KR20100098277A - Method for judging word proficiency - Google Patents

Abstract

PURPOSE: A method for judging word proficiency is provided to classify words through difficulty analysis of words into levels, thereby measuring a word proficiency level of a leaner using the classified words. CONSTITUTION: Words are classified and saved based on each level according to difficulty. It is determined whether a word level of a leaner is saved(S20). If the word level of the leaner exists, test words are extracted among words belonging to the word level. A test problem is generated(S50). The test problem is provided to the learner. A right answer rate is calculated using the test result of the leaner. The calculated answer rate is compared with reference answer rates, the level of the leaner is determined(S70).

Description

How to detect word skills {METHOD FOR JUDGING WORD PROFICIENCY}

The present invention relates to a method for detecting a word ability, and to classify and store words for learning at a plurality of levels (ie, difficulty levels) through analysis of difficulty of words to induce immersive learning, and using the classified stored words. The present invention relates to a method for detecting word proficiency that can measure a student's word proficiency level.

Conventional English learning level is generally measured from the results of the test, such as TOEIC and TOEFL. In other words, it is a method of evaluating the relative examinee's ability from all the examinees who have taken the test from the score statistics of all examinees who have taken the same test.

However, the test as described above has a limitation in evaluating the ability of the limb multiple choice, it is not easy to check the connection of meaning and meaning, there was a problem that can not objectively measure the examinee's word level.

Knowing the current level leads to basic motivation and feedback in all learning, but vocabulary, which is an important factor in current English language learning, enables learners to directly grasp the achievement or level of the word despite the various tests. There was a problem that can not be objectively detected the learner's vocabulary.

In the case of a book form of a word book conventionally used to memorize a word, a known word and a unknown word are presented together, and a sorting operation is required, and the electronic dictionary form also has the same problem.

In addition, the word history function in the portable electronic dictionary has a disadvantage that the learner's labor productivity is lower than that of the present invention because the learner goes through a typing or a text input process.

In the case of an electronic dictionary in a computer application, a word that is unknown in the text can be searched through a hyperlink function, but the current word level is not indicated by the objective dls index, so a sentence or phrase that can be understood in the reading comprehension ability ( Because there is no methodology or device to classify articles or to know the current level, learners have no choice but to study sentences based on their senses.

Most of existing word detection methods are based on the progress of the comprehensive procedural learning theory of leveling. Therefore, it was difficult for the learner to grasp the learner's current vocabulary, such as entering his or her level.

However, there is a drawback in not being able to perform smooth learning when the word ability of the correct learner is not understood. In other words, the adaptability and learning ability of learning varies according to the learner's learning ability and the difficulty of words. For example, if a word of difficulty is provided to a learner with low learning ability, the learner will be indifferent. In addition, when a word having a low difficulty is provided to a learner having excellent learning ability, the learner may be bored.

Therefore, in order for the learner to be interested in learning, it is necessary to accurately measure the learner's learning ability and to classify the difficulty of the word accurately to provide a word corresponding to the difficulty according to the learner's current learning ability.

Accordingly, an object of the present invention is to provide a method for detecting word proficiency that can classify words according to difficulty and diagnose the learner's ability using the classified words to easily verify the learner's word ability in a short time.

The present invention also provides a method of detecting word proficiency that can be used for learning by storing learner's word test history, extracting learner statistics, and checking learner's vocabulary.

In order to achieve the above object, the step of classifying the plurality of words according to the level of the word according to the difficulty of the present invention stored in the database, and determining whether or not the word level of the learner is stored in the database; Determining the word level of the learner by performing an initial learner word level determination operation when there is no word level of the learner, and if the word level of the learner is determined, the word level of the learner corresponds to the word level of the learner. Extracting a test word by sampling among words included in a word level in a database to generate a test test problem, providing the generated test test problem to the learner, and calculating a correct answer rate using the test result of the learner And compare the calculated correct answer rate with the level reference correct rates. It provides a method for detecting word skills comprising the step of determining the level of the female learner.

The determining the word level of the learner by performing the initial learner word level determining operation may include: generating a level test problem by sampling words corresponding to each representative index for each level of the database; Providing a learner with the sampled level test problem; Calculating a correct answer rate of the learner for each level; And determining whether the correct answer rate corresponds to the reference correct rate from the lowest level and setting a level having a correct answer rate smaller than the reference correct rate as the minimum word level of the learner.

The determining of the word level of the learner by performing the initial learner word level determination operation may include generating a lowest level test problem by sampling a word corresponding to a representative index at the lowest word level of the database and providing the same to the learner. Making; Calculating a learner's correct answer rate for the lowest level test problem; Determining whether the learner's correct answer rate is greater than or equal to a reference correct rate; Determining a lowest word level as a learner's word level when the correct answer rate is less than or equal to a reference correct rate; If the correct answer rate is equal to or greater than a reference correct rate, generating a high level test problem by providing a high level test problem by sampling a high level word; Calculating a correct answer rate of the learner for the high level test problem; Determining the current level as the word level of the learner when the correct answer rate of the learner is less than or equal to the reference correct rate, and generating and providing a high level test problem by sampling the upper level word when the learner's correct rate is greater than or equal to the reference correct rate. It is possible to include the step of performing again.

The level reference correct rate has a lower reference level and a higher reference level, and if the learner's correct answer rate is lower than or equal to the lower reference level, downgrade the learner level. If the correct answer rate is higher than or equal to the lower reference level and lower than the upper reference level, the learner level. It is possible to upgrade the learner level when the correct answer rate is higher than the upper reference level.

The method may further include estimating the number of words known to the learner using Equation 1 below, but it is effective to estimate the total number of words of the learner by assigning a weight of 1.5 to 1.7 to the result of Equation 1 below. .

<Equation 1>

는 현재 레벨 이전 레벨의 단어수와 상위 설정 기준치를 곱한 값의 합, P는 상위 설정 기준치, N_L은 현재 레벨의 단어수, G는 현재 레벨의 정답률임.Where N is the total number of words the learner knows,

Is the sum of the number of words from the level before the current level multiplied by the higher setting criterion, P is the higher setting criterion, N _L is the number of words in the current level, and G is the correct answer rate of the current level.

As described above, the word proficiency detecting method according to the present invention is very effective in improving the language skills because it can detect the word proficiency of the learner easily and quickly. In addition, by storing the test history of the learner to grasp the vocabulary statistics, there is an excellent effect that can determine at a glance whether or not to improve the skills. The present invention is more efficient than the existing method of testing the word level and determining the current level of accuracy and the process of extracting the word of the level to be memorized.

Hereinafter, with reference to the accompanying drawings will be described an embodiment of the present invention in more detail. It will be apparent to those skilled in the art that the present invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, It is provided to let you know. Like numbers refer to like elements in the figures.

1 is a flow chart for explaining a word proficiency detection method according to an embodiment of the present invention.

2 is a flowchart illustrating an initial learner word level determination operation, according to an exemplary embodiment.

3 is a flowchart illustrating an initial learner word level determination operation according to a modified example of the embodiment.

First, as shown in FIG. 1, a learner loads a program for detecting a word ability (S10).

In this case, the learner may access the server connected to the learner terminal through wired or wireless communication, go through a login process for learner authentication, and then load the program.

In addition, the present invention is not limited thereto, and a program embedded in a predetermined electronic device may be activated.

In the present embodiment, before loading the program, a plurality of words are classified into levels according to the difficulty of the words and stored in the database.

Here, the word classification is based on the first word classification based on the words used by age. It can use the age-based word criteria specified by the country where the word is the native language. Alternatively, words designated in the domestic curriculum, for example, a junior high school test or a high school test word, may be used as a reference word for age.

For example, in the United States, primary word classification may be performed using the word classification provided in the ESL process, or primary word classification may be performed using domestic test words or TOEIC and TOEFL words. In addition, the second word classification is performed based on the sentence length (ie, the number of words used in the sentence).

This is used for short sentences in the case of easy difficulty, so second classification is performed.

That is, a word used in a sentence having a short sentence length (that is, a small number of words used in the sentence) is a word having an easy difficulty, and in the opposite case, the difficulty is gradually difficult. This is because, in language learning, the younger the sentence, the shorter the sentence length, and the more the sentence is, the longer the sentence length becomes.

In this way, by classifying words through the first and second order, the word level according to the difficulty of the word can be set accurately.

For example, even if a single word is located at the first word level through the first word classification, when the single word is used in a sentence composed of at least six words, the level of the single word is defined as the second word level. Raise to and save. The difficulty setting of the words can enhance the interest of the learner.

The classification of word level is carried out for native speakers' curriculum and curriculum recommendation books. At this time, extract nouns around the nouns. In addition, it is possible to use a fry readability fomula regarding the recognition rate of native speakers for the sentence length data.

Next, learner identification is performed, and it is determined whether or not the word level of the learner is stored in the database (S20).

In this case, when there is no stored word level of the learner, an initial learner word level determination operation is performed (S30). In this case, as shown in FIG. 2, the initial learner word level determination operation is first performed by sampling (ie, extracting) words corresponding to each representative index for each level of the database classified by level according to the difficulty of the word. Generate a test problem (S110). The sampled level test problem is provided to the learner (S120). At this point, the learner solves the level test problem.

Here, the extraction of the word corresponding to the representative index is preferably extracted by an algorithm that is randomly extracted for each word level.

Here, it is effective to extract 5 to 30 words at each level. In this case, when extracting a word corresponding to the representative index by the number less than 5, there is a disadvantage that it is difficult to determine the level of the learner, and when extracting more than 30 words, the learner can easily feel empirical when the level test There is a problem.

Therefore, it is effective to select words within the above ranges at each level.

Next, the correct answer rate of learners for each level is calculated (S130).

Subsequently, it is determined whether the correct answer rate corresponds to the standard correct answer rate from the lower level (S140). At this time, the level that does not meet the standard correct answer rate is set as the first word level of the learner (S150). The result is then stored in the database. Here, the reference score may be a score that recognizes 80 to 90% of the provided word.

Of course, this embodiment is not limited to this, and various modifications to the initial learner word level determination operation are possible. That is, as shown in FIG. 3, first, a word corresponding to a representative index is sampled at the lowest word level to generate and provide a level test problem (S210). Calculate the correct answer rate of the learner (S220). It is determined whether the learner's correct answer rate is greater than or equal to the standard correct answer rate (S230). In this case, when the correct answer rate is lower than the reference, the lowest word level is determined as the word level of the learner (S240). On the other hand, when the learner's correct answer rate is greater than or equal to the reference correct rate, the word of the higher level is sampled to generate a level test problem and provide it (S250). Next, the correct answer rate of the learner is calculated, and it is determined whether the correct answer rate is equal to or greater than the reference correct rate (S260). As a result of the determination, if the correct answer rate is lower than the reference, the current word level is determined as the word level of the learner (S270). When the correct answer rate is greater than or equal to the reference correct rate, the word of the higher level is sampled again to generate a level test problem, and provide it (S250).

If there is a stored word level of the learner, a test word is generated by extracting a test word by sampling among the words included in the word level in the database corresponding to the word level of the learner (S40).

Subsequently, the skills test problem is provided to the learner (S50). Subsequently, a learner's input on the provided ability test problem is received (S60).

Here, the test word extraction generates a word list by extracting a test word by sampling among words corresponding to the word level of the learner, and when the word list is generated, the word list is sequentially or randomly displayed on the screen. The selected words are immediately stopped on the screen, and the unselected words are sequentially stopped and are not visible on the screen. Alternatively, the selected words may be sequentially or randomly replaced by the words in the extracted word list.

As described above, an interface for inputting an answer to the test problem is provided to the learner, and the learner inputs an answer to the test problem using an input means such as a keyboard, a keypad, a mouse, and a touch screen. The learner's answer is input by the input unit, and the input unit is connected to the touch screen, mouse, keyboard, and USB so that the learner generates electric or magnetic signals during operation and transmits and inputs them to the processing unit of the device through the USB port. Alternatively, a button interface for selecting more learners may be a component.

Here, the method of inputting the answer may be configured to check only whether the test word is known or not, and if it is known, enter a key corresponding to "0", and if not, enter a key corresponding to "X". If the learner is provided with the above-mentioned opt-in interface, the O and X can be positioned within the visual range of the interface and selected by clicking and touching, and the method of assigning a value of a specific keyboard to the O and X is selected. If the learner is provided with the multi-selection interface, the mouse or the touch screen device can be selected by placing the cursor in the visual range of a specific word while the plurality is simultaneously posted.

A single test word displayed on the screen may be sequentially displayed, and a plurality of test words may be sequentially displayed. When a plurality of words are displayed, each word includes an identification number, and the learner inputs an interface so that an answer can be input to a part corresponding to the identification number.

Subsequently, the test result data, which is the input of the provided learner, is stored in the database, the correct answer rate is calculated, and the calculated correct answer rate is compared with the level reference correct rates (S70).

In this case, when the comparison result is lower than the lower reference level, the learner level is downgraded. If the comparison result is above the lower reference level and below the upper reference level, the learner level is maintained. If the comparison result is higher than the higher reference level, the learner level is upgraded (S81, S82, S83, S84, and S85).

That is, when an answer is input from the learner as described above and the test is completed, the test answer input from the learner is stored in a database, and the correct answer rate of the test answer is checked to determine whether to downgrade, maintain, or upgrade the level.

The level reference value (%) set for each level according to the correct answer rate is stored, and the level answer value calculated from the learner test answer is compared with the level reference value (%) to determine whether to downgrade, maintain or upgrade the level.

As the level reference value, a level up criterion for upgrading and a level down criterion for downgrading may be set.

For example, if the level-up criterion for upgrading the level is 90% and the level-down criterion for the level downgrade is 40%, the learner test results downgrade to the lower level if the correct test rate is 0 to 39%. If the correct rate is 40-89%, the learner level is maintained at the current level. If the correct rate is 90% or higher, the learner level is upgraded to a higher level.

The level up criterion and the level down criterion may be set differently for each level, and may be determined in consideration of the word level and the number of words included in the level.

When the level is determined as described above, the test data which is the test result is stored in a database. Here, the test data may include information such as a student identification code, a test date, a list of known words, a list of unknown words, a student word level, and the like.

Therefore, the learner can check the stored test history and analyze the progress of improvement and achievement.

In addition, the word proficiency determination module may estimate the total number of words currently known by the learner by the following equation.

는 현재 레벨 이전 레벨의 단어수와 상위 설정 기준치를 곱한 값의 합, P는 상위 설정 기준치, N_L은 현재 레벨의 단어수, G는 현재 레벨의 정답률이다.Where N is the total number of words the learner knows,

Is the sum of the number of words before the current level multiplied by the higher setting criterion, P is the higher setting criterion, N _L is the number of words in the current level, and G is the correct answer rate of the current level.

In addition, the total number of words of the learner may be estimated by assigning a weight of 1.5 to 1.7 to the result value in consideration of the multiword, root, plural, inching, and the like.

Here, if the weight is closer to 1.5, the object has the purpose of checking the octopus level. As the weight is closer to 1.7, the objectivity of the spoken level, i.e., the language, dialect, and sociolect, is detected. Will have

Of course, if it is out of the above range it is difficult to check the octopus level or spoken level. And, the limitation to the above range is to apply the principle of linguistic mutual exclusion of linguistics.

Apparatus and system for performing the above-described word ability detection method may vary. The following describes a system for performing this word ability detection method.

4 is a system configuration diagram according to the first embodiment of the present invention.

Referring to FIG. 4, the word proficiency detection system according to the present embodiment may be provided in a network environment using an internet network, and may include a learner terminal 10 and a word proficiency detection server 20.

Here, the learner terminal 10 may be a key, such as a desktop, a notebook, a PDA, a PMP, a mobile communication terminal, and any terminal capable of accessing the Internet.

The learner terminal 10 includes a client 110 for accessing the word proficiency detecting server, an application 120 for providing an interface for detecting the word proficiency, and an input unit 130 for inputting key data for the word proficiency test. And an output unit 140 for outputting video and audio data for detecting word proficiency.

And the word proficiency detection server 20 is a UI unit 210 that allows the access of the learner terminal and provides a learner interface for the test, the difficulty of the word (age of the word is mainly used, length of the sentence used the word) According to the word level is divided into a plurality of word levels stored in the database 220, the level determiner 230 for determining the initial learner level using the words stored in the database 220, and corresponding to the learner level And a word ability determining unit 240 for determining a word ability of the learner using the words in the word level.

In this embodiment, a separate word level separation module 250 is provided. The word level classification module 250 classifies words according to the difficulty of the words and stores the words in the first to seventh word level spaces.

The word level classification module 250 performs the first word classification based on the words used by age. It can use the age-based word criteria specified by the country where the word is the native language. Alternatively, words designated in the domestic curriculum, for example, a junior high school test or a high school test word, may be used as a reference word for age.

For example, in the United States, primary word classification may be performed using the word classification provided in the ESL process, or primary word classification may be performed using domestic test words or TOEIC and TOEFL words.

The level determiner 230 according to the present exemplary embodiment first samples a word in the database 220 to determine an initial learner level.

To this end, the level determination unit 230 includes a level test word extraction module 231 and a level determination module 232.

The level test word extraction module 231 samples each of the plurality of word levels of the database 220 and extracts words corresponding to the representative index for each word level.

The level test word extraction module 231 extracts a level test word by sampling a word from the lowest word level to the highest word level stored in the database 220 in stages.

The level determining module 232 stores the learner's input result (ie, input result of recognition or not) for the test word sampled as the representative index for each word level in the database 220 and according to the learner's input result. Determine the level of.

The level determination module 232 calculates a score for each level by synthesizing the learner's input result for the test word sampled as the representative index for each word level. Then, it is determined whether the score calculated from the lower level is higher or lower than the reference score. As a result of the determination, when the level is lower than the reference score, the level becomes the learner's level. In this case, the reference score may be a score that recognizes 80 to 90% of the provided word.

The word skills determining unit 240 includes a skills test word extraction module 241 and a word skills determination module 242.

The ability test word extraction module 241 provides a test problem by extracting the ability test word through sampling of words within a word level corresponding to the learner level among the words stored in the database 220. Here, the ability test word may be extracted by an algorithm for randomly extracting words included in the level.

The word proficiency determination module 242 stores the result input from the learner for the provided test problem in the database 220 and determines the learner's word proficiency from the result.

In addition, the word proficiency determination module 242 stores the learner's input result for the sampled proficiency test words in the database 220, and if the correct answer rate exceeds a set level up criterion, upgrades the learner level by one step, and the correct answer rate is If the level is not met, the student level is downgraded one level. If the correct answer rate is between the level up and the level down criteria, the current learner level is maintained.

Here, the level up criterion and the level down criterion are set to a percentage of percent correct (%) and determine the criterion in consideration of the level and difficulty of the word. For example, you can set the level up criterion to 90% and the level down criterion to 40%, in which case the level is downgraded if the percentage of correct answers is between 0 and 40%, and the current level is maintained between 40 and 90%. If it is 90% or higher, the level is upgraded.

In addition, the present embodiment is not limited to the above description and can be changed to various embodiments. That is, as mentioned above, the system of the present embodiment may be provided embedded in a single terminal or device. Description of the overlapping description of the description of the first embodiment described above will be omitted. Also, the technique described in the second embodiment can be applied to the first embodiment.

5 is a system configuration diagram according to a second embodiment of the present invention.

Referring to FIG. 5, the word proficiency detection system according to the present embodiment is provided when the electronic device 300 is embedded in the electronic device 300. The input unit 310 receives key input from a learner and generates key data, and the difficulty level of the word. Accordingly, each word is classified by level and stored in the database 320 and the words of each level stored in the database 320 to provide a level test problem, and the initial learner level from the level test result input from the learner. A level determining unit 330 for determining a word level, a word within a word level corresponding to the level of the learner, to provide a skills test problem, and to determine the word ability of the learner based on the test result input from the learner. Unit 340, an output unit 360 for outputting audio and video signals to provide an interface for testing, and an entire unit It may be configured to include a control unit 370 for controlling the device. In addition, as described in the above embodiment, the word level classification module 380 may further include a word level classification.

Here, the word proficiency detection system according to the present embodiment may be implemented at a firmware, an operating system, and an application level embedded in an electronic device. The first embodiment described above is similar in structure to the word proficiency detection system except that the system manages learners on a network in a server, and the second embodiment is embedded in an electronic device and managed by learners. Therefore, the configuration of the database 320, the level determining unit 330, the word ability determining unit 340 and the like is similar to the first embodiment described above.

On the other hand, the present invention is not limited to the above-described specific embodiments, anyone of ordinary skill in the art belonging to the present invention without departing from the gist of the invention claimed in the claims, the order of the processing procedure Various changes may be made, such as changing the type of hardware on which the component is to be located.

 1 is a flow chart for explaining a word skills detection method according to an embodiment of the present invention.

2 is a flowchart illustrating an initial learner word level determination operation according to an exemplary embodiment.

3 is a flowchart illustrating an initial learner word level determination operation according to a variation of an embodiment.

4 is a system configuration diagram according to the first embodiment of the present invention.

5 is a system configuration diagram according to a second embodiment of the present invention.

<Explanation of symbols for the main parts of the drawings>

10: learner terminal 20: detection server

220, 320: database 230, 330: level determination unit

231, 331: level test word extraction module

232, 332: level determination module 240, 340: word ability determination unit

241, 341: skills test word extraction module

242, 342: word ability determination module 250, 380: word level separation module

Claims (5)

Classifying the plurality of words by level according to the difficulty of the words and storing the plurality of words in a database; Determining whether a word level of a learner is stored in the database; Determining a word level of the learner by performing an initial learner word level determination operation when there is no word level of the learner as a result of the determination; If there is a word level of the learner as a result of the determination, extracting a test word from a word included in the word level in the database corresponding to the word level of the learner to generate a test test problem; Providing the learner with the generated skills test problem; And Calculating a correct answer rate by using the test result of the learner, and comparing the calculated correct answer rate with the level reference correct answer rates to determine a learner's level. The method of claim 1, wherein the determining of the word level of the learner by performing the initial learner word level determination operation comprises: Generating a level test problem by sampling words corresponding to each representative index for each level of the database; Providing a learner with the sampled level test problem; Calculating a correct answer rate of the learner for each level; And And determining a level having a correct answer rate smaller than the reference correct rate as the learner's lowest word level by determining whether the correct answer rate corresponds to the reference correct rate from the lowest level. The method of claim 1, wherein the determining of the word level of the learner by performing the initial learner word level determination operation comprises: Sampling a word corresponding to a representative index at the lowest word level of the database to generate a lowest level test problem and providing the same to a learner; Calculating a student's correct answer rate for the lowest level test problem; Determining whether the learner's correct answer rate is greater than or equal to a reference correct rate; Determining a lowest word level as a learner's word level when the correct answer rate is less than or equal to a reference correct rate; If the correct answer rate is equal to or greater than a reference correct rate, generating a high level test problem by providing a high level test problem by sampling a high level word; And Calculating a correct answer rate of the learner for the high level test problem; Determining the current level as the word level of the learner when the correct answer rate of the learner is less than or equal to the reference correct rate, and generating and providing a high level test problem by sampling the upper level word when the learner's correct rate is greater than or equal to the reference correct rate. A word proficiency detection method comprising the step of performing again. The method of claim 1, The level reference correct rate has a lower reference level and a higher reference level, If the correct answer rate of the learner is lower than the lower reference level, the learner level is downgraded, and if the correct answer rate is higher than the lower reference level and lower than the upper reference level, the learner level is maintained. How to detect word skills to upgrade. The method of claim 1, The method may further include estimating the number of words known by the learner using Equation 1 below, by assigning a weight of 1.5 to 1.7 to the result of Equation 1 to estimate the total number of words of the learner. How to detect the word skills. <Equation 1>

Where N is the total number of words the learner knows,

Is the sum of the number of words from the level before the current level multiplied by the higher setting criterion, P is the higher setting criterion, N _L is the number of words in the current level, and G is the correct answer rate of the current level.

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