KR102050266B1 - Server, method and computer program for providing english study service - Google Patents

Abstract

An English learning providing server for providing an English learning service may include an English data receiving part for receiving English data; a vocabulary index analysis part for analyzing a vocabulary index for each of a plurality of vocabularies included in the English data; an English data analysis part for analyzing the difficulty of the English data by performing an analysis based on at least one of the vocabulary index, grammar index and readability index for the English data; a vocabulary providing part for classifying a plurality of vocabularies by a predetermined vocabulary level based on the vocabulary index for each of the analyzed vocabularies, and providing the plurality of vocabularies classified for each vocabulary level to a learner terminal; and an English learning providing part for providing an English leaning service based on the difficulty of the analyzed English data and the vocabulary level selected by the learner terminal.

Description

SERVER, METHOD AND COMPUTER PROGRAM FOR PROVIDING ENGLISH STUDY SERVICE}

The present invention relates to a server, a method and a computer program for providing an English learning service.

In the existing English learning content, most of the learning methods are provided in such a way that learners voluntarily learn by providing a workbook and a wordbook.

When a learner encounters words that are difficult to memorize, they not only have low interest, but also have low achievement because of the difficulty of memorization, which leads to a decrease in motivation to learn.

On the other hand, the index for the conventional English fingerprint is used to determine the learner's level of English learning for the learner's English education, it is an indicator indicating the difficulty of the English fingerprint.

Currently, there are various indices of English difficulty in the English education market, but these indices have a simple standard for classifying difficulty, which makes it difficult to accurately measure English difficulty and is not suitable for the Korean educational environment. .

Korean Laid-Open Patent Publication No. 2017-0041387 (published April 17, 2017)

The present invention is to solve the above-described problems of the prior art, and analyzes the difficulty of the English data based on the lexical index, grammar index and readability index for the received English data, the difficulty of the analyzed English data and the learner terminal An English learning service is provided to a learner terminal based on the selected vocabulary level. In addition, the present invention is to provide a learner terminal by classifying a plurality of vocabulary for each preset vocabulary level based on the analyzed vocabulary index. However, the technical problem to be achieved by the present embodiment is not limited to the technical problems as described above, and other technical problems may exist.

Technical means for achieving the above-described technical problem, English learning providing server for providing an English learning service according to the first aspect of the present invention English language receiving unit for receiving English data; A vocabulary index analyzer for analyzing a vocabulary index for each of a plurality of vocabularies included in the English data; An English data analyzer configured to analyze the difficulty of the English data by performing an analysis based on at least one of the lexical index, the grammar index, and the readability index of the English data; A vocabulary providing unit classifying the plurality of vocabularies by a predetermined vocabulary level based on the vocabulary indexes of the analyzed vocabularies, and providing a plurality of vocabularies classified by the vocabulary levels to learner terminals; And an English language learning provider for providing the English language learning service based on the difficulty of the analyzed English data and the vocabulary level selected by the learner terminal.

According to a second aspect of the present invention, a method for providing an English learning service performed by an English learning providing server includes: receiving English data; Analyzing a vocabulary index for each of a plurality of vocabularies included in the English data; Analyzing the difficulty of the English data by performing an analysis based on at least one of the lexical index, the grammar index, and the readability index of the English data; Classifying the plurality of vocabularies by a predetermined vocabulary level based on a vocabulary index for each of the analyzed vocabularies and providing a plurality of vocabularies classified by the vocabulary levels to a learner terminal; And providing the English learning service based on the difficulty of the analyzed English data and the lexical level selected by the learner terminal.

A computer program stored in a medium containing a sequence of instructions for providing an English language learning service according to a third aspect of the present invention, when executed by a computing device, receives English data and stores each of a plurality of vocabularies contained in the English data. Analyze the lexical index for the English data, perform an analysis based on at least one of the lexical index, the grammar index, and the readability index for the English data to analyze the difficulty of the English data, and the lexical index for each of the analyzed plurality of vocabularies. Classify the plurality of vocabularies by predetermined vocabulary levels based on the plurality of vocabulary levels, provide the plurality of vocabularies classified by the vocabulary levels to learner terminals, and based on the difficulty of the analyzed English data and the vocabulary levels selected by the learner terminals. A sequence of instructions to provide the English learning service Can be included.

The above-mentioned means for solving the problems are merely exemplary, and should not be construed to limit the present invention. In addition to the exemplary embodiments described above, there may be additional embodiments described in the drawings and detailed description of the invention.

According to any one of the above problem solving means of the present invention, the difficulty of the English data based on the lexical index, grammar index and readability index for the received English data, and analyzed by the difficulty of the English data and the learner terminal The English learning service may be provided to the learner terminal based on the selected vocabulary level. In addition, the present invention may classify a plurality of vocabularies for each preset vocabulary level based on the analyzed vocabulary index and provide them to the learner terminal.

In this way, the present invention provides an English learning service suitable for the level of the learner, thereby inducing the learner's interest in learning English, thereby improving learning motivation.

1 is a block diagram of an English learning providing system according to an embodiment of the present invention.
2 is a block diagram of an English learning providing server shown in FIG. 1 according to an embodiment of the present invention.
3A to 3G are diagrams for describing a method of providing English learning according to an embodiment of the present invention.
4A to 4B are diagrams for describing an English learning providing method according to another exemplary embodiment of the present invention.
5 is a flowchart illustrating a method of providing an English learning service according to an embodiment of the present invention.

DETAILED DESCRIPTION Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art may easily implement the present invention. As those skilled in the art would realize, the described embodiments may be modified in various different ways, all without departing from the spirit or scope of the present invention. In the drawings, parts irrelevant to the description are omitted in order to clearly describe the present invention, and like reference numerals designate like parts throughout the specification.

Throughout the specification, when a part is "connected" to another part, this includes not only "directly connected" but also "electrically connected" with another element in between. . In addition, when a part is said to "include" a certain component, which means that it may further include other components, except to exclude other components unless otherwise stated.

In the present specification, the term 'unit' includes a unit realized by hardware, a unit realized by software, and a unit realized by both. In addition, one unit may be realized using two or more pieces of hardware, and two or more units may be realized by one piece of hardware.

Some of the operations or functions described as being performed by a terminal or a device in the present specification may instead be performed in a server connected to the terminal or device. Similarly, some of the operations or functions described as being performed by the server may be performed by a terminal or a device connected to the server.

Hereinafter, with reference to the accompanying configuration diagram or processing flow chart, it will be described in detail for the practice of the present invention.

1 is a block diagram of an English learning providing system according to an embodiment of the present invention. Referring to FIG. 1, the English learning providing system may include an English learning providing server 100, a learner terminal 110, and an instructor terminal 120. However, since the English learning providing system of FIG. 1 is only one embodiment of the present invention, the present invention is not limitedly interpreted through FIG. 1 and may be configured differently from FIG. 1 according to various embodiments of the present invention. .

In general, each component of the English learning providing system of FIG. 1 is connected through a network (not shown). A network refers to a connection structure capable of exchanging information between nodes such as terminals and servers, and includes a local area network (LAN), a wide area network (WAN), and the Internet (WWW: World). Wide Web), wired / wireless data communication network, telephone network, wired / wireless television communication network, and the like. Examples of wireless data networks include 3G, 4G, 5G, 3rd Generation Partnership Project (3GPP), Long Term Evolution (LTE), World Interoperability for Microwave Access (WIMAX), Wi-Fi, Bluetooth communications, Infrared communications, Ultrasound Communication, visible light communication (VLC), liFi (LiFi), and the like, but are not limited thereto.

The English learning providing server 100 may receive English data for the learner to learn from the learner terminal 110 or the instructor terminal 120. Here, the English data may include, for example, an English fingerprint that a learner intends to learn or an English fingerprint that an instructor wants to learn to the learner on a web site (eg, the New York Times) or a web document.

The English learning providing server 100 may analyze a lexical index for each of a plurality of vocabularies included in the English data. For example, the English learning providing server 100 may analyze a lexical index for each of a plurality of vocabularies included in the English data based on vocabulary related data, textbook vocabulary list, vocabulary frequency and importance of each test. .

The English learning providing server 100 may analyze the difficulty of the English data by performing an analysis (eg, multiple regression analysis) based on at least one of a lexical index, a grammar index, and a readability index on the received English data. Here, the grammar index may be calculated based on a plurality of grammar elements (or preset grammar criteria). The readability index is an indicator of how easily a learner can read an English sentence. For example, the readability index may be calculated based on the presence or absence of a signal vocabulary, the sentence length, and the like.

The English learning providing server 100 classifies a plurality of vocabularies by a predetermined vocabulary level based on a vocabulary index for each of the plurality of vocabularies analyzed from the received English data, and classifies the plurality of vocabularies classified by vocabulary levels into a learner terminal ( 110 or the instructor terminal 120 may be provided. For example, the English learning providing server 100 displays the vocabulary level information for each vocabulary to the learner terminal 110 or the instructor terminal 120 by displaying the color of the vocabulary differently corresponding to each vocabulary level for each preset vocabulary level. Can provide

The English learning providing server 100 may provide an English learning service to the learner terminal 110 based on the difficulty of the analyzed English data and the vocabulary level selected by the learner terminal 110. For example, the English learning providing server 100 may generate and provide a plurality of English example sentences to the learner terminal 110 based on a structure of a sentence similar to the difficulty of English data. For example, the English learning providing server 100 generates an example sentence having a sentence structure similar to that of English data using a plurality of vocabulary corresponding to the vocabulary level selected by the learner terminal 110 to learner terminal 110. It can also be provided to.

Hereinafter, the operation of each component of the English learning providing system of FIG. 1 will be described in more detail.

2 is a block diagram of the English learning providing server 100 shown in FIG. 1 according to an embodiment of the present invention.

Referring to FIG. 2, the English learning providing server 100 includes an English data receiving unit 201, a lexical index analyzer 203, an English data analyzing unit 205, a vocabulary providing unit 207, and an English learning providing unit 209. ), A lexical level option providing unit 211, a lexical level information receiving unit 213, a question type selection unit 215, a learner level determining unit 217, a code generating unit 219, and a code transmitting unit 221. can do. However, the English learning providing server 100 shown in FIG. 2 is just one implementation example of the present invention, and various modifications are possible based on the components shown in FIG. 2.

Hereinafter, a description will be given with reference to FIGS. 3A to 4B together with FIG. 2.

The English data receiver 201 may receive English data from the learner terminal 110 or the instructor terminal 120. For example, referring to FIG. 3A, the English terminal 301 or the English data 303 provided in the English web document may receive some or all of the English data that the learner wants to learn from the learner terminal 110. have.

As another example, the English data receiver 201 may receive a document file including the English data 303 that the instructor wants to learn from a plurality of learners from the instructor terminal 120. Here, the learner terminal 110 or the instructor terminal 120 may copy the English data 303 for English learning of the learner into a plurality of methods (eg, copying the English data to the English data document interface of the English learning providing site 305). Inputting or uploading English data to the corresponding English data document interface), and the like, may be transmitted to the English learning providing server 100 through the English learning providing site 305.

The English data receiver 201 may perform spell correction on the received English data. Here, the spelling correction may be processed through one of a plurality of spelling correction methods. The plurality of spelling correction methods may include a typing correction method, a white space only correction method, and an inference correction method.

The typing correction method is a method of correcting spelling of a plurality of vocabularies included in the English data after considering the English data received from the learner terminal 110 or the instructor terminal 120 as a sentence written by a person. For example, any vocabulary not retrieved through the English vocabulary database can potentially be corrected using a deep-learing model because it has a potential typo.

The white space correction method regards English data received from the learner terminal 110 or the instructor terminal 120 as a sentence obtained through crawling, copy-pasting, etc., and corrects spelling of a plurality of vocabulary words included in the English data. That's the way it is. Here, the sentences obtained by crawling, copy-pasting, etc. are usually misspelled in the vocabulary itself, but there are many cases in which blank symbols such as spaces are incorrectly written. The white space correction method can remove unnecessary white space by using an algorithm for correcting white space in a sentence obtained through crawling, copy-pasting, and the like.

The reasoning correction method is a method of determining whether the English data received from the learner terminal 110 or the instructor terminal 120 is corrected by spelling correction of a typing correction method or a white space correction method. Such a reasoning correction method may determine typographical modeling by estimating probabilistic inference modeling by identifying typos of vocabulary input by a learner or an instructor, and then determine an appropriate spelling correction method.

The lexical index analyzer 203 may analyze lexical indexes for each of the plurality of vocabularies included in the received English data. For example, the lexical index analysis unit 203, each of the plurality of vocabulary included in the English data, the frequency of questions and the plurality of corpus (Corpus: language) that are asked in the actual test (for example, TOEIC test, civil service test, college entrance test, etc.) Vocabulary indexes for each vocabulary included in the English data can be calculated by combining the language data).

Or, the lexical index analysis unit 203 is a vocabulary ranking according to the frequency of use of the vocabulary calculated through representative corpus (eg, COCA / BNC, etc.) and electronic document big data (eg, English novels, English current magazine, news, etc.) Based on the lexical index for each of the plurality of vocabulary included in the English data can be calculated. Alternatively, the lexical index analysis unit 203 may include vocabulary (eg, beautiful and beautifully) that have similar meanings or only parts of speech based on an English affix defined in the received English data, and vocabulary having a grammatical function (eg, The vocabulary index for each vocabulary may be calculated after grouping the vocabulary except for to, the, in, on, etc.) into a plurality of groups based on the frequency of the test, the frequency of use, and the level of difficulty.

On the other hand, the lexical index may vary depending on the environment using the vocabulary. That is, the lexical index in an environment where a bilingual language is used and the lexical index in an environment where a second foreign language is acquired can be differentiated. For example, the 'sirloin' vocabulary is a basic vocabulary for US elementary school students, the vocabulary is used frequently in English-speaking countries, and the learning priority will be measured as a high level. The index can be calculated low. However, the candidates who are preparing for the SAT in Korea do not have a high learning priority for the 'sirloin' vocabulary, and because it is a difficult vocabulary, the vocabulary index for the 'sirloin' vocabulary may be high.

The English data analyzer 205 may analyze the difficulty of the English data by performing a regression analysis based on the lexical index, the grammar index, and the readability index of the English data. Difficulty of English data can be calculated through [Equation 1].

[Equation 1]

Difficulty of English Data = Vocabulary Index + Grammar Index + Readability Index + Constant

Here, the grammar index for the English data is calculated based on a plurality of grammar elements (or preset grammar criteria) and has a direct relationship with the difficulty of the grammar.

For example, the grammar index may be calculated as a numerical average value for the grammar elements used in each sentence of the English data, based on the numerical values assigned to the plurality of preset grammar elements. For example, when comparing a first sentence connected with conjunctions such as and, or, and a second sentence connected with a mixture of infinitives and relative pronouns, the grammar index of the second sentence is higher than that of the first sentence.

As another example, a sentence containing a short vocabulary (eg, ain't or cuz) may increase in grammar index because it is difficult to find in textbooks or SAT tests. Alternatively, when a plurality of grammar elements are contained in one English sentence, the grammar index is increased. For example, even if the English sentence is a short sentence composed of easy vocabulary, the grammar index is increased if the sentence is composed of various grammatical elements. Also, if the English sentence has a structure having a plurality of clauses (eg, an adverb clause, a relative clause) or a phrase (eg, to indefinite phrase, injection phrase, same name phrase, etc.), the grammar index can be calculated high.

Here, the readability index for English data is an index of how easily a learner can read a sentence, and is calculated based on whether a signal vocabulary or a summary sentence exists in the English data, a sentence length, or the like. It is directly proportional to the difficulty of English data.

For example, even if the vocabulary and grammar structure used in each sentence constituting the English data is high, each sentence presents an example in a simple enumeration, and if there is a summary sentence, the readability index for the English data is low. Can be. Conversely, even if each sentence is a simple sequence, it is difficult to determine how many cases are present if the signal vocabulary (eg one, two, three, etc.) does not exist. have.

The vocabulary providing unit 207 may provide the learner terminal 110 with information about each of the plurality of vocabularies based on the vocabulary indexes for each of the analyzed plurality of vocabularies (a plurality of vocabularies included in the English data). For example, referring to FIG. 3B, when the analysis of the English data 303 received from the learner terminal 110 is completed, the vocabulary providing unit 207 has a difficulty level for each vocabulary included in the English data 303. Vocabulary information 307 including / meaning / phonetic symbol / test frequency / part-of-speech may be provided to the learner terminal 110 through the English learning providing site 305.

The vocabulary providing unit 207 may classify a plurality of vocabularies by a predetermined vocabulary level based on a vocabulary index for each of the analyzed vocabularies, and provide the learner terminal 110 with a plurality of vocabularies classified by vocabulary levels. have.

For example, referring to FIGS. 3B and 3C, when the learner terminal 110 selects the learning mode 309 displayed on the screen of the English learning providing site 305, the vocabulary providing unit 207 displays the English data 303. The difficulty information of each vocabulary can be displayed by changing the color for each of the preset vocabulary levels for the plurality of vocabularies appearing in the vocabulary.

For example, the vocabulary providing unit 207 displays the vocabulary corresponding to the elementary level in the first color (for example, yellow), and the vocabulary corresponding to the level 2 to 3 among the second color (for example, the green). And the vocabulary corresponding to the high level 2 to the high level 3 may be displayed in a third color (eg, red). In addition, the vocabulary providing unit 207 may provide the learner terminal 110 with information 311 about the number of vocabularies and the frequency of occurrence of the vocabulary for each vocabulary level based on a plurality of vocabularies classified for each vocabulary level.

The vocabulary level option providing unit 211 may provide the learner terminal 110 with an interface for selecting at least one of a plurality of preset vocabulary levels.

The vocabulary level information receiver 213 may receive information about the vocabulary level selected by the learner terminal 110 from the learner terminal 110 through an interface.

For example, referring to FIG. 3D, the learner terminal 110 may set a range corresponding to the vocabulary level 317 that the learner wants to learn from the English data through the vocabulary level selection interface 315.

3C and 3D, the vocabulary providing unit 207 filters a vocabulary corresponding to a vocabulary level 317 selected by a learner among a plurality of vocabularies included in the English data 313, and filters the vocabulary corresponding to the filtered vocabulary. Information 313 may be provided to the learner terminal 110. For example, the vocabulary providing unit 207 selects a vocabulary corresponding to the vocabulary level 317 selected by the learner based on the corpus, the vocabulary related data, the textbook vocabulary list, the vocabulary occurrence frequency and the importance in various tests, from the English data. You can filter.

In more detail, the vocabulary providing unit 207 may highlight and display only a plurality of vocabulary corresponding to the vocabulary level 317 selected by the learner in the English data 313. In addition, the vocabulary providing unit 207 provides the vocabulary information 313 including difficulty level, meaning, phonetic symbol, test frequency, part-of-speech, and the like for the vocabulary corresponding to the vocabulary level 317 selected by the learner, the site for learning English. It may be provided to the learner terminal 110 through 305. Here, the frequency of the test questions means, for example, the frequency of the vocabulary that frequently appears in the SAT test, when the learner selects the vocabulary level 'SAT'.

For example, when the vocabulary providing unit 207 receives the original document of the English novel from the learner terminal 110, the vocabulary providing unit 207 learns the vocabulary extracted based on the vocabulary level of the learner among the plurality of vocabularies appearing in the original document. Selected as a meaningful core vocabulary for may be provided to the learner terminal (110).

In addition, the vocabulary providing unit 207 may provide a vocabulary (eg, an old word, a slang word, etc.) that is not worth learning by the learner in the application document as the reference vocabulary to the learner terminal 110 for reference.

In addition, when the learner changes the vocabulary level, the English learning provider 209 may provide the learner terminal 110 with the vocabulary belonging to the changed vocabulary level. For example, when the learner selects a vocabulary level corresponding to the 'high 1 to high 3' range, the vocabulary providing unit 207 extracts and extracts only the vocabulary corresponding to the 'high 1 to high 3' level from the English data. The learner terminal 110 may provide the vocabulary information including the difficulty level, meaning, phonetic symbol, test frequency, part-of-speech, and the like for the vocabulary corresponding to the 'high 1 to 3' level.

When the learner changes the vocabulary level to 'civil official test', the vocabulary provider 207 extracts only the vocabulary corresponding to the 'civil officer test' level from the English data, and extracts the vocabulary corresponding to the extracted 'civil officer test' level. Vocabulary information including difficulty / meaning / phonetic symbols / test frequency / parts of speech can be provided to the learner terminal (110).

The English learning provider 209 may provide an English learning service based on the difficulty of the English data analyzed by the English data analyzer 205 and the vocabulary level selected by the learner terminal 110.

English learning provider 209 is a difficulty for generating a test question using a filtered vocabulary based on the vocabulary level selected by the learner terminal 110 (for example, the difficulty of the test problem, the difficulty of the vocabulary included in the test problem, etc.) ) And the question type (eg, short answer, multiple choice, crossword puzzle, etc.) in question.

In addition, the English learning provider 209 may generate a plurality of questions using the filtered vocabulary based on at least one of the determined difficulty of the test question and the question type, and provide the same to the learner terminal 110.

For example, referring to FIG. 3C and FIG. 3D, the vocabulary level selected by the learner terminal 110 is in the 'high 1 to high 3' level range, and the learner terminal 110 of the English learning providing site 305 When the question generation mode 321 displayed on the screen is selected, the English language learning provider 209 determines the difficulty level of the test question as 'high 1 to high 3' level, and the vocabulary corresponding to the 'high 1 to high 3' level. By using a plurality of problems can be generated and provided to the learner terminal (110). At this time, the learner terminal 110 selects a problem solving mode 323 displayed on the screen of the English learning providing site 305 to check a plurality of problems generated by the English learning providing unit 209, and to determine a plurality of problems. Can be solved.

As another example, referring to FIGS. 3C, 3F, and 3G, when the English learning provider 209 receives information about a difficulty level 325 of a test question or a question number 327 of a test question from the learner terminal 110, Based on the difficulty 325 of the test question set by the learner or the number of questions 327 of the test question, a plurality of questions may be generated and provided to the learner terminal 110.

In this case, the learner terminal 110 may select a problem solving mode 323 displayed on the screen of the English learning providing site 305 and download a plurality of problems generated by the English learning providing unit 209. When the learner terminal 110 completes problem solving for a plurality of problems, the feedback mode 329 displayed on the screen of the English learning providing site 305 is selected to provide feedback information 331 (eg, problem solving) for the problem solving. Scoring results).

The English learning provider 209 may generate a plurality of English examples based on the difficulty of the English data and provide them to the learner terminal 110. For example, referring to FIG. 3E, the English learning provider 209 may generate a plurality of English examples 319 based on a vocabulary, idioms, phrases, sentences, and the like similar to the difficulty of the English data 303. have. In addition, when there is a difficult sentence structure or grammar in the fingerprint of the English data 30, the English learning provider 209 may generate another English example using the grammar structure or grammar.

The English learning provider 209 generates a plurality of English examples using the difficulty of the English data and the filtered vocabulary (the vocabulary corresponding to the vocabulary level selected by the learner terminal 110 among the plurality of vocabularies of the English data). It may be provided to the learner terminal 110. For example, the English learning provider 209 may generate an English example corresponding to the grammar index and readability index of the English data using the filtered vocabulary.

The English learning provider 209 may generate an English example of the vocabulary corresponding to the vocabulary level selected by the learner terminal 110 and provide the same to the learner terminal 110. For example, the English learning provider 209 may provide the learner terminal 110 with example lengths corresponding to the vocabulary level selected by the learner terminal 110 with the length of the English example sentence, the grammar element, and the sentence structure.

The English learning provider 209 receives a selected example sentence field to be provided by the learner from the learner terminal 110 through an interface for selecting a plurality of preset example sentence fields (eg, SAT test field, civil service field, etc.). In this case, the learner terminal 110 may provide the English terminal sentence (eg, an English sentence generated in the test) actually used in the selected example sentence field.

On the other hand, most teachers find it difficult to distribute customized test papers to students of different levels. If different test papers are distributed to each student in a class, it is difficult to score them. In order to solve this problem, the present invention may provide a method of generating an optimal test question that can satisfy the learning level of each student through a plurality of model methods (question types of test questions).

In detail, the question type selection unit 215 may receive one of the first model method and the second model method regarding the question type of the test question from the instructor terminal 120. Here, the first model method is a method in which a plurality of predetermined learners construct a test question based on a question that is different from a predetermined probability or more. The second model method is a method of constructing a test question by estimating a probability that a plurality of learners select a wrong answer among test questions provided to a plurality of predetermined learners.

When the instructor terminal 120 selects the first model method as the question type of the test question, the English learning provider 209 may generate a test question based on a question that is different from a preset probability by a plurality of preset learners. . For example, assume that the first learner is wrong in words 1, 3, 5, the second learner is wrong in words 1, 3, 4, 5, and the third learner is wrong in words 2, 3, 5, 7. If you organize the students for the correct answer by word, they are as follows. The learner who has the wrong word 1 is the first learner, the second learner, the learner who has the wrong word 2 is the third learner, the learner who has the wrong word 3 is the first learner, the second learner, the third learner, the learner who has the wrong word 4 Assume that is the second learner, the wrong learner is the first learner, the second learner, the third learner, all learners correct the word 6, and the wrong learner is the third learner. . In this case, the English learning provider 209 may configure a test question including words 1, 3, and 5, which are questions that are incorrect or overlapped by all of the first learner, the second learner, and the third learner.

When the instructor terminal 120 selects the second model method as the question type of the test question, the English language learning provider 209 selects a plurality of learners whose error is more than a preset probability among the test questions provided to the plurality of preset learners. Test questions can be generated based on questions. For example, a return rate of each word for each of the first learner, the second learner, and the third learner is as follows.

The return rate of word 1 is 30% for first learners, 25% for second learners, and 1% for third learners.

The return rate of vocabulary 2 is 2% for 1st learner, 1% for 2nd learner, and 12% for 3rd learner.

The return rate of word 3 is 1% for 1st student, 2% for 2nd student, 5% for 3rd student

The return rate of word 4 is 0% for first learners, 15% for second learners, and 1% for third learners.

The return rate of word 5 is 50% for first learners, 40% for second learners, and 44% for third learners.

The return rate of word 6 is 3% for 1st learner, 1% for 2nd learner, 4% for 3rd learner.

The return rate of word 7 is 0% for first learners, 22% for second learners, and 34% for third learners.

Here, the word return error rate for each learner may be estimated by the second model method. For example, the third learner never misspelled word 1. However, when the third learner defers the correct answer rate of other words that have been solved so far, the probability that the third learner misses word 1 may be estimated to be 1% latent by the second model method. Word 3 is a word that every student is wrong once, but in general, it can be hard to get it wrong again. In the case of word 3, the return rate of the first learner, the second learner, and the third learner is less than 10%. Accordingly, the English learning provider 209 may generate a test question including words 1, 5, and 7 that have a total sum of learners' error rates for words higher than a predetermined criterion.

The learner level determiner 217 may determine a learning level of each of a plurality of learners belonging to the same learning level group by using a predetermined learner level algorithm. Here, the predetermined learner level algorithm is an algorithm for determining the learner level in the same learner group and may be used to provide more accurate customized learning. For example, the learner level determiner 217 calculates a standard deviation value for the result of the same test question provided to each of a plurality of learners included in the same learning level group (eg, the high 2 group) to calculate a difference in the median. As a criterion, the upper and lower grades of each learner in the same group can be determined.

Even if the learner belongs to the same grade group (or adult group) as the learner, the learner level determination unit 217 uses the preset learner level algorithm to determine the learner's learning level using the preset learner level algorithm. And determine which group the learner will belong to based on the learner's level of learning. For example, when problem solving is provided to the first learner based on the lexical level selected by the first learner, the learner level determiner 217 inputs the result of the problem solving to the preset learner level algorithm as an input value. You can decide which group level the learner will enter.

The English learning provider 209 may provide a customized English learning service based on the learning level for each learner belonging to the same learning level group.

The English learning provider 209 may generate a test question based on a common difficulty range and an individual (learning level) difficulty range for the test question set by the instructor terminal 120 and provide the test question to a plurality of learner terminals. For example, the English learning provider 209 sets each difficulty set by the instructor terminal 120 when the instructor terminal 120 sets the common difficulty range to 50% and the difficulty level for each individual level to 50%. Based on the scope, you can generate questions of test questions.

The English learning provider 209 may generate an item of a test question using a vocabulary having a lower percentage of correct answers than a vocabulary having a high percentage of individual answers based on analysis of results of a plurality of learners' test questions.

The English learning provider 209 may generate a question of a test question by using a vocabulary that a plurality of vocabulary level groups may know or need to know and provide the plurality of learner terminals. For example, the English learning provider 209 may provide the first learner who belongs to the 900 study group aiming at the TOEIC score as the priority with the lowest error rate in the test results in the study group. This lowest vocabulary may be used to provide questions for test questions.

The English learning provider 209 may provide the test questions to the plurality of learner terminals based on the test question solving time set by the instructor terminal 120 (eg, the start time and the end time of the problem solving). For example, the instructor can set a time for the learner to solve a test question at a specific time (e.g., a time set in class, a time set after school, etc.), and the learner can solve the test question set by the instructor. You can solve problems for hours.

The English learning provider 209 may provide the test questions to each learner by grouping the difficulty and the questions of the test questions based on the preset vocabulary levels of the plurality of learners. In addition, the English learning provider 209 may generate and provide various other problems within the same difficulty range.

For example, assuming that problem difficulty gradually increases in the order of Y, YG, G, B, R, and P, the English language learning provider 209 provides a plurality of learners belonging to the first group to the difficulty range of Y to YG. It is possible to provide a corresponding test question (or a personalized test question) and to provide a plurality of learners belonging to the second group to a test question (or a personalized test question) corresponding to a difficulty range of G to B.

The English learning provider 209 reduces the proportion of questions with a high percentage of correct answers and increases the percentage of questions with a high percentage of incorrect answers based on the cumulative data of the results of the test questions of a plurality of learners belonging to each group. Custom test questions can be created and provided to each learner.

As another example, the English learning provider 209 provides a plurality of learner terminals with a quiz contest to move to the next item when the number of correct answers for a sentence reaches the number set by the instructor while the same test question is provided to the plurality of learners. can do. Such a quiz competition method can help to increase learners' concentration and quickness.

The code generator 219 may generate a secret code to allow the learner terminal 110 to access a learning folder in which English learning data written by the instructor terminal 120 is stored.

The code transmitter 221 may transmit the information about the secret code to the learner terminal 110. For example, referring to FIGS. 4A to 4B, the instructor terminal 120 inputs English data for the learner's English learning through the English data analysis file 402 of the English learning providing site 400 connected to the instructor account. The English learning providing server 100 may analyze a lexical index, a grammar index, and a readability index for English data.

A plurality of English learning data (e.g., information about vocabulary, English examples, test questions, etc.) generated based on the difficulty of the analyzed English data (derived from lexical index, grammar index, and readability index) correspond to a plurality of difficulty levels Each of the plurality of learning folders 406 may be stored. For example, English learning data corresponding to the elementary level may be stored in the first level learning folder, and English learning data corresponding to the secondary level may be stored and stored in the second level learning folder.

When a secret code generation request is received from the instructor terminal 120 through the secret code generation folder 404 of the English learning providing site 400, the English learning providing server 100 includes the English learning included in each learning folder 406. The secret code 408 is generated so that the learner or the group containing the learners to which the instructor wants to disclose data can access each learning folder, and the generated secret code 408 is transmitted to each terminal of the learner or learner group. Can be.

The learner or learner group learners who share the generated secret code 408 can use the English learning data according to the teacher's approval range for the English learning data in the learning folder. Alternatively, the instructor terminal 120 may directly transmit a learning folder including English learning data corresponding to the learning level of each learner to each learner. Learners can log in to the English language learning site, receive a learning folder for their level, and enter the learning folder to learn from the English learning data assigned to them.

The instructor can adjust the learning relationship with the learner (eg, maintaining or deleting the secret code) through the secret code issuance status and connection information (learner information sharing the secret code, 410).

On the other hand, those skilled in the art, English data receiving unit 201, lexical index analysis unit 203, English data analysis unit 205, vocabulary provider 207, English language learning provider 209, vocabulary level option provider 211 ), The lexical level information receiver 213, the question type selection unit 215, the learner level determiner 217, the code generator 219, and the code transmitter 221 are each implemented separately or one or more of them. It will be fully understood that this may be implemented in an integrated manner.

5 is a flowchart illustrating a method of providing an English learning service according to an embodiment of the present invention.

Referring to FIG. 5, in operation S501, the English learning providing server 100 may receive English data. In operation S503, the English learning providing server 100 may analyze a lexical index for each of the plurality of vocabularies included in the English data. In operation S505, the English learning providing server 100 may analyze the difficulty of the English data by performing a regression analysis based on the lexical index, the grammar index, and the readability index of the English data. In operation S507, the English learning providing server 100 classifies a plurality of vocabularies by a preset vocabulary level based on the vocabulary indexes for each of the analyzed vocabularies, and classifies the plurality of vocabularies classified by vocabulary levels. Can be provided to In operation S509, the English learning providing server 100 may provide an English learning service based on the difficulty of the analyzed English data and the vocabulary level selected by the learner terminal 110.

In the above description, steps S501 to S509 may be further divided into additional steps or combined into fewer steps, according to an embodiment of the present invention. In addition, some steps may be omitted as necessary, and the order between the steps may be changed.

An embodiment of the present invention may also be implemented in the form of a recording medium including instructions executable by a computer, such as a program module executed by the computer. Computer readable media can be any available media that can be accessed by a computer and includes both volatile and nonvolatile media, removable and non-removable media. In addition, computer readable media may include all computer storage media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data.

The above description of the present invention is intended for illustration, and it will be understood by those skilled in the art that the present invention may be easily modified in other specific forms without changing the technical spirit or essential features of the present invention. will be. Therefore, it should be understood that the embodiments described above are exemplary in all respects and not restrictive. For example, each component described as a single type may be implemented in a distributed manner, and similarly, components described as distributed may be implemented in a combined form.

The scope of the present invention is shown by the following claims rather than the detailed description, and all changes or modifications derived from the meaning and scope of the claims and their equivalents should be construed as being included in the scope of the present invention. .

100: English learning server
110: learner terminal
120: instructor terminal

Claims (18)

In the English learning providing server that provides an English learning service,
An English data receiver for receiving English data;
A vocabulary index analyzer for analyzing a vocabulary index for each of a plurality of vocabularies included in the English data;
An English data analyzer configured to analyze the difficulty of the English data by performing an analysis based on the lexical index, grammar index, and readability index of the English data;
A vocabulary providing unit classifying the plurality of vocabularies by a predetermined vocabulary level based on the vocabulary indexes of the analyzed vocabularies, and providing a plurality of vocabularies classified by the vocabulary levels to learner terminals; And
English learning provider for providing the English learning service based on the difficulty of the analyzed English data and the vocabulary level selected by the learner terminal
Including,
The grammar index is calculated based on a numerical value previously assigned to each of a plurality of preset grammar elements,
The readability index is calculated based on the presence or absence of at least one of a counting vocabulary and a summary sentence,
The lexical index analysis unit calculates a lexical index for each of the plurality of vocabulary included in the English data based on the lexical ranking according to the frequency of use of the vocabulary calculated through corpus and electronic document big data,
The English language learning site offers a learning mode, problem generation mode, and problem solving mode.
When the learning mode is selected by the learner terminal, the English learning provider selects a lexical level from the learner terminal through a lexical level selection interface, and based on the corpus, the textbook vocabulary list, and the frequency of lexical occurrences in the English test. Filtering the vocabulary corresponding to the selected vocabulary level from the English data, and providing vocabulary information including difficulty and test question frequency for the vocabulary corresponding to the selected vocabulary level to the learner terminal,
When the problem generation mode is selected by the learner terminal, the English language learning provider generates a plurality of problems using the vocabulary corresponding to the selected vocabulary level, and provides the generated plurality of problems to the learner terminal.
When the problem solving mode is selected by the learner terminal, the English learning provider generates a plurality of English examples corresponding to the grammar index and readability index for the English data using the filtered vocabulary, and from the learner terminal. When one of a plurality of preset example sentences are selected, the English learning providing server generates the plurality of English examples used in the selected example sentence field and provides the generated plurality of English examples to the learner terminal.
delete delete The method of claim 1,
The English learning provider
Determine at least one of a difficulty level and a question type of a question to generate a test question using the filtered vocabulary,
And generating a plurality of questions using the filtered vocabulary based on at least one of the determined difficulty and the question type of the question, and providing the plurality of questions to the learner terminal.
delete delete The method of claim 1,
The English learning providing server further comprises a question type selection unit that receives one of a first model method and a second model method regarding a question type of a test question from an instructor terminal.
The method of claim 7, wherein
The English learning provider
When the first model method is selected as the question type of the test question,
A plurality of preset learners generate the test question based on a question that is different than a preset probability,
When the second model method is selected as the question type of the test question,
And generating the test question based on a question in which the plurality of learners select a wrong answer more than a predetermined probability among test questions provided to the plurality of preset learners.
The method of claim 1,
And a learning level determiner configured to determine a learning level of each of the plurality of learner terminals using a preset learner level algorithm.
The English learning provider
To provide a customized English learning service based on the learning level for each of the plurality of learner terminal, English learning providing server.
The method of claim 1,
A code generator for generating a secret code to allow the learner terminal to access a learning folder in which English learning data created by an instructor terminal is stored; And
The English learning providing server further comprises a secret code information transmission unit for transmitting the information on the secret code to the learner terminal.
In the method for providing an English learning service performed by the English learning providing server,
Receiving English data;
Analyzing a vocabulary index for each of a plurality of vocabularies included in the English data;
Analyzing the difficulty of the English data by performing an analysis based on the lexical index, grammar index, and readability index on the English data;
Classifying the plurality of vocabularies by a predetermined vocabulary level based on a vocabulary index for each of the analyzed vocabularies and providing a plurality of vocabularies classified by the vocabulary levels to a learner terminal; And
Providing the English learning service based on the difficulty of the analyzed English data and the vocabulary level selected by the learner terminal.
Including,
The grammar index is calculated based on a numerical value previously assigned to each of a plurality of preset grammar elements,
The readability index is calculated based on the presence or absence of at least one of a counting vocabulary and a summary sentence,
Analyzing the lexical index includes calculating a lexical index for each of the plurality of vocabularies included in the English data based on the lexical ranking according to the frequency of use of the vocabulary calculated through corpus and electronic document big data. and,
Providing the English learning service,
Providing a learning mode, a problem generating mode, and a problem solving mode through an English language learning providing site;
When the learning mode is selected by the learner terminal, a vocabulary level is selected from the learner terminal through a vocabulary level selection interface, and the vocabulary level is selected based on the corpus, the textbook vocabulary list, and the frequency of vocabulary occurrences in the English test. Filtering a corresponding vocabulary from the English data and providing the learner terminal with vocabulary information including difficulty of a vocabulary corresponding to the selected vocabulary level and a frequency of a test question;
If the problem generation mode is selected by the learner terminal, generating a plurality of questions using a vocabulary corresponding to the selected vocabulary level, and providing the generated plurality of questions to the learner terminal; And
When the problem solving mode is selected by the learner terminal, a plurality of English sentences corresponding to the grammar index and the readability index for the English data are generated using the filtered vocabulary, and the plurality of example sentences preset from the learner terminal. If one of the fields is selected, generating the plurality of English examples used in the selected example sentence field and providing the generated plurality of English example sentences to the learner terminal.
delete delete The method of claim 11,
Providing the English learning service
Determining at least one of difficulty and question type of problem to generate a test question using the filtered vocabulary;
And generating a plurality of questions using the filtered vocabulary based on at least one of the determined difficulty and the question type of the question and providing the plurality of questions to the learner terminal.
The method of claim 11,
Providing the English learning service
And selecting one of a first model method and a second model method regarding a question type of a test question from an instructor terminal.
The method of claim 15,
Providing the English learning service
When the first model method is selected as the question type of the test question,
And generating a test question based on a plurality of preset learners different from a preset probability or more.
The method of claim 15,
Providing the English learning service
When the second model method is selected as the question type of the test question,
And generating the test question based on a question in which the plurality of learners select a return error more than a preset probability among the test questions provided to the preset plurality of learners.
A computer program stored in a medium containing a sequence of instructions for providing an English language learning service,
When the computer program is executed by a computing device,
Receive English data,
Analyze the lexical index for each of the plurality of vocabulary included in the English data,
Analyze the difficulty of the English data by performing an analysis based on the lexical index, grammar index and readability index on the English data,
Classifying the plurality of vocabularies by predetermined vocabulary levels based on the lexical indexes of the analyzed plurality of vocabularies, and providing a plurality of vocabularies classified by the vocabulary levels to learner terminals;
And a sequence of instructions for providing the English learning service based on the difficulty of the analyzed English data and the lexical level selected by the learner terminal.
The grammar index is calculated based on a numerical value previously assigned to each of a plurality of preset grammar elements,
The readability index is calculated based on the presence or absence of at least one of a counting vocabulary and a summary sentence,
The sequence of the command for analyzing the lexical index is a command for calculating a lexical index for each of the plurality of vocabulary included in the English data based on the lexical ranking according to the frequency of use of the vocabulary calculated through corpus and electronic document big data. Contains a sequence of,
The sequence of instructions for providing the English learning service,
The English language learning site offers a learning mode, problem generation mode, and problem solving mode.
When the learning mode is selected by the learner terminal, a vocabulary level is selected from the learner terminal through a vocabulary level selection interface, and the vocabulary level is selected based on the corpus, the textbook vocabulary list, and the frequency of vocabulary occurrences in the English test. Filtering the corresponding vocabulary from the English data, providing the vocabulary information including the difficulty level and the test frequency frequency for the vocabulary corresponding to the selected vocabulary level to the learner terminal,
When the problem generation mode is selected by the learner terminal, a plurality of problems are generated using the vocabulary corresponding to the selected vocabulary level, and the generated plurality of problems are provided to the learner terminal.
When the problem solving mode is selected by the learner terminal, a plurality of English sentences corresponding to the grammar index and readability index for the English data are generated using the filtered vocabulary, and the plurality of example sentences preset from the learner terminal. A computer program stored in the medium, wherein the computer program comprises a sequence of instructions for generating the plurality of English examples used in the selected example sentence field and providing the generated plurality of English example sentences to the learner terminal. program.

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