first epiphany evaluation information and the second epiphany evaluation information of the tester, so as to obtain the tester's epiphany ability according to the first epiphany evaluation information and the second epiphany evaluation information Conduct a comprehensive assessment. In particular, since there is a graph epiphany detection branch that is less affected by the test subject's vocabulary, age, cultural background, etc., the evaluation method of the embodiment of the present invention can adapt to the epiphany detection needs of test subjects of different ages and education levels , and combined with English word epiphany detection and graphic epiphany detection to evaluate epiphany, the evaluation accuracy is higher.

Description of drawings

In order to explain the technical solutions of the embodiments of the present invention more clearly, the following briefly introduces the accompanying drawings used in the description of the embodiments. Obviously, the drawings in the following description are some embodiments of the present invention, which are of great significance to the art For those of ordinary skill, other drawings can also be obtained from these drawings without any creative effort.

1 is a schematic flowchart of a method for evaluating insight ability provided by an embodiment of the present invention;

Figure 2a and Figure 2b are schematic diagrams of images of a method for assessing insight ability provided by an embodiment of the present invention;

3 is a schematic structural diagram of an epiphany ability evaluation device provided by an embodiment of the present invention;

FIG. 4 is a schematic structural diagram of an epiphany ability evaluation device provided by an embodiment of the present invention.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

It should be understood that the terms "first", "second" and the like in the description and claims of the present application and the drawings are used to distinguish different objects, rather than to describe a specific order. Furthermore, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but optionally also includes unlisted steps or units, or optionally also includes For other steps or units inherent to these processes, methods, products or devices.

Reference herein to an "embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor a separate or alternative embodiment that is mutually exclusive of other embodiments. It is explicitly and implicitly understood by those skilled in the art that the described embodiments of the present invention may be combined with other embodiments.

Creativity is a high-level thinking activity that does not depend on a single mental activity or the activation of a certain brain area, but is a complex cognitive process that is coordinated by multiple brain areas. The detection of creative thinking usually needs to be done in specific cognitive activities. For example, in a problem-solving task, creative thinking is embodied as an epiphany, usually as an idea, a solution to a problem, etc. that pops into consciousness in an "all-or-nothing" fashion, also known as "Ah ha time". An epiphany is considered to be a manifestation of the ability to innovate, as it is usually a completely new idea or solution that emerges suddenly. Corresponding to this is the analytical ability, which emphasizes the step-by-step analysis of problems and solutions with the participation of consciousness. Analytical capabilities often suggest using existing solutions, or a combination of existing solutions, to solve problems. But epiphanies often lead to new solutions in an all-or-none fashion. Also, unlike analytical skills, epiphanies are generally accompanied by strong rewarding feedback. In the process of cultivating creative thinking, cognitive activities such as epiphany often form a benign positive feedback process, that is, the spiritual pleasure brought by epiphany will motivate students to think further to strengthen this process.

In the prior art, in order to realize the detection of epiphany ability, the CRAT method and the word guessing method can be used for detection. However, the accuracy of the detection results of the aforementioned two methods depends to a certain extent on the vocabulary mastery of the tester, resulting in the above two methods. The detection accuracy of the epiphany ability of this method is not high. Therefore, the present application proposes an epiphany ability evaluation method, which can meet the testing needs of testers of different ages and cultural backgrounds, and has high evaluation accuracy.

Please refer to FIG. 1 , which is a schematic flowchart of a method for evaluating an insight ability provided by an embodiment of the present invention; the method for evaluating an insight ability includes:

101. Perform epiphany ability detection on the tester according to the English word database, and obtain the first detection parameter;

Specifically, the English word database is used for epiphany ability detection, that is, word guessing. Generally, during detection, the alphabetical order of words in the database is scrambled, and the tester performs letter recovery, and obtains the tester's letter recovery process. The relevant parameter is used as the first detection parameter, and the first detection parameter is associated with the epiphany ability.

102. Perform epiphany ability detection on the tester according to the graph database, and obtain second detection parameters;

Specifically, the method of detecting the tester's ability to understand according to the graphic database is a non-verbal graphic detection paradigm. The graphic detection paradigm requires the tester to combine several basic geometric figures into a common figure, including children, the elderly, and the elderly. The testers including the testers have strong ability to recognize and understand graphics, which can effectively avoid the tester's vocabulary limit on the accuracy of the test results. Similarly, the relevant parameters of the tester in the graphic combination process are obtained as the second detection parameter, and the second detection parameter is associated with the epiphany ability.

103. Obtain the first epiphany evaluation information and the second epiphany evaluation information of the tester according to the first detection parameter and the second detection parameter, respectively.

Specifically, the tester's first epiphany evaluation information can be obtained according to the first detection parameter, and the tester's second epiphany evaluation information can be obtained according to the second detection parameter, wherein the first epiphany evaluation information and the second epiphany evaluation information The evaluation information may be an epiphany ability score, or an epiphany ability grade/gear, etc., which indicates the level of the epiphany ability.

Using the method in Figure 1, the tester's first epiphany evaluation information and second epiphany evaluation information can be obtained. Since the graphic detection method is less affected by vocabulary, age, cultural background, etc., by flexibly comparing graphic detection and word guessing methods The results will help to comprehensively investigate the development of epiphany ability of different age groups, effectively overcome the influence of the tester's vocabulary mastery on the accuracy of epiphany ability evaluation results, and ensure the accuracy of epiphany ability evaluation. Epiphany testing needs of test takers by age group and education level.

In particular, the execution order of step 101 and step 102 is not limited, and step 101 may be executed first, and then step 102 may be executed. Alternatively, step 102 may be performed first, and then step 101 may be performed.

In a possible embodiment, the first detection parameter includes a first EEG index, a first reaction time, a first subjective evaluation, a first correct rate, and a first percentage of epiphany; step 101 includes:

1011. Determine a test word for ability detection according to an English word database;

Specifically, an English word database for epiphany ability detection is pre-established, wherein the words in the English word database may include words of elementary introductory English, intermediate English, and advanced English, that is, the English word database includes English words of different difficulty. When the tester's epiphany ability is detected according to the English word database, a certain number of words may be randomly selected from the English word database as test words.

1012. Output the test words after scrambled alphabetical order to the tester;

Specifically, at the beginning of the test, according to the test words selected in step 1011, the alphabetical order of each test word is scrambled, and then output to the tester in turn. Among them, the alphabetical order can be randomly shuffled, so as to prevent the tester from knowing the law of shuffling the alphabetical order, which affects the accuracy of the epiphany ability detection; and the tester is required to input the correct English words. For example, output "taody" to the tester on the computer or mobile phone, and ask the tester to input the correct English word, and the correct word corresponding to "taody" is "today".

1013. Obtain the tester's first EEG index in the process of recovering the word, the first reaction time for recovering the word, and the tester's first subjective evaluation of the method of recovering the word. The first EEG index is related to the ability of epiphany. - Subjective evaluation includes epiphany and analysis;

Specifically, since there are obvious changes in the EEG signal when the epiphany occurs, when the tester performs the epiphany ability test, the tester's EEG signal will be monitored synchronously to obtain the first EEG indicator. In this embodiment, the first EEG indicator is related to the epiphany ability, including the energy in the gamma band of the prefrontal lobe and the energy in the alpha band of the temporal lobe. After the monitoring signal is filtered through noise reduction and interference signals such as eye movements are removed, a relatively pure EEG signal can be obtained. Then, by calculating the energy changes in the relevant gamma and alpha frequency bands, the dynamic changes of the tester's epiphany and creative thinking can be objectively analyzed.

In addition, in the process of the tester recovering the words, the length of time the tester inputs the answer will be monitored, that is, the test words that are scrambled in alphabetical order are output to the tester, and the time until the tester inputs the answer will be used as the tester. The first reaction time on the test word. In general, the response time of epiphany solutions is generally earlier than that of analytical solutions.

Finally, after the tester entered the answer, the tester was also asked to give a first subjective evaluation on the way of recovering the word. The first subjective evaluation included epiphany and analysis; the answer was selected in an all-or-none manner suddenly What appears in the mind, the epiphany answer, is also obtained through step-by-step reasoning and analysis, that is, the analytical answer. For example, "Epiphany" and "Analysis" can be displayed on the computer or mobile phone for testers to choose.

1014. Obtain the first correct rate of the tester's recovery of the test words and the first proportion of the epiphany among the recovery methods.

Specifically, for all the test words selected in step 1011, calculate the frequency of the epiphany answer, that is, the proportion of the epiphany answer, as the first proportion, the first proportion is used to measure whether the tester prefers analytical or analytical Problem-solving with epiphany. In addition, the correct rate of the tester in this test will be counted as the first correct rate.

In a possible embodiment, in order to improve the accuracy of epiphany ability detection, it is necessary to determine test words of different difficulty according to different situations of the tester. Step 101 further includes:

1015. According to the tester's age and education, determine an English word database for detecting the tester's epiphany ability from English word databases of different difficulty levels.

Specifically, the age is divided into 5 to 12 years old, 13 to 18 years old, 19 to 40 years old, 41 years old to 60 years old, and 61 years old and above; and the education status is below elementary school, junior high school, high school, junior college, undergraduate, and master's degree or above. The English word database of different difficulty is established in advance, and the words in the database are divided into 5 grades according to the indicators such as the common degree of the word and the length of the string, that is, 5 English word databases of different difficulty are established according to the difficulty level from low to high. The first level of difficulty English word database, the second level of difficulty English word database, the third level of difficulty English word database, the fourth level of difficulty English word database, the fifth level of difficulty English word database. In the actual selection, according to the tester's situation, such as age, education level, etc., the word data of different difficulty is called. For example, for a 38-year-old tester A, whose education is primary school, in order to improve the accuracy of the epiphany ability test results, an English word database originally suitable for 13 to 18 years old and a junior high school education (such as the English word database) can be selected. It is the second-level difficulty English word database) to test the epiphany ability of tester A.

On the other hand, when selecting the English word database corresponding to the difficulty according to the age and education of the tester, it can be weighted according to the age and education (the respective weights of age and education can be adjusted as needed) to calculate a recognition score. Age corresponds to different scores (specific scores can be set as needed), different educational situations also correspond to different scores (specific scores can be set as needed), and the corresponding English words can be found according to the recognition score and the English word database correspondence table database. For example, the pre-established English word database correspondence table is shown in Table 1.

Table 1

Assuming that the weight of age is 0.4 and the weight of education status is 0.6, the identification score S is age N*0.4+education status J*0.6, assuming that the age-score correspondence table is shown in Table 2, and the education situation-score correspondence table is shown in the table 3 shown.

Table 2

age group/year Fraction 5-12 5 13-18 10 19-40 20 41-60 10 61 and above 5

table 3

educational status Fraction Below elementary school 1 junior high school 5 high school 10 Specialist 15 Undergraduate 20 Master's degree or above 25

In addition, after the English word database is determined, a certain number of English words can be randomly selected as the test words of the tester, and the number of different test words can also be determined according to the age and education of the tester, for example, according to the difficulty level from low to high The number of test words is divided into 5 grades, namely 5, 10, 15, 20, and 25. Different numbers of test words correspond to English word databases of different difficulty.

For example, during the test, the first level of difficulty in the English word database is to select 5 test words.

The second level of difficulty in the English word database is to select 10 test words.

The third level of difficulty in the English word database is to select 15 test words.

The fourth level of difficulty in the English word database is to select 20 test words.

The fifth difficulty English word database is to select 25 test words.

Different from the above step 1011, it is necessary to select test words with different numbers of words and different levels of difficulty from a single English word database with a large amount of words according to the tester's situation. The speed of determining the test words is slow and the tester's experience is poor. Combining steps 1011 and 1015, since step 1015 pre-establishes English word databases of different difficulty levels, when selecting test words, it is only necessary to determine the English word database corresponding to the difficulty level according to the tester's age and education, and then from the determined English word database. It is enough to select a certain number of test words from the English word database. In contrast, the speed of determining the test words is faster.

In a possible embodiment, in order to further improve the accuracy of the epiphany ability detection result, step 101 further includes:

S1. After the epiphany ability test, obtain the tester's recognition result of the test word;

Specifically, after the tester completes the test word determined in step 1011, the tester is again required to identify the test word used in the above-mentioned detection process, so as to obtain the tester's identification result of the test word. It can be to display the test word list again on the computer or mobile phone, and provide options for the tester to choose whether to recognize it, for example, display "Know", "Don't recognize". It is also possible to provide a paper list, which is checked by the tester.

S2. The identification result is that the identification fails, and the first EEG index, the first reaction time and the first subjective evaluation of the test word are eliminated;

Specifically, if the recognition result is a recognition failure, for example, the tester has checked "do not recognize", then the first EEG index, the first reaction time and the first subjective evaluation of the test word are excluded, and the test word does not participate in other first Calculation of detection parameters.

S3. Obtain the first correct rate and the first proportion according to the eliminated data.

Specifically, after excluding the data of the test words that failed to be recognized, the remaining data are calculated for the first correct rate and the first proportion. For example, if there are 10 test words in total, and 2 words fail to be recognized by the tester, after removing the data corresponding to these two words, the first correct rate and the first proportion corresponding to the remaining 8 test words are calculated as the The tester's final first correct rate and first proportion.

After the test is over, word recognition is performed again to eliminate the test data corresponding to the test words that the tester does not know, so as to improve the accuracy of epiphany ability detection.

It is particularly pointed out that the word discrimination test can be carried out between the period before the official test (for example, the first two weeks), to ensure that the formal test results are not affected by factors such as the tester's vocabulary, and can be adjusted in a targeted manner The database of English words used for formal detection. Conducting formal tests later can also minimize the interference effect of pre-experiments on formal tests. For example, when the pre-test shows that the first correct rate is lower than 50%, the word difficulty can be appropriately adjusted, and the words in the English word database with a lower level of difficulty are used as the test words for the formal test.

In a possible embodiment, the second detection parameter includes a second EEG index, a second reaction time, a second subjective evaluation, a second correct rate, and a second percentage of epiphany; step 102 includes:

1021. Determine a test image for capability detection according to a graphic database, where the graphic database includes multiple images, and the images are composed of multiple basic graphics;

Specifically, each image in the graphics database is made up of several basic graphics, and the basic graphics include circles, triangles, squares, trapezoids, and the like. Referring to Fig. 2a and Fig. 2b, the image of Fig. 2b is formed by splicing the five basic graphics in Fig. 2a. Similar to the English word database, a graph database for epiphany ability detection needs to be established in advance, wherein the graphs in the graph database can include primary difficulty graphs, intermediate difficulty graphs, and advanced difficulty graphs, that is, graphs in the graph database include graphs with different patching difficulties. , the number of basic shapes of each figure of primary difficulty is less than the number of basic figures of each figure of intermediate difficulty, the number of basic figures of each figure of intermediate difficulty is less than the number of basic figures of each figure of advanced difficulty, for example, the number of basic figures of a figure of primary difficulty The number can be 3-5, the number of basic patterns for a basic difficulty pattern can be 6-10, and the number of basic patterns for an advanced difficulty pattern can be 11-15. When the tester's epiphany ability is detected according to the graphic database, a certain number of images can be randomly selected from the graphic database as test images.

1022. Output the test image after disrupting the position of the basic graphic to the tester;

Specifically, output the test image after disrupting the position of the basic graphics to the tester, such as Fig. 2a, which can be displayed on the computer or mobile phone, and require the tester to select the basic graphics in turn through the mouse to combine them into the correct complex Graph, the correct graph is Figure 2b. Among them, the position of the basic figure may be randomly scrambled, so as to prevent the tester from knowing the regularity of the position of the scrambled basic figure, which affects the accuracy of the epiphany ability detection.

1023. Obtain the second EEG index of the tester in the process of recovering the test image, the second reaction time for recovering the test image, and the tester's second subjective evaluation of the method of recovering the test image, the second EEG index and the epiphany ability Relevant, the second subjective evaluation includes epiphany and analysis;

Specifically, similar to the word guessing method, when the epiphany is detected according to the image of the graph database, the EEG signal of the tester is monitored in real time to obtain the second EEG index; the second EEG index can be the energy of the prefrontal gamma band and temporal lobe alpha band energy. At the same time, it is also necessary to obtain the time spent by the tester when restoring the test image, and use this time as the second reaction time, that is, to count the time from outputting the test image that scrambled the position of the graphic to the time when the tester completes the image splicing, which can be calculated as The tester clicks the "Confirm" button displayed on the computer or mobile phone to submit their spliced answers as the deadline. Finally, it is also necessary to obtain the tester's self-evaluation of the method used to restore the image, that is, to give a second subjective evaluation.

1024. Obtain the second correct rate of the tester's recovery of the test image and the second proportion of the epiphany in the recovery of words.

Specifically, after completing all the test images selected in step 1021, calculate the tester's accuracy rate in this recovery test as the second accuracy rate, and calculate the proportion of epiphany in the second subjective evaluation, that is, the first Two proportions, so that the tester's epiphany ability can be subsequently evaluated according to these second detection parameters.

In a possible embodiment, step 102 further includes:

1025. According to the tester's age and education, from the graph databases of different difficulty levels, determine a graph database for detecting the tester's epiphany ability.

Specifically, graph databases with different levels of difficulty can be established in advance according to the number of each basic pattern, mutual intersection, spatial resolution, etc. For example, graph databases with five levels of difficulty can be established, the first level of difficulty pattern database and the second level of difficulty level respectively. Graphic database, third-level difficulty graphics database, fourth-level difficulty graphics database, and fifth-level difficulty graphics database. For example, for a 38-year-old tester A, whose education is primary school, in order to improve the accuracy of the epiphany ability test results, a graph database originally suitable for 13-18 years old and a junior high school education can be selected (for example, the graph database is the first The second-level difficulty graph database) tests the epiphany ability of tester A.

Similarly, when the graph database of the corresponding difficulty level is determined according to the age and education of the tester, another identification score can be obtained by weighting according to age and education (the respective weights of age and education can be adjusted as needed), Different recognition scores correspond to graph databases of different difficulty levels. For example, the weight of age is 0.4, and the weight of education is 0.6. The weighted calculation according to Tables 2 and 3 determines the tester's identification score, and then according to Table 4, the graph database for the tester's epiphany detection can be determined.

Table 4

During the test, a certain number of images can be randomly selected as test images from the above determined graphic database, or different numbers of test images can be determined according to the age and education of the tester, for example, in order of difficulty from low to high. , the number of test images is divided into 5 grades, namely 5, 10, 15, 20, and 25. Different numbers of test images correspond to graph databases with different difficulties.

For example, during the test, the first level of difficulty graph database is to select 5 test images.

The second level of difficulty graph database is to select 10 test images.

The third difficulty graph database is to select 15 test images.

The fourth level of difficulty graph database is to select 20 test images.

The fifth difficulty graph database is to select 25 test images.

Using the method of step 1021, it is necessary to select a test image that is consistent with the tester's age and educational situation from a single graph database with a large number of graphs, and the selection takes a long time. Combining steps 1021 and 1025, using step 1025, you can first determine the graph database that matches the tester's age and education, and then select a certain number of test images from it. Experience the feeling.

In particular, a graphic discrimination test is carried out between the period before the formal test (for example, the first two weeks) to ensure that the formal test results are not affected by factors such as the subject's image recognition, and the formal test can be adjusted in a targeted manner The graph database called when . Conducting formal tests later can also minimize the interference effect of pre-experiments on formal tests. For example, when it is displayed in the pre-test that the first correct rate is lower than 50%, the difficulty of the graph can be appropriately adjusted, and the image in the graph database with a lower difficulty level is used as the test image for the formal test.

In a possible embodiment, whether the tester has an epiphany can be determined according to the first EEG indicator and the first EEG indicator threshold, and when the first EEG indicator is greater than the first EEG indicator threshold, it indicates that an epiphany has occurred. Otherwise, the test subject did not have an epiphany. For example, the thresholds of the first EEG indicators are the gamma frequency band energy threshold and the temporal lobe alpha frequency band energy threshold. When the gamma frequency band energy corresponding to a test word is greater than the gamma frequency band energy threshold, and the temporal lobe alpha frequency band energy corresponding to the test word is greater than the temporal lobe energy threshold When the energy threshold of the leaf alpha frequency band is reached, it indicates that the tester has had an epiphany; otherwise, the tester has not had an epiphany. Similarly, according to the second EEG index and the threshold value of the second EEG index, it can be determined whether the tester has an epiphany, which will not be repeated here.

In a possible embodiment, step 103 includes:

1031. Calculate the relative Euclidean distance between the first detection parameter, the parameter of the first epiphany upper limit, and the parameter of the first epiphany lower limit according to the first detection parameter, the parameter of the first epiphany upper limit, and the parameter of the first epiphany lower limit , according to the relative Euclidean distance to determine the tester's first epiphany evaluation information;

Specifically, the detection parameters corresponding to the upper limit of the first epiphany and the detection parameters corresponding to the lower limit of the first epiphany are preset, wherein the detection parameters of the lower limit of the first epiphany are the detection parameters in the state of no testers, and the first epiphany The first EEG index of the lower limit of force is no-load white noise, the first reaction time and the first subjective evaluation are empty; and the first accuracy rate and the first proportion are 0. The detection parameters of the upper limit of the first epiphany can be the parameters in the ideal epiphany state, that is, for each test word, the first EEG index of the first EEG index is consistent with the epiphany index (that is, the first EEG index is greater than the threshold of the first EEG index) , the first reaction time is less than the ideal epiphany time (which can be obtained according to the limited number of experiments), the first correct rate is 100%, and the first subjective evaluation is the epiphany. The detection parameters corresponding to the upper limit of the first epiphany can be fine-tuned as required, for example, the first correct rate can be 99% and so on.

The first detection parameter (including the first EEG index, the first reaction time, the first subjective evaluation, the first correct rate and the first proportion of the epiphany) is equivalent to a point in the multi-dimensional space. Similarly, the first epiphany The parameter of the upper limit of force corresponds to the point P1 in the multidimensional space, and the parameter of the lower limit of the first epiphany corresponds to the point P2 in the multidimensional space (corresponding to the origin in the multidimensional space). For example, the first detection parameter of tester A is point A in the multi-dimensional space, and the relative Euclidean distance between point A, point P1, and point P2 is equivalent to calculating the relative position of point A between point P1 and point P2. According to the relative Euclidean distance, the tester's first epiphany evaluation information can be obtained. Suppose the first epiphany evaluation information is the epiphany ability score. Since the point P1 represents the highest score of the epiphany ability, assuming that it is 1000 points, it can be converted according to the relative Euclidean distance. For example, if the Euclidean distance between point P1 and point P2 is 100, and the relative Euclidean distance between point A, point P1, and point P2 is 40, tester A’s epiphany ability score is 400. point.

When the first epiphany evaluation information is the epiphany ability level/gear, it can be based on the corresponding relationship between different relative Euclidean distances and different epiphany ability grades/gear. Assuming that the relative Euclidean distance corresponding to the upper limit of the first epiphany is 100, then the relative Euclidean distance is 100-80 corresponding to A-level epiphany ability, 80-60 corresponding to B-level epiphany ability, 60-40 corresponding to C-level epiphany ability, and 40-0 corresponding to C-level epiphany ability Ding and other epiphany ability. If tester A's relative Euclidean distance is 40, tester A's epiphany ability level is D-level epiphany ability.

1032. Calculate the relative Euclidean distance between the second detection parameter, the parameter of the second epiphany upper limit, and the parameter of the second epiphany lower limit according to the second detection parameter, the parameter of the second epiphany upper limit, and the parameter of the second epiphany lower limit , according to the relative Euclidean distance to determine the tester's second epiphany evaluation information.

Specifically, similar to the first detection parameter, detection parameters corresponding to the upper limit of the second epiphany and detection parameters corresponding to the lower limit of the second epiphany need to be preset. Among them, the detection parameter of the second epiphany lower limit is the detection parameter in the state of no testers, the second EEG index of the second epiphany lower limit is no-load white noise, the second reaction time and the second subjective evaluation are empty; and The second accuracy rate and the second proportion are 0. The detection parameters of the upper limit of the second epiphany can be the parameters in the ideal epiphany state, that is, for each test image, the second EEG index is in line with the epiphany index, and the second reaction time is less than the ideal epiphany time (can be based on a limited number of experiments. Statistics), the second correct rate is 100%, and the second subjective evaluation is epiphany. The detection parameters corresponding to the upper limit of the second epiphany can be fine-tuned as required, for example, the second correct rate can be 99% and so on.

According to the same method as the first detection parameter, the relative Euclidean distance between the second detection parameter and the parameter of the second epiphany upper limit and the parameter of the second epiphany lower limit can be calculated and obtained, and the second epiphany can be determined according to the relative Euclidean distance. The second epiphany evaluation information can also be an epiphany ability score or an epiphany ability level/gear.

In particular, if the epiphany evaluation information is calculated using only one graph and word epiphany ability detection result, the epiphany evaluation accuracy is relatively low. Therefore, the same tester can perform multiple tests (more than 2 times) to obtain multiple first detection parameters and multiple second detection parameters, and obtain multiple relative Euclidean distances according to multiple first detection parameters. Calculate the average of the relative Euclidean distances, take the average value as the tester's final relative Euclidean distance, and then calculate the first epiphany evaluation information according to the final relative Euclidean distance, which can ensure the accuracy of the first epiphany evaluation information and avoid single Epiphany assessment error due to chance of detection. Similarly, according to a plurality of second detection parameters, a plurality of relative Euclidean distances are calculated, and then an average value is obtained, and the second epiphany evaluation information is calculated according to the average value.

Wherein, the numbers in step 1031 and step 1032 do not limit the execution order between them. Step 1031 may be executed first, and then step 1032 may be executed; or step 1032 may be executed first, and then step 1031 may be executed; Steps 1031 and 1032 are performed.

In another possible embodiment, step 103 includes:

1033. Perform clustering on the first detection parameters and the second detection parameters of the multiple testers respectively to obtain multiple first sets and multiple second sets;

Specifically, after obtaining the first detection parameter and the second detection parameter of different testers through steps 101 and 102 , the epiphany evaluation can be performed on all the testers at one time. A plurality of first detection parameters are clustered to obtain a plurality of first sets; and a plurality of second detection parameters are clustered to obtain a plurality of second sets. Here, plural refers to two or more.

Among them, the first detection parameter is used as one of the input parameters of the convolutional neural network, and the first EEG index, the first correct rate, the first reaction time and the first proportion are integrated, and the cluster analysis method of unsupervised learning is adopted. A plurality of classification results of the first detection parameters are obtained, that is, a plurality of first sets are obtained, and each first set has a cluster center.

Similarly, the clustering process of unsupervised learning is performed according to the plurality of second detection parameters to obtain a plurality of second sets, each of which has a cluster center.

1034. Calculate the cluster centers of the first set, the parameters of the first epiphany upper limit, and the parameters of the first epiphany lower limit according to the cluster centers of the first set, the parameters of the upper limit of the first epiphany, and the parameters of the lower limit of the first epiphany The relative Euclidean distance between the two, and the first epiphany evaluation information of the testers in the first set is determined according to the relative Euclidean distance;

Specifically, according to the method of step 1031, the cluster centers of the first set are processed as the first detection parameters in step 1031, and the cluster centers of the first set and the parameters of the first epiphany upper limit, the first The relative Euclidean distance between the parameters of the lower limit of epiphany, and then the first epiphany evaluation information of the cluster center can be determined according to the relative Euclidean distance. Since the cluster center of the first set can represent all the The first detection parameter, therefore, the first epiphany evaluation information of the cluster center can be used as the first epiphany evaluation information of all testers corresponding to the first set.

For example, the first set includes 10 first detection parameters, corresponding to 10 testers respectively, and the first epiphany evaluation information of the cluster center of the first set is the first-class epiphany ability, then the 10 tests in the first set The first epiphany evaluation information of the participants is the first-class epiphany ability.

1035. Calculate the cluster centers of the second set, the parameters of the upper limit of the second epiphany, and the parameters of the lower limit of the second epiphany according to the cluster centers of the second set, the parameters of the upper limit of the second epiphany, and the parameters of the lower limit of the second epiphany The relative Euclidean distance between the two, and the second epiphany evaluation information of the testers in the second set is determined according to the relative Euclidean distance.

Specifically, similar to the method in step 1034, referring to the method in step 1032, the second set of cluster centers is calculated to be equal to the second detection parameter in step 1032, and the second epiphany of the second set of cluster centers is calculated. Evaluation information. The second epiphany evaluation information is used as the second epiphany evaluation information of all testers corresponding to the second set.

Using the methods of step 1033, step 1034 and step 1035, the tester can perform the epiphany ability test only once, that is, relatively accurate epiphany evaluation information can be obtained, and the tester's test experience can be improved without the need for multiple tests.

Among them, the numbers in steps 1034 and 1035 do not limit the execution order between them. It may be that step 1034 is performed first, and then step 1035 is performed; it may be that step 1035 is performed first, and then step 1034 is performed; Steps 1034 and 1035 are performed.

In step 103, the first epiphany evaluation information and the second epiphany evaluation information are obtained according to the first detection parameter and the second detection parameter of the tester respectively. The characteristic data can comprehensively judge the epiphany ability of the tester, avoid the problem of over-reliance on the subjective evaluation of the tester, and also provide a basis for the in-depth analysis of the EEG data.

Further, the epiphany ability evaluation method also includes:

According to the tester's first epiphany evaluation information and second epiphany evaluation information, the tester's comprehensive analysis report on epiphany is obtained.

Among them, the introduction of a non-verbal graphic detection system in the epiphany detection will greatly compensate for the dependence of the traditional scheme on Chinese and English vocabulary, and is suitable for promotion to students of different ages and developmental levels. Using two paradigms, verbal and non-verbal, based on the test results of the two paradigms, comprehensively compare the students' ability of epiphany in processing language tasks and graphic tasks, and obtain an in-depth report of students' comprehensive epiphany ability. The test results are described separately. By comprehensively comparing students' performances in language tasks and graphic tasks, students' ability of epiphany can be systematically analyzed in order to obtain more comprehensive and reliable test results. In addition, further analysis of the two types of test results will help to deeply understand the cognitive performance of testers (such as students) in different tasks, and provide important reference and basis for educational practice.

The comprehensive analysis report may include the first epiphany evaluation information, the second epiphany evaluation information, the analysis of the first epiphany evaluation information, the analysis of the second epiphany evaluation information, the epiphany training suggestion, and the like. After the tester has completed the epiphany ability test, the comprehensive analysis report can be output on the computer or mobile phone. Among them, when the comprehensive analysis report is output on the mobile terminal, the cloud server can calculate the first epiphany evaluation information and the second epiphany evaluation information, and generate a comprehensive analysis report, which is sent to the tester's mobile terminal for convenient testing. to view the assessment results.

Based on the description of the above-mentioned embodiment of the insight ability evaluation method, an embodiment of the present invention also discloses an insight ability evaluation device. Referring to FIG. 3, FIG. 3 is a schematic structural diagram of an insight ability evaluation device provided by an embodiment of the present invention. The evaluation set includes:

The first detection module 301 is configured to perform epiphany ability detection on the tester according to the English word database, and obtain the first detection parameter;

The second detection module 302 is configured to perform epiphany ability detection on the tester according to the graph database, and obtain a second detection parameter, where the first detection parameter and the second detection parameter are associated with the epiphany ability;

The evaluation module 303 is configured to obtain the first epiphany evaluation information and the second epiphany evaluation information of the tester according to the first detection parameter and the second detection parameter, respectively.

In a possible embodiment, the first detection parameter includes a first EEG index, a first reaction time, a first subjective evaluation, a first correct rate, and a first percentage of epiphany; the first detection module 301 includes:

The first submodule 3011 is used to determine the test words for ability detection according to the English word database;

The second submodule 3012 is used for outputting the test word after scrambled alphabetical order to the tester;

The third sub-module 3013 is used to obtain the first EEG index of the tester in the process of recovering the word, the first reaction time for recovering the word, and the first subjective evaluation of the tester on the way of recovering the word, the first EEG index Related to epiphany ability, the first subjective evaluation includes epiphany and analysis;

The fourth sub-module 3014 is used to obtain the first correct rate of the tester's recovery of the test word and the first proportion of the epiphany in the recovery of the word.

In a possible embodiment, the first detection module 301 includes:

The fifth sub-module 3015 is used to determine the English word database for detecting the tester's epiphany ability from the English word database of different difficulty levels according to the tester's age and education;

In a possible embodiment, the first detection module 301 includes:

The sixth submodule 3016 is used to obtain the tester's recognition result of the test word after the epiphany ability detection;

The seventh sub-module 3017 is used for the identification result of identification failure, and removes the first EEG index, the first reaction time and the first subjective evaluation of the test word;

The fourth sub-module 3014 is specifically configured to obtain the first correct rate and the first proportion according to the excluded data.

In a possible embodiment, the second detection parameter includes a second EEG index, a second reaction time, a second subjective evaluation, a second correct rate, and a second percentage of epiphany; the second detection module 302 includes:

The eighth sub-module 3021 is used for determining a test image for capability detection according to a graph database, the graph database includes a plurality of images, and the images are composed of a plurality of basic graphs;

The ninth submodule 3022 is used to output the test image after disturbing the position of the basic graphic to the tester;

The tenth sub-module 3023 is used to obtain the second EEG index of the tester in the process of restoring the test image, the second reaction time for restoring the test image, and the tester's second subjective evaluation of the way to restore the test image, the second EEG indicators are related to epiphany ability, and the second subjective evaluation includes epiphany and analysis;

The eleventh sub-module 3024 is configured to obtain the second correct rate of the tester in restoring the test image and the second proportion of the epiphany in the way of restoring words.

In a possible embodiment, the second detection module 302 includes:

The twelfth sub-module 3025 is configured to determine a graph database for detecting the tester's epiphany ability from graph databases of different difficulty levels according to the tester's age and education.

In a possible embodiment, the evaluation module 303 includes:

The thirteenth sub-module 3031 is configured to calculate the first detection parameter, the parameter of the first epiphany upper limit, and the parameter of the first epiphany lower limit according to the first detection parameter, the parameter of the first epiphany upper limit, and the parameter of the first epiphany lower limit The relative Euclidean distance between the parameters, according to the relative Euclidean distance to determine the tester's first epiphany evaluation information;

The fourteenth sub-module 3032 is configured to calculate the second detection parameter, the parameter of the second epiphany upper limit, the parameter of the second epiphany lower limit according to the second detection parameter, the parameter of the second epiphany upper limit, and the parameter of the second epiphany lower limit The relative Euclidean distance between parameters, according to the relative Euclidean distance to determine the tester's second epiphany evaluation information.

In a possible embodiment, the evaluation module 303 includes:

The fifteenth sub-module 3033 is configured to separately cluster the first detection parameters and the second detection parameters of the multiple testers to obtain multiple first sets and multiple second sets;

The sixteenth submodule 3034 is configured to calculate the cluster centers of the first set and the parameters of the first epiphany upper limit according to the cluster centers of the first set, the parameters of the upper limit of the first epiphany, and the parameters of the lower limit of the first epiphany, The relative Euclidean distance between the parameters of the first epiphany lower limit, and the first epiphany evaluation information of the testers in the first set is determined according to the relative Euclidean distance;

The seventeenth sub-module 3035 is configured to calculate the cluster centers of the second set and the parameters of the upper limit of the second epiphany according to the cluster centers of the second set, the parameters of the upper limit of the second epiphany, and the parameters of the lower limit of the second epiphany, The relative Euclidean distance between the parameters of the second epiphany lower limit, and the second epiphany evaluation information of the testers in the second set is determined according to the relative Euclidean distance.

It is worth noting that, for the specific function implementation manner of the epiphany ability assessment device, reference may be made to the description of the above-mentioned epiphany ability assessment method, which will not be repeated here. The individual units or modules in the epiphany ability evaluation device may be combined into one or several other units or modules, respectively or all, or some of the units or modules may be further divided into functional units. The same operation can be achieved without affecting the realization of the technical effects of the embodiments of the present invention. The above units or modules are divided based on logical functions. In practical applications, the function of one unit (or module) can also be implemented by multiple units (or modules), or the functions of multiple units (or modules) are implemented by one unit. (or module) implementation.

Based on the descriptions of the foregoing method embodiments and apparatus embodiments, the embodiments of the present invention further provide an epiphany ability evaluation device.

Please refer to FIG. 4 , which is a schematic structural diagram of an epiphany ability evaluation device provided by an embodiment of the present invention. As shown in FIG. 4 , the above-mentioned epiphany ability evaluation apparatus can be applied to the epiphany ability evaluation device 400 , and the epiphany ability evaluation device 400 may include: a processor 401 , a network interface 404 and a memory 405 , in addition, the epiphany ability The evaluation device 400 may also include a user interface 403 , and at least one communication bus 402 . Among them, the communication bus 402 is used to realize the connection and communication between these components. The user interface 403 may include a display screen (Display) and a keyboard (Keyboard), and the optional user interface 403 may also include a standard wired interface and a wireless interface. Optionally, the network interface 404 may include a standard wired interface and a wireless interface (eg, a WI-FI interface). The memory 405 may be high-speed RAM memory, or may be non-volatile memory, such as at least one disk memory. The memory 405 can optionally also be at least one storage device located away from the aforementioned processor 401 . As shown in FIG. 4 , the memory 405 as a computer storage medium may include an operating system, a network communication module, a user interface module, and a device control application program.

In the epiphany ability evaluation device 400 shown in FIG. 4 , the network interface 404 can provide a network communication function; the user interface 403 is mainly used to provide an input interface for the user; and the processor 401 can be used to call the device stored in the memory 405 Control the application to implement the method steps of the insight assessment method described above.

It should be understood that the epiphany ability evaluation device 400 described in the embodiment of the present invention can execute the foregoing insight ability evaluation method, and can also execute the description of the foregoing epiphany ability evaluation apparatus, which will not be repeated here. In addition, the description of the beneficial effects of using the same method will not be repeated.

In addition, it should be pointed out here that an embodiment of the present invention further provides a computer storage medium, and the computer storage medium stores a computer program executed by the aforementioned epiphany ability evaluation device, and the computer program includes The program instructions, when the processor executes the program instructions, can execute the description of the foregoing insight ability evaluation method, and therefore will not be repeated here. In addition, the description of the beneficial effects of using the same method will not be repeated. For technical details not disclosed in the computer storage medium embodiments involved in the present invention, please refer to the description of the method embodiments of the present invention.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. During execution, the processes of the embodiments of the above-mentioned methods may be included. The storage medium may be a magnetic disk, an optical disk, a read-only memory (Read-Only Memory, ROM), or a random access memory (Random Access Memory, RAM) or the like.

The above disclosures are only preferred embodiments of the present invention, and of course, the scope of the rights of the present invention cannot be limited by this. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims (10)

1. a kind of insight ability evaluation method, is characterized in that, comprises: According to the English word database, the tester's epiphany ability is detected, and the first detection parameter is obtained; Perform epiphany ability detection on the tester according to the graph database, and obtain a second detection parameter, wherein the first detection parameter and the second detection parameter are associated with the epiphany ability; The first epiphany evaluation information and the second epiphany evaluation information of the tester are obtained according to the first detection parameter and the second detection parameter, respectively. 2. The method according to claim 1, wherein the first detection parameter comprises the first EEG index, the first reaction time, the first subjective evaluation, the first correct rate and the first proportion of the epiphany ; According to the English word database, the tester is tested for the ability of epiphany, and the first test parameters are obtained, including: Determine test words for ability detection according to the English word database; outputting the scrambled test words to the tester; Obtain the tester's first EEG index in the process of recovering the word, the first reaction time for recovering the word, and the tester's first subjective evaluation of the way to recover the word, the first EEG index and the epiphany Ability-related, the first subjective evaluation includes epiphany and analysis; Obtain the first correct rate of the tester's recovery of the test words and the first proportion of the epiphany in the recovery of the words. 3. method according to claim 2, is characterized in that, according to the English word database, the tester is carried out epiphany ability detection, obtains the first detection parameter, comprising: According to the tester's age and education, the English word database for detecting the tester's epiphany ability is determined from the English word database of different difficulty levels. 4. method according to claim 2 or 3, is characterized in that, according to the English word database, the tester is carried out epiphany ability detection, obtains the first detection parameter, comprising: After the epiphany ability test, obtain the tester's recognition result of the test word; The identification result is identification failure, and the first EEG index, the first reaction time and the first subjective evaluation of the test word are eliminated; The first correct rate and the first proportion are obtained according to the eliminated data. 5. The method according to any one of claims 1 to 3, wherein the second detection parameter comprises a second EEG index, a second reaction time, a second subjective evaluation, a second accuracy rate and an epiphany the second proportion of Test the tester's epiphany ability according to the graph database, and obtain the second test parameters, including: determining a test image for capability detection according to the graphic database, the graphic database comprising a plurality of images, and the images are composed of a plurality of basic graphics; outputting the test image after disturbing the position of the basic graphics to the tester; Obtain the tester's second EEG index in the process of restoring the test image, the second reaction time for restoring the test image, and the tester's second subjective evaluation of the way to restore the test image, the second EEG The indicator is related to the ability of epiphany, and the second subjective evaluation includes epiphany and analysis; Obtain the second correct rate of the tester in restoring the test image and the second proportion of epiphany in the way of restoring words. 6. The method according to any one of claims 1 to 3, wherein, according to the first detection parameter and the second detection parameter, the tester's first epiphany evaluation information and second Epiphany assessment information, including: Calculate the first detection parameter, the parameter of the first epiphany upper limit, and the parameter of the first epiphany lower limit according to the first detection parameter, the parameter of the first epiphany upper limit, and the parameter of the first epiphany lower limit The relative Euclidean distance between the two, the first epiphany evaluation information of the tester is determined according to the relative Euclidean distance; Calculate the second detection parameter, the parameter of the second epiphany upper limit, and the parameter of the second epiphany lower limit according to the second detection parameter, the parameter of the second epiphany upper limit, and the parameter of the second epiphany lower limit The relative Euclidean distance between them is determined according to the relative Euclidean distance. The tester's second epiphany evaluation information is determined. 7. The method according to any one of claims 1 to 3, wherein, according to the first detection parameter and the second detection parameter, the tester's first epiphany evaluation information and second Epiphany assessment information, including: Clustering the first detection parameters and the second detection parameters of the multiple testers respectively to obtain multiple first sets and multiple second sets; According to the cluster centers of the first set, the parameters of the upper limit of the first epiphany, the parameters of the lower limit of the first epiphany, the cluster centers of the first set and the parameters of the upper limit of the first epiphany are calculated. The relative Euclidean distance between the parameters of the lower limit of comprehension, according to the relative Euclidean distance, determine the first epiphany evaluation information of the testers in the first set; According to the cluster centers of the second set, the parameters of the upper limit of the second epiphany, the parameters of the lower limit of the second epiphany, the cluster centers of the second set and the parameters of the upper limit of the second epiphany are calculated. The relative Euclidean distance between the two parameters of the lower limit of epiphany, and the second epiphany evaluation information of the testers in the second set is determined according to the relative Euclidean distance. 8. An epiphany ability assessment device, characterized in that, comprising: The first detection module is used to perform epiphany ability detection on the tester according to the English word database, and obtain the first detection parameter; A second detection module, configured to perform epiphany ability detection on the tester according to the graph database, and obtain a second detection parameter, wherein the first detection parameter and the second detection parameter are associated with the epiphany ability; An evaluation module, configured to obtain first epiphany evaluation information and second epiphany evaluation information of the tester according to the first detection parameter and the second detection parameter, respectively. 9. An epiphany ability assessment device, comprising: a processor and a memory; The processor is connected to a memory, wherein the memory is used for storing a program code, and the processor is used for calling the program code to execute the insight ability evaluation method according to any one of claims 1-7. 10. A computer storage medium, characterized in that the computer storage medium stores a computer program, the computer program comprises program instructions, and the program instructions, when executed by a processor, execute any one of claims 1-7. Insights assessment method described in item.

Images