JP2011128365A - Language learning device and language learning method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To suitably provide learning contents suitable for a learning level of a user to a terminal of the user, and to optimize the learning contents of the user. <P>SOLUTION: A language learning device has a user management part for managing each registered information of a plurality of users, a content management part for managing to store a plurality of learning contents including words and phrases classified with a grammar and an example of usage, a language information management part for managing a plurality of words and phrases setting attribute information of a learning level or the like, respectively, a leaning history management part for managing to accumulate each attribute information of words and phrases included in learning contents selected by the terminal of a user classified by the user as a learning history, a user learning level determination part for totalizing and analyzing attribute information set in words and phrases included in learning contents on the basis of the learning history to determine a leaning level for each of users, and a learning content recommendation part for recommending to generate learning contents suitable for each of users on the basis of learning levels for each of users. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a language learning apparatus and a language learning method for providing a learning environment for learning a language to a learner's terminal via a communication network.

  2. Description of the Related Art In recent years, services for learning languages are provided to terminals such as a user's computer via a network such as the Internet. For example, in the language learning system described in Patent Literature 1, even if there is a grammatical error in the content of a foreign language generated by a learner with respect to an inquiry from a language learning device, a desired key that is a key to the inquiry is desired. If a word is included, the conversation is continued by sending the next question so that interactive language learning can be easily performed.

JP 2002-175006 A

  However, the language learning system described in Patent Document 1 only provides an environment for learning conversation, and the learning environment provided to the user is uniform. It is difficult to optimize the learning content according to the situation.

  In view of the above problems, the present invention provides a language learning apparatus and a language learning method that appropriately provide learning content suitable for a user's learning level to a user's terminal and optimize the learning content of the user. With the goal.

  A language learning apparatus according to an embodiment of the present invention is a language learning apparatus that provides a language learning environment to terminals of a plurality of users connected via a communication network, the plurality of users A user management unit that manages each registered information, a content management unit that stores and manages a plurality of learning contents including words and phrases classified by the grammar and examples of the language, and a learning environment of the language A language information management unit that stores and manages a plurality of the words and phrases that are each set with attribute information such as a learning level, and a word included in the learning content selected by the user's terminal in the language learning environment And a learning history management unit that stores and manages each attribute information of the phrase as a learning history for each user, and the unit included in the learning content based on the learning history. And the attribute information set in the phrase, the user learning level determination unit that analyzes the aggregation result and determines the learning level for each user, and the user learning level determination unit determines the learning level Learning content recommendation that extracts the word and the phrase from the language information management unit based on the learning level for each user, generates learning content suitable for the user, and recommends it to the terminal of the corresponding user And a section.

  A language learning method according to an embodiment of the present invention is a language learning method executed by a language learning apparatus that provides a language learning environment to a plurality of user terminals connected via a communication network. The language learning device manages registration information of the plurality of users, the language learning device stores and manages a plurality of learning contents including words and phrases classified by the grammar and examples of the language, A language learning device stores and manages a plurality of language information including the word and the phrase, each of which is set with attribute information such as a learning level applied to the language learning environment, and the language learning device manages the language learning environment. In the language learning, each attribute information of words and phrases included in the learning content selected by the user's terminal is accumulated and managed as a learning history for each user. Based on the learning history, the device aggregates the attribute information set in the word and the phrase included in the learning content, analyzes the aggregation result to determine a learning level for each user, and the language learning Based on the determined learning level for each user, the device extracts the corresponding words and phrases from the plurality of words and phrases, and generates learning contents suitable for each user. Including recommendations for user terminals.

  According to the present invention, the learning level of the user is determined based on the learning history of the learning content selected by the user, the learning content suitable for the learning level is appropriately provided to the user terminal, and the user learning is performed. A language learning device and a language learning method that optimize contents can be provided.

It is a figure which shows the whole structure of the learning system which concerns on one embodiment to which the language learning apparatus of this invention is applied. (A) is a figure which shows an example of the word table managed by the word management part of FIG. 1, (b) is a figure which shows an example of the text table managed by the text management part of FIG. (A) is a figure which shows an example of the expression table managed by the expression management part of FIG. 1, (b) is a figure which shows an example of the expression table managed by the grammar management part of FIG. It is a figure which shows an example of the content table managed by the content management part of FIG. (A) is a figure which shows an example of the user table managed by the authentication part of FIG. 1, (b) is a figure which shows an example of the learning history table managed by the learning history management part of FIG. It is a block diagram which shows schematic structure in the control part of FIG. It is a flowchart which shows the production | generation process of the recommended learning content performed in the language learning apparatus of FIG. It is a figure which shows operation | movement of each part in the language learning apparatus in connection with the process of FIG. It is a figure which shows an example of the game screen of English word learning provided by the language learning apparatus of FIG. It is a figure which shows an example of the results screen which shows the result of the English word learning game of FIG. It is a figure which shows an example of the learning progress screen provided by the language learning apparatus of FIG. It is a flowchart which shows the process which introduces the learning fellow performed in the language learning apparatus of FIG. It is a figure which shows operation | movement of each part in the language learning apparatus in connection with the process of FIG. It is a flowchart which shows the process which analyzes the message content exchanged between the users performed in the language learning apparatus of FIG. 1, and produces | generates a recommended learning content. It is a figure which shows operation | movement of each part in the language learning apparatus in connection with the process of FIG. It is a figure which shows an example of the situation editor screen provided by the language learning apparatus of FIG. It is a figure which shows an example of the chat screen provided by the language learning apparatus of FIG. It is a figure which shows an example of the dictionary screen provided by the language learning apparatus of FIG. 1, (a) is a figure which shows an example of the dictionary screen which displays the meaning of a search word, (b) displays the phrase of a search word. It is a figure which shows an example of a dictionary screen. It is a figure which shows an example of the dictionary screen provided by the language learning apparatus of FIG. 1, (a) is a figure which shows an example of the dictionary screen which displays the example sentence of a search word, (b) displays the related word of a search word. It is a figure which shows an example of the dictionary screen to do. It is a figure which shows an example of the dictionary screen which displays the ranking of the search word provided by the language learning apparatus of FIG.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

(Configuration explanation)
First, the configuration of a language learning system according to an embodiment of the present invention will be described with reference to FIG. FIG. 1 is a diagram showing a schematic configuration of a language learning system 100 according to the present embodiment. 1, a language learning system 100 includes a language learning device 101 configured by a server device or the like, and one or a plurality of user terminals 1031 to 103n connected via a communication network 102. The language learning device 101 includes a language information management unit 104, a content management unit 105, a user management unit 106, and a control unit 107. In FIG. 1, the language learning device 101 is described as a single server device. However, the functions of the content server device 101 are realized using a plurality of server devices, and the functions are distributed and made redundant. May be.

  The language information management unit 104 manages information related to a language learned by a user who uses the user terminals 1031 to 103n. Generally, a language has words as lower-level components, and a plurality of words are combined to form phrases and sentences. In addition, the user needs to learn grammar related to language and characteristic expressions related to language. Therefore, the language information management unit 104 includes, for example, a word management unit 111, a sentence management unit 112, an expression management unit 113, a grammar management unit 114, and a dictionary management unit 115 in order to manage information related to such languages. As a result, the language structure can be managed. The word management unit 111 assigns and manages an ID (identification information), a part of speech, and various attributes (for example, at which learning level to learn and a situation to be used) to the word. Similarly, the sentence management unit 112 assigns IDs and various attributes to phrases and sentences for management. The expression management unit 113 assigns IDs and various attributes to the characteristic expressions of the language and manages them. The grammar management unit 114 manages the grammar of the language by assigning IDs and various attributes. The dictionary management unit 115 manages a dictionary corresponding to the language learning environment provided by the language learning device 101. By assigning IDs to words, phrases, sentences, expressions, etc., the words, phrases, sentences, expressions, etc. learned by the user can be managed.

  FIG. 2A shows an example of a word table as a database managed by the word management unit 111. FIG. 2B shows an example of a sentence table as a database managed by the sentence management unit 112. FIG. 2A illustrates a word table 201 managed by the word management unit 111. The word table 201 is a table for associating a word ID and attribute information with a word. For example, “W01” is set as the word ID for the word “I”, “part of speech: noun, level (importance 1)” is set as the attribute information, and the word ID is set as the word “grafpic”. “W04” is set, and “part of speech: adjective / noun, level (importance 2), category: art” is set as subordinate information. Here, the level (importance 1) is an index indicating at which learning level each word should be learned in the language learning environment provided by the language learning device 100 to the user. For example, a word for which a level (importance 1) is set is a word that the user should learn when at learning level 1. The learning level at which a word is to be acquired is determined according to the frequency with which the word is used, for example, when the language is actually used. Further, the frequency with which words are used can be determined, for example, by acquiring news articles or blog articles that can be browsed using the Internet. The category is a classification item that is set in consideration of the situation and field of use of each word. The word table 201 can identify words to be selected by the user and words to be written in the language learning environment provided to the user by the language learning device 101.

  The sentence table 202 is a table for associating a sentence ID and attribute information with a sentence, and indicates at which learning level the sentence should be learned. For example, in the sentence “Can I ask you what you ~?”, “S01” is set as the sentence ID, and “level (importance): 1” is set as the attribute information. The learning level at which a sentence should be learned can be determined in accordance with the frequency with which the sentence is used when the language is actually used, as in the case of words.

  FIG. 3A shows an example of the expression table 203 as a database managed by the expression management unit 113. The expression table 203 is a table for associating expression IDs and attribute information with expressions. For example, for the expression “Can I ask...”, “F01” is set as the expression ID, “Type: Formal, Level (importance): 1” is set as the attribute information, and “Help me. In the expression “.”, “F02” is set as the expression ID, and “type: Casual, level (importance): 1” is set as the attribute information. The learning level at which an expression should be learned can be determined according to the frequency with which the expression is used, as in the case of words, when the language is actually used.

  FIG. 3B shows an example of the grammar table 204 as a database managed by the grammar management unit 114. The grammar table 204 is a table for associating a grammar ID and attribute information with a grammar. For example, “G01” is set as the grammar ID for the grammar “S + V + O”, “level (importance): 1” is set as the attribute information, and “G02” is set as the grammar ID for the grammar “S + V + M”. And “level (importance): 1” is set as attribute information. The learning level at which a grammar is to be acquired can be determined according to the frequency with which the grammar is used when the language is actually used, as in the case of words.

  The content management unit 105 manages learning content for a user who uses the user terminals 1031 to 103n to learn a language. The content management unit 105 accumulates still images, moving images, voices, learning contents combined with these, etc. distributed to the user terminals 1031,... 103n, updates learning contents, and the like. Therefore, the content management unit 105 includes a content storage unit 116, a content update unit 117, and a content creation unit 118. The content accumulation unit 116 assigns an ID to the learning content, and stores and accumulates information on the learning content in a storage device. Thereby, for example, the learning content can be read by specifying the ID. In addition, by associating learning content with the IDs of words, phrases, and sentences used in the learning content, information on words and phrases that the user can learn when the learning content is viewed by the user Can be obtained. The content update unit 117 updates the learning content stored in the content storage unit 116 by the operation of the administrator of the language learning device 101. In addition, when learning content is added, words, phrases and the like used in the learning content are associated with the learning content.

  In addition, the content update unit 117 can add learning content created by a user who uses the user terminals 1031 to 103n. The learning content created by the user can be stored in the content storage unit 115 in association with the user ID for identifying the user, and the user can learn using any of the user terminals 1031, ... 103n. When logging in to the system 100, access may be possible from a start page displayed on the user terminal.

  The content creation unit 118 provides a content creation tool for simplifying and facilitating creation of learning content when a user who uses the user terminals 1031 to 103n creates learning content in the language learning device 101. . For example, it provides items for setting situations, items for setting user avatars, operation setting tools for setting movements of avatars, editing tools for editing items and avatars in time series, etc. Allows you to create content. Each item is associated with a corresponding word ID.

  FIG. 4 shows an example of a content table 301 managed by the content storage unit 116. The content table 301 is a table for associating a content ID, a word ID of a word included in the learning content, and a time when the word appears during reproduction of the learning content with a file name holding the learning content. By specifying a content ID from the content table 301, a file name for storing learning content can be acquired. For example, for the learning content whose file name is “C01001.swf”, “C01” is set as the content ID, “W01, W02,...” Is set as the word ID of the word included in the learning content, “0:30, 0:50,...” Is set as a time when a word appears during the reproduction of the learning content. Instead of using the content table 301, the file name may be associated with the content ID according to some rule.

  In the content table 301, when the learning content indicated by the content ID is viewed, reproduced, or the like, the word ID of the word that the user learns is associated with the position (time) at which the word appears in the learning content. For example, when the learning content having “C01” as the content ID is viewed, the word having the word ID of W01 is viewed by the user when 0:30 has elapsed from the start time. With such a structure of the content table 301, it is possible to acquire information on a word to be learned when the user views the learning content. Moreover, even when the viewing of the learning content is interrupted in the middle, it is possible to acquire information on the word that was actually viewed.

  The user management unit 106 manages users who use the user terminals 1031 to 103n. The user management unit 106 includes an authentication unit 119, a learning history management unit 120, and a communication analysis unit 121. The authentication unit 119 authenticates users who use the user terminals 1031,... 103n, and identifies users who are using the learning system 100. The learning history management unit 120 manages the history learned by the user using the language learning environment provided by the language learning device 101. In addition, when using the language learning environment provided by the language learning device 101 to exchange messages by chatting between users, the words and phrases included in such messages were learned. It may be included in the history. In addition, the history of learning and the like is such that the user views the learning content and receives a message, and the user creates learning content such as words and phrases that are output from the language learning device 101 to the user. Or by transmitting a message or the like to distinguish and manage words or phrases that the user has input to the language learning device 101. As a result, the words that the user has as part of the knowledge and the words actually used by the user can be distinguished and managed, and the learning level of the user can be known more accurately.

  FIG. 5A shows an example of a user table 401 managed by the authentication unit 119. The user table 401 is a table for associating user IDs with user registration information. User registration information includes name, gender, age, ID, password, and the like. The ID and password are information that is input when the user logs in to the learning system 100 from the user terminals 1031. When the user logs in to the learning system 100 from the user terminals 1031,... 103n, the authentication unit 117 can authenticate the input ID and password with the registration information in the user table 401.

  FIG. 5B shows an example of the learning history table 402 managed by the learning history management unit 120. The learning history table 402 uses the history learned by the user using the learning environment of the language provided by the learning system 100 as the learning history by associating the learning date and time, the learning sentence, the learning expression, and the learning word. It is a table which accumulate | stores according to person ID. The learning history is associated with the user ID, and the sentences, expressions, and words included in the learning content that the user has learned by viewing and the like are recorded. By using the learning history table 402, for example, the usage tendency of sentences and expressions can be detected based on the learning progress for each user ID, and the preference of sentences and expressions can be known for each user ID. The learning history table 402 allows the user to obtain information about the learned word by viewing content or the like. In addition, the learning history table 402 can be used to aggregate the number of learnings for sentences, expressions, and words for each user ID. The aggregation result can be used when determining the learning level and the progress of the learning level. In addition, using the learning history table 402, for example, it is possible to detect sentences, expressions, and words that the user has repeatedly learned, and to obtain information such as topics that the user is good at.

  The communication analysis unit 121 is included in such messages when users exchange messages using participatory content such as chat and situation editor in a language learning environment provided by the language learning device 101. Words and phrases are analyzed, and sentence expressions (Formal, Casual), etc. that users prefer based on the analysis results are estimated. The estimation result of the sentence expression (Formal, Casual) is used in a learning content recommendation unit 107c in the control unit 107 described later. It should be noted that each ID such as words and phrases analyzed from messages exchanged between users is stored in the learning history management unit 120 in the learning history table 402 for each user ID.

  The control unit 107 controls processing of each unit in the language learning device 101 in response to a request from the user terminals 1031 to 103n used by the user. For example, as shown in FIG. 6, the control unit 107 includes a user learning level determination unit 107a, a learning content recommendation unit 107b, and a user recommendation unit 107c. The control unit 107 has a communication function for executing data communication with the user terminals 1031 to 103n via the communication network 102.

  The user learning level determination unit 107a totals each ID of sentences, expressions, and words learned in the past from the learning history table 402 for each user ID shown in FIG. 5B, and analyzes the total result. The learning level and the progress of the learning level are determined for each user ID, and it is estimated that the user is interested. The determination result and the estimation result for each user ID are used in the learning content recommendation unit 107b. In addition, the user learning level determination unit 107 a totals the learning histories of a plurality of users in the learning history table 402, and based on the total result and the attribute information of the plurality of users in the user table 401 Are analyzed, and a plurality of user IDs having the same learning tendency are extracted. This extracted user ID is used in the user recommendation unit 107c. In addition, the user learning level determination unit 107a counts the number of appearances of words and phrases related to messages stored for each user ID in the learning history table 402, analyzes the total result, and analyzes the learning level of the user. In addition to determining the progress of the user, it is presumed that the user is interested. The learning level progress determination result and the estimation result are used in the learning content recommendation unit 107b.

  The learning content recommendation unit 107b is based on the learning level determination result for each user ID and the progress determination result of the learning level by the user learning level determination unit 107a, and the estimation result regarding the user's interest. The corresponding IDs are extracted from the word table 201, the sentence table 202, the expression table 203, and the grammar table 204, and the words, sentences, expressions, and grammars are read out by the extracted corresponding IDs. The learning content suitable for the progress of the learning and the favorite field is generated. The learning content recommendation unit 107b recommends the generated learning content to the corresponding user terminals 1031 to 103n.

  In addition, the learning content recommendation unit 107b has a learning level progress determination result for each user ID by the user learning level determination unit 107a, a guess result regarding interest, and a preferred sentence expression for each user ID by the communication analysis unit 121 ( Formal, Casual), each correspondence ID is extracted from the word table 201, the sentence table 202, the expression table 203, and the grammar table 204 in the language information management unit 104, and the word, sentence, The expression and grammar are read out, and learning contents of a favorite expression are generated in a favorite field suitable for the learning level or the progress of the learning level for each user ID. The learning content recommendation unit 107b recommends the generated learning content to the corresponding user terminals 1031 to 103n.

  The user recommendation unit 107c reads out the registered information of the corresponding user from the user table 401 using the user ID of the same learning tendency extracted by the user learning level determination unit 107a, and the user terminal 1031 of the corresponding user. , ... Recommended for 103n as learning friends.

Example 1
Next, various processes of the language learning apparatus 101 will be described with reference to the drawings. First, the process of generating learning content recommended by the language learning device 101 based on the learning history for each user ID will be described with reference to FIGS. In this process, an example of learning English as a language will be described.

  FIG. 7 is a flowchart showing the recommended learning content generation process based on the learning history for each user ID executed in the language learning device 101. FIG. 8 is a diagram illustrating a specific example of processing executed by each unit in the language learning device 101 corresponding to the processing shown in FIG. FIG. 9 is a diagram illustrating an example of a game screen for learning English words. FIG. 10 is a diagram showing a learning result of English words by the game of FIG. FIG. 11 is a diagram illustrating an example of a screen that displays learning progress of English words and recommended learning content.

  In FIG. 7, the language information management unit 104 and the content management unit 105 in the language learning device 101 perform tagging on each of words, sentences, expressions, grammars, and learning contents (step S501). That is, the word table 201 shown in FIG. 2A, the sentence table 202 shown in FIG. 2B, the expression table 301 shown in FIG. 3A, the grammar table 204 shown in FIG. And like the content table 301 shown in FIG. 4, the process which provides ID and attribute information with respect to each of a word, a sentence, an expression, a grammar, and learning content is implemented.

  Next, when the user management unit 121 in the language learning device 101 logs in from the user terminal 1031 used by the user, the user management unit 121 authenticates the input ID and password with registration information in the user table 401. Next, the control unit 107 in the language learning device 101 transmits an English learning front page to the user terminal 1031 and waits for a learning content selection operation. When the user of the user terminal 1031 performs a learning content selection operation, the content management unit 105 transmits the selected learning content to the user terminal 1031 via the control unit 107 (step S502).

  Next, when an action is performed on the learning content by the user of the user terminal 1031 (seeing the learning content, trying to pronounce, solving the problem, searching for a word from the dictionary, etc.), an instruction signal corresponding to the action Is transmitted to the language learning device 101. When the control unit 107 in the language learning device 101 detects reception of an instruction signal corresponding to an action transmitted from the user terminal 1031 (step S503), an English word, sentence, expression, grammar, or the like corresponding to the action. Are recorded for each corresponding user ID in the class history table 402 in the learning history management unit 120 (step S504).

  Next, the user learning level determination unit 107a in the control unit 107 counts the number of word IDs, sentence IDs, expression IDs, and grammar IDs from the past learning history recorded in the class history table 402 of the corresponding user ID. (Step S505). Next, the user learning level determination unit 107a analyzes the aggregation result (step S506), determines the learning level of the user ID and the progress of the learning level, and is interested in the user (interested). Field etc.) is estimated (step S507).

  Next, the learning content recommendation unit 107c in the control unit 107 is based on the determination result of the learning level of the user ID and the progress of the learning level by the user learning level determination unit 107a and the estimation result on the user's interest. The corresponding IDs are extracted from the word table 201, the sentence table 202, the expression table 203, and the grammar table 204 in the language information management unit 104, and the words, sentences, expressions, and grammars are read out by the extracted corresponding IDs. The learning content suitable for the learning level or the progress of the learning level is generated for each ID and in a favorite field. The learning content recommendation unit 107b recommends the generated learning content to the corresponding user terminals 1031 to 103n (step S508). In step S508, when an action is performed on the recommended learning content by the user at the user terminal 1031, the processing from step S503 to step S508 is repeatedly executed. If no action is performed on the recommended learning content by the user at the user terminal 1031, this processing is terminated.

  Next, the operation of each unit in the language learning apparatus 101 related to the processing shown in FIG. 7 will be described with reference to FIG. In FIG. 8, each block indicated by T101 to T104 indicates the main operation in the language learning apparatus 101 related to the processing shown in FIG. 7, and the operation content of each part related to these blocks T101 to T104 is shown below it. Shown in

  In FIG. 8, first, the learning content selected by the user A of the user terminal 1031 is provided (T101). At this time, it is assumed that the English text included in the selected learning content is "-Can I ask you what you thought of the movie?-The graphics were beautiful." Each setting of word ID, sentence ID, expression ID, and grammar ID for the English sentence, and attribute information of the word “graphic” and attribute information of the expression “Can I ask... Assume that the language information management unit 104 and the content management unit 105 are set. These settings are based on the settings of the tables 201 to 204 shown in FIGS.

  Next, when the user A of the user terminal 1031 performs an action on the learning content (see the learning content, try to pronounce it, solve the problem, search for a word from the dictionary, etc.) (T102), the language learning device The control unit 107 in 101 records each ID of English words, sentences, expressions, grammars, etc. corresponding to the action in the class history table 402 of the corresponding user A in the learning history management unit 120 (T103). . In this case, as shown in FIG. 8, the learning history table 402 in the learning history management unit 120 includes “learning text: S01, S02, learning expression: F01, learning word: W01,” as the class history of the user A. W02, W03, W04, W06, W08,.

  Next, the user learning level determination unit 107a totals the IDs of sentences, expressions, and words learned by the user A in the past from the learning history table 402. For example, as shown in FIG. 8, “W04: 3 times, W08: 4 times, F01: 1 time,...” Is obtained as a totaling result of user A (attribute: male, 40 years old). Subsequently, the user learning level determination unit 107a analyzes the aggregation result, determines the learning level and the progress of the learning level for each user ID, and estimates that the user is interested. For example, as shown in FIG. 8, the analysis result is “User A is interested in art. User A is learning to a level of 2 or less. User A has studied formal expression. 40's are interested in art. Men in their 40's often use Formal expressions. " The determination result and the estimation result of the user A are used in the learning content recommendation unit 107b.

  Next, the learning content recommendation unit 107b is a language information management unit based on the learning level determination result of the user A by the user learning level determination unit 107a, the progress determination result of the learning level, and the estimation result regarding the user's interest. 104, each corresponding ID is extracted from the word table 201, the sentence table 202, the expression table 203, and the grammar table 204, and the words, sentences, expressions, and grammars are read out based on the extracted corresponding IDs. A learning content suitable for the progress of the learning level and in a favorite field is generated. For example, as shown in FIG. 8, “other words of art W17: animation, W14: create” and “other expressions of formal type F04, F05” are extracted and used as elements for generating recommended content. Learning content recommended for the user A is generated. Also, as shown in FIG. 8, “levels 1 and 2 words W101, W403” and “level 1 grammars G04, G05” are extracted as elements for generating a problem, and are recommended to user A. Is also generated. The learning content recommendation unit 107b transmits the generated learning content and problem to the user terminal 1031 of the user A (T104).

  When the user A performs an action on the recommended learning content and the problem received from the language learning device 101 at the user terminal 1031 (T102), the operation related to T103 to T104 is repeated in the language learning device 101. Executed.

  Next, specific examples of learning content provided by the language learning device 101 to the user terminal 1031 will be described with reference to FIGS. FIG. 9 is a diagram illustrating an example of a game screen for learning English words. FIG. 10 is a diagram showing an example of a screen that displays the learning result after the game shown in FIG. FIG. 11 is a diagram illustrating an example of a screen displaying a past learning progress of a certain user.

  First, the game screen P600 for learning English words shown in FIG. 9 will be described. The game screen P600 includes an English word display portion P601 that displays English words, a remaining display portion P602 that displays the number of remaining English words, a results display portion P603 that indicates results during the game, and an English word display portion P601. A selection operation unit P604 for selecting and operating Japanese corresponding to the displayed English word; and an animation display unit P605 for displaying an animation corresponding to the selection operation during the game.

  In the game screen P600 for learning English words, when the user selects and corrects the Japanese language for the English words displayed on the English word display unit P601, the watermelon is displayed on the animation display unit P605. The animation to be shipped is displayed, and the number of “shipments” is added and displayed on the results display section P603. Also, if the user selects and mistakes the Japanese language for the English word displayed on the English word display unit P601 in the selection operation unit P604, an animation in which the watermelon is broken is displayed in the animation display unit P605, and the results display unit In P603, the number of “damaged” is added and displayed. In the remaining display part P602, every time an English word is given, the remaining number is displayed by subtraction. Note that the content of the English words presented on the game screen P600 is based on the learning level determination result and learning level progress determination result for each user ID by the user learning level determination unit 107a, and the logged-in use It is adjusted according to the person's learning level.

  In this game screen P600, the user can easily select English words suitable for the progress of his / her learning level by playing the game while selecting the Japanese corresponding to the English words to be asked in one of three alternatives. Can learn to.

  Next, FIG. 10 shows an example of a results screen on which the result of executing the English word learning game shown on the game screen P600 is displayed. This results screen P700 includes a result display unit P701 that displays the results of the game, a word display unit P702 that displays a list of English words presented in the English language learning game, and a response that displays a list of Japanese selected by the user. The display part P703, the correct answer display part P704 which displays a list of correct answers, and the determination display part P705 which displays the determination result of each question as a list are provided. The result display section P701 displays a game result of a certain user, and displays that “SAFE (correct answer): 32” and “WRONG (error): 8” with respect to “number of questions: 40”. The detailed contents of the game result are displayed on the word display part P702, the answer display part P703, the correct answer display part P704, and the determination display part P705.

  The user who has finished the game on the game screen P600 can immediately learn the learning result of the English word from the results screen. Next, FIG. 11 shows an example of a screen that displays the past learning progress of the user. The learning progress screen P800 includes a grammar acquisition ratio display unit P801 that displays the acquisition ratio of “Grammar / mechanism” in a pie chart, and a grammar acquisition progress display unit that displays the acquisition ratio of “Grammar / mechanism” in a time-series graph. P802, a word acquisition ratio display unit P803 that displays the acquisition ratio of “Vocabulary / word” in a pie chart, a word acquisition progress display unit P804 that displays the acquisition ratio of “Vocabulary / word” in a time series graph, and a recommendation A recommended content display unit P805 that displays learning content to be displayed.

  In this learning progress screen P800, the grammar acquisition ratio display unit P801 displays the number of contents touched by the user to learn the grammar and the number acquired in a pie chart, and learns to the right of the pie chart. The number of grammars that have not been acquired is displayed as “Number 21 that has not been worn”, and the number of grammars that have been acquired is displayed as “Number that has been learned 0”. In this case, since the number of mastered grammars is “0”, the number acquired by the user is not displayed in the pie chart. In the grammar acquisition progress display section P802, the number of contents that the user has touched to learn the grammar is displayed every day (12/3 to 12/10). In this grammar acquisition progress display section P02, the display period can be selected from “1 week, 1 month, 3 months, 6 months, 1 year”.

  Moreover, in the word acquisition ratio display part P803, the number of words that the user has contacted to learn English words and the number of words acquired by the user are displayed in a pie chart, and are not acquired on the right side of the pie chart. The number of English words is displayed as “number 280 not worn”, and the number of acquired words is displayed as “number 63 worn”. In this case, since the number of acquired English words is “63”, the user displays “number 63 worn” in different colors for the number “343” touched in the pie chart. Moreover, in the word acquisition progress display part P804, the number of words touched by the user to learn English words is displayed every day (12/3 to 12/10). In this word acquisition progress display section P804, the display period can be selected from “1 week, 1 month, 3 months, 6 months, 1 year”.

  The display contents of the grammar acquisition ratio display unit P801, the grammar acquisition progress display unit P802, the word acquisition ratio display unit P803, and the word acquisition progress display unit P804 are displayed based on the learning history for each user ID in the learning history table 402. Is possible. In the recommended content display unit P805, the learning content recommendation unit 107b displays learning content recommended based on the learning level of the user and the progress of the learning level.

  In this learning progress screen P800, the user can easily recognize the progress of the self-confidence learning level, and can easily grasp the subsequent learning plan. On the game screen P600, the user can learn English words while enjoying the game. In addition, although the game screen P600 for learning English words is illustrated, by preparing a game screen for learning grammar, the user can recognize the progress of the self-confidence learning level and perform subsequent learning. The plan can be easily grasped. Moreover, the language learning apparatus 101 can optimize and provide learning content according to a user's learning level. As a result, the user can easily improve the learning level with the optimized learning content in the language learning environment provided from the language learning device 101, and can easily obtain the optimum learning environment. Can do.

(Example 2)
Next, processing in which the language learning apparatus 101 introduces learning friends by analyzing learning tendency based on the learning history for each user ID will be described with reference to FIGS. 12 and 13. In this process, an example of learning English as a language will be described.

  FIG. 12 is a flowchart showing a process of introducing learning friends by analyzing a learning tendency based on a learning history for each user ID executed in the language learning device 101. FIG. 13 is a diagram illustrating a specific example of processing executed by each unit in the language learning device 101 corresponding to the processing shown in FIG.

  In FIG. 12, the language information management unit 104 and the content management unit 105 in the language learning device 101 perform tagging on each of words, sentences, expressions, grammars, and learning contents (step S901). That is, the word table 201 shown in FIG. 2A, the sentence table 202 shown in FIG. 2B, the expression table 301 shown in FIG. 3A, the grammar table 204 shown in FIG. And like the content table 301 shown in FIG. 4, the process which provides ID and attribute information with respect to each of a word, a sentence, an expression, a grammar, and learning content is implemented.

  Next, when the user management unit 121 in the language learning device 101 logs in from the user terminal 1031 used by the user, the user management unit 121 authenticates the input ID and password with registration information in the user table 401. Next, the control unit 107 in the language learning device 101 transmits an English learning front page to the user terminal 1031 and waits for a learning content selection operation. When the user of the user terminal 1031 performs a learning content selection operation, the content management unit 105 transmits the selected learning content to the user terminal 1031 via the control unit 107 (step S902).

  Next, when an action is performed on the learning content by the user of the user terminal 1031 (seeing the learning content, trying to pronounce, solving the problem, searching for a word from the dictionary, etc.), an instruction signal corresponding to the action Is transmitted to the language learning device 101. When the control unit 107 in the language learning device 101 detects reception of an instruction signal corresponding to an action transmitted from the user terminal 1031 (step S903), an English word, sentence, expression, grammar, or the like corresponding to the action. Are recorded in the learning history table 402 of the corresponding user ID in the learning history management unit 120 (step S904).

  Next, the user learning level determination unit 107a in the control unit 107 determines the number of word IDs, sentence IDs, expression IDs, and grammar IDs of a plurality of users from past learning histories recorded in the class history table 402. (Step S905). Next, the user learning level determination unit 107a analyzes the learning tendency among users based on the aggregation results of a plurality of users, and extracts user IDs having the same learning tendency (step S906).

  Next, the user recommendation unit 107c reads the registration information of the corresponding user from the user table 401 using the user ID of the same learning tendency extracted by the user learning level determination unit 107a, and uses the corresponding user. Are recommended as learning companions to the person terminals 1031,... 103n (step S907). Thus, the present process is terminated.

  Next, the operation of each unit in the language learning apparatus 101 related to the processing shown in FIG. 12 will be described with reference to FIG. In FIG. 13, each block indicated by T201 to T204 indicates the main operation in the language learning apparatus 101 related to the processing shown in FIG. 12, and the operation content of each part related to these blocks T201 to T204 is shown below it. Shown in

  In FIG. 13, first, the learning content selected by the user A of the user terminal 1031 is provided (T201). At this time, it is assumed that the English text included in the selected learning content is "-Can I ask you what you thought of the movie?-The graphics were beautiful." Each setting of word ID, sentence ID, expression ID, and grammar ID for the English sentence, and attribute information of the word “graphic” and attribute information of the expression “Can I ask... Assume that the language information management unit 104 and the content management unit 105 are set. These settings are based on the settings of the tables 201 to 204 shown in FIGS.

  Next, when the user A of the user terminal 1031 performs an action on the learning content (see the learning content, try to pronounce, solve the problem, search for a word from the dictionary, etc.) (T202), the language learning device The control unit 107 in 101 records each ID of English words, sentences, expressions, grammars, etc. corresponding to the action in the class history table 402 of the corresponding user A in the learning history management unit 120 (T203). .

  Next, the user learning level determination unit 107a totals IDs of sentences, expressions, and words learned in the past by the plurality of users A, B, C,... To analyze learning trends among users. For example, as shown in FIG. 13, the analysis result “user A and user B have the same learning tendency. User C is higher than user A but has learned to the same level up to that level” is obtained. It is done. Based on the analysis result of the learning tendency between users, the user learning level determination unit 107a extracts the user IDs (U0001, U0002, U0003) of the users A, B, and C from the user table 401. This user ID (U0001, U0002, U0003) is used in the user recommendation unit 107c.

  Next, the user recommendation unit 107c reads the registration information of the corresponding user from the user table 401 based on the user IDs (U0001, U0002, U0003) with the same learning tendency extracted by the user learning level determination unit 107a. To the corresponding user terminals 1031... 103 n are recommended as learning friends (T204).

  Through the above user recommendation processing, the users A, B, and C can easily learn learning friends having the same learning tendency in the language learning environment provided by the language learning device 101, and are motivated to continue learning. Can be maintained.

(Example 3)
Next, processing in which the language learning device 101 analyzes the contents of messages in other languages exchanged between users and generates learning content in a recommended learning language will be described with reference to FIGS. . In this processing, an example in which Japanese is used as a message in another language and English is used as a learning language will be described.

  FIG. 14 is a flowchart showing a process of recommending learning content of a learning language based on the analysis content of the other language message between users, which is executed in the language learning device 101. FIG. 15 is a diagram illustrating a specific example of processing executed by each unit in the language learning device 101 corresponding to the processing shown in FIG. FIG. 16 is a diagram illustrating an example of a situation editor screen as participatory content. FIG. 17 is a diagram illustrating an example of a screen during chatting between users.

  In FIG. 14, the language information management unit 104 and the content management unit 105 in the language learning device 101 perform tagging on each of words, sentences, expressions, grammars, and learning contents (step S1001). That is, the word table 201 shown in FIG. 2A, the sentence table 202 shown in FIG. 2B, the expression table 301 shown in FIG. 3A, the grammar table 204 shown in FIG. And like the content table 301 shown in FIG. 4, the process which provides ID and attribute information with respect to each of a word, a sentence, an expression, a grammar, and learning content is implemented. The language information management unit 104 also performs tagging (assigning an ID) to words, sentences, expressions, and grammars included in Japanese messages exchanged between users (step S1001).

  Next, when the user management unit 121 in the language learning device 101 logs in from the user terminal 1031 used by the user, the user management unit 121 authenticates the input ID and password with registration information in the user table 401. Next, the control unit 107 in the language learning device 101 transmits an English learning front page to the user terminal 1031 and waits for a learning content selection operation. When a participatory content selection operation such as chat or situation editor is performed by a plurality of users of the user terminals 1031,... 103n, the content management unit 105 selects the selected participatory content via the control unit 107 as a user. It transmits to terminals 1031, ... 103n (step S1002).

  Next, when a writing / type-in action (for example, inputting a Japanese message between users by chat) is performed on a participatory content by a plurality of users of the user terminals 1031,. A message is transmitted to the language learning device 101. When the control unit 107 in the language learning device 101 detects reception of a Japanese message transmitted from the user terminal 1031 (step S1003), the communication analysis unit 121 includes words, sentences, and expressions included in the Japanese message. Each ID such as grammar is recorded for each user ID in the class history table 402 in the learning history management unit 120 (step S1004). In this case, each ID tagged with the word, sentence, expression, and grammar of the Japanese message in step S1001 is recorded in the class history table 402 for each corresponding user ID.

  Next, the communication analysis unit 121 analyzes words, sentences, expressions, grammar, and the like included in the Japanese message input by the user using participatory content such as chat and a situation editor (step S1005). Based on this analysis result, a sentence expression (Formal, Casual) etc. that the user prefers is estimated. This sentence expression (Formal, Casual) estimation result is used in the user learning level determination unit 107a.

  Next, the user learning level determination unit 107a determines each ID of the word, sentence, expression, grammar, etc. based on the analysis result of the word, sentence, expression, grammar included in the Japanese message analyzed by the communication analysis unit 121. The number of appearances is counted (step S1006). Next, the user learning level determination unit 107a determines the learning level of each user and the progress of the learning level based on the total result of each ID, and each user is interested (such as a field of interest). Is estimated (step S1007).

  Next, the learning content recommendation unit 107c in the control unit 107 is based on the determination result of the learning level of the user ID and the progress of the learning level by the user learning level determination unit 107a and the estimation result on the user's interest. The corresponding IDs of the learning languages are extracted from the word table 201, the sentence table 202, the expression table 203, and the grammar table 204 in the language information management unit 104, and the words, sentences, expressions, and grammars are read out using the extracted corresponding IDs. The learning content suitable for the learning level or the progress of the learning level is generated for each user ID, and English learning content in a favorite field is generated. The learning content recommendation unit 107b recommends the generated learning content to the user terminals 1031 to 103n of the corresponding user (step S1008). In addition, in step S1008, when an action is performed on the recommended learning content by the user at the user terminals 1031,... 103n, the processes of steps S1003 to S1008 are repeatedly executed. If no action is performed by the user on the user terminal 1031 to 103n with respect to the recommended learning content, this process is terminated.

  Next, the operation of each unit in the language learning apparatus 101 related to the processing shown in FIG. 14 will be described with reference to FIG. In FIG. 15, each block indicated by T301 to T304 indicates the main operation in the language learning apparatus 101 related to the processing shown in FIG. 14, and the operation content of each part related to these blocks T301 to T304 is shown below it. Shown in

  In FIG. 15, first, participatory content such as a chat or situation editor selected between users A, B, C,... Of a plurality of user terminals 1031,. At this time, it is assumed that chat is selected between users A and B. Next, when a user A, B performs a writing and typing action in chat (for example, inputting a Japanese message between users by chat), the input Japanese message is transmitted to the language learning device 101. The When the control unit 107 in the language learning device 101 detects the reception of the Japanese message transmitted from the user terminal 1031, the communication analysis unit 121 displays the word, sentence, expression, grammar, etc. included in the Japanese message. The analyzed words, sentences, expressions, and grammar IDs are recorded in the class history table 402 in the learning history management unit 120 for each corresponding user ID. In this case, for example, as shown in FIG. 15, if “User A: How was the movie you saw yesterday?” Is input, “User B: The graphic was beautiful.” The communication analysis unit 121 analyzes the text of each input message. As an analysis result of this sentence, for example, as shown in FIG. 15, “W04: yesterday, W52: watch, W06: movie, W101: how” is recorded in the user A, and the preference result of the expression is estimated. "Casual expression" is obtained.

  Next, the user learning level determination unit 107a determines each ID of the word, sentence, expression, grammar, etc. based on the analysis result of the word, sentence, expression, grammar included in the Japanese message analyzed by the communication analysis unit 121. The number of occurrences of In this case, for example, as shown in FIG. 15, “word W06: 3 times, W52: 4 times, expression F01: 1 time” is obtained as a totaling result of user A (attribute: male, 40 years old). Subsequently, the user learning level determination unit 107a analyzes the aggregation result, determines the learning level and the progress of the learning level for each user ID, and estimates that the user is interested. For example, as shown in FIG. 15, the analysis result is “User A is interested in art. User A is still learning at a level of 2 or less. User A has studied Casual expression. 20's are interested in art. Women in their 20's often use Casual's expression. ”The learning level determination result and the learning level progress determination result for User A and the user's favorite expression A guess result is obtained. The determination result and the estimation result of the user A are used in the learning content recommendation unit 107b.

  Next, the learning content recommendation unit 107c is based on the learning level of the user ID and the determination result of the progress of the learning level by the user learning level determination unit 107a, and the estimation result regarding the user's interest, and the language information management unit Each correspondence ID of the learning language is extracted from the word table 201, the sentence table 202, the expression table 203, and the grammar table 204 in 104, and the words, sentences, expressions, and grammars are read out by the extracted correspondence IDs, and are classified by user ID. Generate English learning content suitable for the learning level or progress of the learning level and in a favorite field. For example, as shown in FIG. 15, “other words of art W17: animation, W14: create” and “other expressions of Casual type F14, F15” are extracted and used as elements for generating recommended content. Learning content recommended for the user A is generated. Also, as shown in FIG. 15, “levels 1 and 2 words W101, W403” and “level 1 grammars G04, G05” are extracted as elements for generating a problem, and are recommended to user A. Is also generated. The learning content recommendation unit 107b transmits the generated learning content and problem to the user terminal 1031 of the user A (T304).

  When the user A performs an action on the recommended learning content and the problem received from the language learning device 101 in the user terminal 1031 (T302), the operations related to the above T303 to T304 are repeated in the language learning device 101. Executed.

  Next, specific examples of participatory content provided by the language learning apparatus 101 to the user terminal 1031 will be described with reference to FIGS. FIG. 16 is a diagram illustrating an example of a situation editor screen for creating learning content in which a user learns English. FIG. 17 is a diagram illustrating an example of a chat screen.

  First, the situation editor screen P1100 for creating learning content for learning English shown in FIG. 16 will be described. This situation editor screen P1100 is a situation display screen P1100 on which various settings such as a user's avatar, background and items (clothes, accessories, other characters, etc.) related to the situation, and sound effects are arranged. And an item display unit P1102 for selecting avatar speech, movement and emotion, items (clothes, accessories, other characters, etc.) and sound effects, etc. to be arranged in the situation display unit P1101, and each setting set in the situation display unit P1101 A timeline display unit P1103 that displays avatar motion units in time series. This situation editor screen P1100 is provided as a content creation tool to the user terminals 1031 to 103n of the user by the content creation unit 118.

  On this situation editor screen P1100, the user selects and operates the avatar's dialogue, movement and emotion, items (clothes, accessories, other characters, etc.) and sound effects from the item display portion P1102, and places them on the situation display portion P1101. Then, blocks including settings (sentences, movements, and emotions) of each avatar are displayed in time series in the timeline display unit P1103 for each avatar motion unit. In the item display part P1102 of FIG. 16, the example which displays the screen which selects the motion of an avatar is shown. With this screen, the user can easily set the motion of the avatar simply by selecting the motion of the avatar. In each block displayed in the timeline display part P1103, the required time for the dialogue, movement, and emotion is set in advance as a setting related to the avatar. In other words, a required time is set in advance for the expression of speech, movement, and emotion selected in the item display unit P1102. The playback time of each block is automatically adjusted according to the longest required time among dialogue, movement and emotion. Therefore, the user only needs to select and place the avatar dialogue, movement and emotion, items (clothes, accessories, other characters, etc.) and sound effects on the situation display part P1101, and the time of each block. There is no need to adjust the operation. For this reason, the user can easily and easily create learning content in a situation of his / her preference using the situation editor screen P1100. The learning content created using the situation editor screen P1100 can be confirmed by immediately reproducing the moving image. In addition, the learning content created by the user can individually change the settings related to the avatar and the settings related to the item on the situation editor screen P1100. Further, the learning content created using the situation editor screen P1100 is given a content ID by the content management unit 105 and stored in the content storage unit 116.

  In addition, words, sentences, expressions, and grammars included in sentences set in the learning content created using the situation editor screen P1100 are analyzed by the user learning level determination unit 107a, and words, sentences, expressions, Each ID corresponding to the grammar is recorded in the learning history table 402 for each user ID. Therefore, the user learning level determination unit 107a records the learning history for each learning ID created by using the situation editor screen P1100, and also uses it for the text input by the user. It is possible to determine the learning level and the progress of the learning level for each person ID.

  Next, the chat screen P1200 shown in FIG. 17 will be described. This chat screen P1200 allows a plurality of users to input comments on the learning content of the situation created by the user using the situation editor screen P1100 shown in FIG. The chat screen P1200 includes a content display unit P1201 for reproducing and displaying the learning content, and a comment display unit P1202 for the user to input a comment.

  In this chat screen P1200, a plurality of users can input comments in the comment display portion P1202 with respect to the learning content being reproduced in the content display portion P1201. The comment input by the user is immediately displayed in the comment frame for each user in the comment display part P1202. The comment displayed in the comment frame for each user is analyzed by the communication analysis unit 121, the word, sentence, expression, grammar, etc. included in the sentence are analyzed, and the analyzed word, sentence, expression, Each ID of the grammar is recorded in the class history table 402 in the learning history management unit 120 for each user ID. Further, in the communication analysis unit 121, the preference (Formal, Casual) of the sentence expression of each user is estimated based on the analysis result.

  Then, in the user learning level determination unit 107a, each of words, sentences, expressions, grammars, etc. based on the analysis results of words, sentences, expressions, grammars included in the comments (Japanese) analyzed by the communication analysis unit 121 The number of appearances of ID is totaled. Further, the user learning level determination unit 107a obtains the learning level determination result for the user, the progress determination result of the learning level, and the estimation result for the user's interest from the total result. Next, in the learning content recommendation unit 107c, the language information management unit 104 is based on the learning level of the user ID and the determination result of the progress of the learning level by the user learning level determination unit 107a and the estimation result regarding the user's interest. Each corresponding ID of the learning language (English) is extracted from the word table 201, sentence table 202, expression table 203, and grammar table 204. Further, the learning content recommendation unit 107c reads words, sentences, expressions, and grammars from the extracted corresponding IDs, and learns English in a favorite field suitable for the learning level or progress of the learning level for each user ID. Content is automatically generated and provided as recommended content to the user terminal of the corresponding user.

  As described above, when the user uses participatory content such as chat or a situation editor, the language learning device 101 records a learning history even for learning content created by the user or comments exchanged by chat. Then, the learning level and the progress of the learning level are determined for each user ID, the matter related to the user's interest is estimated, the learning level suitable for each user ID based on the determination result and the estimation result, and the favorite field It is possible to create and recommend learning content. Accordingly, the language learning device 101 can optimize and provide learning content according to the learning level of the user. As a result, in the language learning environment provided by the language learning device 101, the user can improve the learning level even if he / she participates in participatory content, and the user participation type learning environment can be facilitated. Obtainable. In the present embodiment, an example is shown in which a sentence of a message exchanged between users is analyzed, and recommended learning content is generated from the analysis result. However, the present invention is not limited to this example. For example, the learning content recommendation unit 107c selects an item that each user is interested in based on an item placed in a situation created by the user or an analysis result of a message sentence exchanged between users. Estimate and recommend items (for example, clothes and accessories) for the avatar created by each user based on the estimation result or items (for example, furniture) to be placed in the situation to the user terminal of the corresponding user. You may do it.

(Dictionary function)
Next, dictionary functions managed by the dictionary management unit 115 will be described with reference to FIGS. FIG. 18 is a diagram illustrating an example of a dictionary screen that displays the meaning of words and phrases using the words. FIG. 19 is a diagram illustrating an example of a dictionary screen that displays an example sentence of a word and a related word of the word. FIG. 20 is a diagram illustrating an example of a dictionary screen that displays rankings of words searched in the past.

  FIG. 18A shows an example of a dictionary screen 1300 displaying the meaning of words. The dictionary screen 1300 includes a function selection unit P1301 that selectively selects dictionary functions such as meanings, phrases, example sentences, and related words corresponding to the input word, and a meaning display unit that displays the meaning of the input word. P1302 and a search word display unit P1303 that displays words searched in the past.

  In this dictionary screen 1300, the user selects “meaning” in the function selection unit P1301, inputs “welcome” as a word to be searched, and displays the meaning on the meaning display unit P1302. In the search word display part P1303, the word searched by the user in the past is displayed as “a footprint of the searched word”. Further, in the function selection unit P1301, the number of times the user inputs the word on the dictionary screen 1300 is displayed as “once / total once”. The display of the word searched in the past and the number of search words can be displayed by recording the word ID of the search word input on the dictionary screen 1300 in the learning history table 402 for each user ID. By using this dictionary screen 1300, the user can simultaneously know the number of searches for the word that the user has input in the past and other search words that have been input in the past, in addition to the meaning of the currently searched word.

  FIG. 18B is a diagram showing an example of a dictionary screen 1300 that displays word phrases. In the dictionary screen 1300, the same parts as those in the dictionary screen 1300 shown in FIG. 18A are denoted by the same reference numerals, and description thereof is omitted. The dictionary screen 1300 includes a function selection unit P1301, a phrase display unit 1304 that displays a phrase of an input word, and a search word display unit P1303.

  In this dictionary screen 1300, the user selects “sung phrase” in the function selection unit P1301, inputs “welcome” as a word to be searched, and “[form] 1. make a person welcome 2. You're [You are] welcome. ”and the phrase“ [name] 1. did a person welcome ← → say welcome to a person 2. outstay [overstay] one's The phrase that is used as a noun such as “welcome” is displayed. The content of the phrase displayed on the phrase display unit 1304 is based on the learning history table 402 in which the word ID of the search word is recorded for each user ID, and the user learning level determination unit 107a counts the word ID of the user. It is determined by the learning level determination result and the learning level progress determination result determined from the result. Therefore, by using this dictionary screen 1300, the user can simultaneously learn the phrase using the word suitable for his / her learning level in addition to the meaning of the currently searched word.

  FIG. 19A shows an example of a dictionary screen 1300 that displays example sentences of words. In the dictionary screen 1300, the same parts as those in the dictionary screen 1300 shown in FIG. 18A are denoted by the same reference numerals, and description thereof is omitted. The dictionary screen 1300 includes a function selection unit P1301, an example sentence display unit 1305 that displays an example sentence of an input word, and a search word display unit P1303.

  In this dictionary screen 1300, the user selects “example sentence” in the function selection unit P1301, inputs “welcome” as a word to be searched, and “1. Welcome home! 2. Welcome to Japan! 3. The President welcome Prime Minister of Japan at the airport. The contents of the example sentence displayed on the example sentence display unit 1304 are calculated by using the learning history table 402 in which the word IDs of the search words are recorded for each user ID, and the user learning level determination unit 107a counts the word IDs of the user. It is determined by the learning level determination result and the learning level progress determination result determined from the result. Therefore, by using the dictionary screen 1300, the user can simultaneously learn an example sentence using the word suitable for his / her learning level in addition to the meaning of the currently searched word.

  FIG. 19A is a diagram illustrating an example of a dictionary screen 1300 that displays related words of a word. In the dictionary screen 1300, the same parts as those in the dictionary screen 1300 shown in FIG. 18A are denoted by the same reference numerals, and description thereof is omitted. The dictionary screen 1300 includes a function selection unit P1301, a related word display unit 1306 that displays related words of the input word, and a search word display unit P1303.

  In this dictionary screen 1300, the user selects “related word” in the function selection unit P1301, inputs “welcome” as a word to be searched, and displays “synonyms: receive antonyms” in the related word display unit 1306 as related words of the word. : Unwelcome "etc. The content of the related word displayed on the related word display unit 1306 is obtained by using the learning history table 402 in which the word ID of the search word is recorded for each user ID, and the user learning level determination unit 107a uses the word ID of the user. It is determined by the learning level determination result determined from the result of summing up and the progress determination result of the learning level. Therefore, by using this dictionary screen 1300, the user can simultaneously learn related words of the word suitable for his / her learning level in addition to the meaning of the currently searched word.

  FIG. 20 is a diagram showing an example of a dictionary screen 1300 displaying the ranking of words searched in the past. In the dictionary screen 1300, the same parts as those in the dictionary screen 1300 shown in FIG. 18A are denoted by the same reference numerals, and description thereof is omitted. The dictionary screen 1300 includes a function selection unit P1301, a ranking display unit 1307 that displays words searched in the past in descending order, a search word display unit P1303, a ranking operation unit 1308 that instructs ranking display, Is provided.

  In this dictionary screen 1300, when the user operates “My Ranking” in the ranking operation unit 1308, the past word IDs of the user recorded in the learning history table 402 are aggregated, and the ranking display unit in the descending order of the number of searches. A list of search words is displayed at 1307. In this ranking display section 1307, as “1. welcome (Lv.1): 6, 2. tomorrow (Lv.1): 3, 3. real (Lv.1): 1, 4. realnumber (Lv. 4): 1, 5. world (Lv.1): 1 ”etc. are displayed. That is, the word with the largest number of searches is “welcome” six times, and the learning level is “1”. The following display contents are the same. Therefore, by using this dictionary screen 1300, the user can know the number of search times for the word that he has searched in the past, and can know the progress of his / her learning level.

  As described above, the dictionary function provided by the dictionary management unit 115 of the language learning device 101 allows the user to appropriately select each function of “sung phrase, example sentence, related word” in the function selection unit 1301 of the dictionary screen 1300. It is possible to display a composition sentence, example sentence, and related word suitable for the learning level of the person. In addition, the user can grasp the search history of the word searched in the past by operating “My Ranking” in the ranking operation unit 1308. Therefore, the language learning apparatus 101 can provide a dictionary function suitable for the user's learning level. Further, the user can use the dictionary function according to the progress of his / her learning level by using the dictionary screen 1300 of the language learning apparatus 101. In each of the above embodiments, the case where the language learning device is applied to English and Japanese as languages has been described. However, the present invention is not limited to these languages, and other languages such as Korean and Chinese can be used. Of course, it is applicable.

  Note that the functions of the respective units shown as the first to third embodiments and the dictionary function can also be provided as a storage medium that stores a program that can be read by the computer system. In addition, the user terminal may be a terminal having a function capable of executing communication and learning content with the language learning device 101 via the communication network 102, for example, a personal computer, a mobile phone, a portable information terminal. Etc. are applicable.

  DESCRIPTION OF SYMBOLS 100 ... Learning system 101 ... Language learning apparatus 102 ... Communication network 104 ... Language information management part 105 ... Content management part 106 ... User management part 107 ... Control part 107a ... User learning level determination part, 107b: Learning content recommendation unit, 107c: User recommendation unit, 111 ... Word management unit, 112 ... Text management unit, 113 ... Expression management unit, 114 ... Grammar management unit, 115 ... Dictionary management unit, 116 ... Content storage unit, 117: Content update unit, 118 ... Content creation unit, 119 ... Authentication unit, 120 ... Learning history management unit, 121 ... Communication analysis unit, 201 ... Word table, 202 ... Text table, 203 ... Expression table, 204 ... Grammar table, 301 ... Content table 401 ... User table 402 ... Learning history table 031~103Nn ... user terminal.

Claims (24)

A language learning device that provides a language learning environment to a plurality of user terminals connected via a communication network,
A user management unit for managing registration information of the plurality of users;
A content management unit for storing and managing a plurality of learning contents including words and phrases classified according to the grammar and examples of the language;
A language information management unit that stores and manages a plurality of the words and phrases that are each set with attribute information such as a learning level applied to a learning environment of the language;
A learning history management unit for accumulating and managing each attribute information of words and phrases included in the learning content selected by the user terminal in the learning environment of the language as a learning history for each user;
A user learning level determination unit that aggregates the attribute information set in the word and the phrase included in the learning content based on the learning history, and analyzes the aggregation result to determine a learning level for each user. When,
Based on the learning level for each user determined by the user learning level determination unit, the word and the phrase are extracted from the language information management unit, and the learning content suitable for the user is generated. A learning content recommendation section recommended for user terminals,
A language learning apparatus comprising: The language information management unit sets and manages attribute information such as the learning level for a plurality of grammatical information based on the grammar of the language and a plurality of expression information based on examples of the language,
The learning history management unit further accumulates and manages each attribute information of the grammar and the expression included in the learning content selected by the user's terminal for each user as a learning history,
The user learning level determination unit aggregates each attribute information of the grammar information and the expression information, analyzes the aggregation result and the aggregation result of the word and the phrase, and determines a learning level for each user. ,
The learning content recommendation unit extracts the learning content suitable for each user by extracting the word, the phrase, the grammar, and the expression from the language information management unit based on the determination result of the learning level for each user. The language learning device according to claim 1, wherein the language learning device is generated and recommended for a corresponding user terminal. The content management unit stores a plurality of learning contents including the word, the phrase, the grammar, and the expression and requesting pronunciation and answer from the user,
The learning history management unit learns the word, the phrase, the grammar, and the expression included in the user's pronunciation and answer to the learning content selected by the user's terminal in the language learning environment. The language learning apparatus according to claim 1, wherein the learning history is stored and managed for each user terminal as the learning history. The content management unit includes a tool for creating the learning content corresponding to the learning environment of the language using the word, the phrase, the grammar, and the expression managed by the language information management unit. Has a content creation section to provide
The learning history management unit uses, as the learning history, the usage history of the word, the phrase, the grammar, and the expression included in the learning content created by the user terminal using the tool for each user. Accumulate and manage,
The user learning level determination unit estimates a preference of language expression for each user based on the usage history,
The learning content recommendation unit extracts the word, the phrase, the grammar, and the expression from the language information management unit based on the preference of the language expression for each user estimated by the user learning level determination unit. 4. The language learning apparatus according to claim 1, wherein the learning learning content is generated for each user and recommended to the terminal of the corresponding user. 5. The user learning level determination unit aggregates the attribute information set in the word, the phrase, the grammar, and the expression included in the learning content based on the learning history, and analyzes the aggregation result. Determine the progress of the learning level for each user,
The learning content recommendation unit extracts the word, the phrase, the grammar, and the expression from the language information management unit based on the progress of the learning level for each user determined by the user learning level determination unit. 5. The language according to claim 1, wherein learning content suitable for the progress of the learning level is generated for each user and recommended to the terminal of the corresponding user. Learning device. The user learning level determination unit adjusts a learning range and a learning content in the learning environment of the language for each user based on the learning level for each user,
The learning content recommendation unit receives the word, the phrase, the grammar, and the expression from the language information management unit based on the learning range and the learning content adjusted for each user by the user learning level determination unit. 6. The language learning device according to claim 1, wherein the learning content suitable for each user is extracted and recommended to the terminal of the corresponding user.   The said user learning level determination part creates the past learning progress for every said user based on the said learning history for every said user, It provides with respect to the terminal of a corresponding user, It is characterized by the above-mentioned. The language learning device according to any one of 1 to 6. The user learning level determination unit aggregates the attribute information set in the word, the phrase, the grammar, and the expression based on the learning history for each user, and analyzes the aggregation result. To determine the learning tendency of multiple users,
User registration information extracted from the user management unit based on the learning tendency of a plurality of users determined by the user learning level determination unit from the user management unit. The language learning apparatus according to claim 1, further comprising a user recommendation unit that recommends the terminal. The language information management unit stores a plurality of words, phrases, grammars and expressions classified according to grammars and examples of languages other than the language to be learned, and attributes such as the learning level for the words, phrases, grammars and expressions Set and manage each information,
The content management unit accumulates and manages participatory content in which the user inputs text in the other language with respect to the learning content,
The learning history management unit further sets each word, phrase, grammar, and expression attribute information included in the sentence of the other language input in the participation type content by the user terminal as a learning history for each user. Accumulate and manage,
The user learning level determination unit totals the attribute information set in the word and the phrase included in the sentence of the other language input in the participatory content based on the learning history, and the aggregation result To determine the learning level for each user,
The learning content recommendation unit is suitable for each user by extracting the word, the phrase, the grammar, and the expression of the learning language from the language information management unit based on the determination result of the learning level for each user. The language learning device according to claim 1, wherein learning content of the learning language is generated and recommended to a corresponding user terminal. The learning history management unit accumulates and manages the attribute information of the word searched by the terminal of the user as the learning history for each user,
The user learning level determination unit totals the number of searches for the word for each user based on the learning history for each user,
The system further comprises a dictionary management unit that displays the words on a corresponding user terminal in accordance with the number of search times for each user based on the total number of search times of the word for each user. The language learning device according to any one of 1 to 9.   The dictionary management unit extracts phrases and sentences using the words searched by the user's terminal from the language information management unit based on attribute information of words included in the phrases and sentences, and the extracted phrases and sentences The language learning device according to claim 1, wherein the language learning device is displayed on a corresponding user terminal. The learning content management unit classifies a plurality of items used by the user in the participation type content by type, accumulates and manages the plurality of items by the classification,
The learning content recommendation unit estimates an object of interest for each user based on a learning history accumulated in the learning history management unit for each user by the sentence in the other language input in the participation type content, 12. The language learning apparatus according to claim 1, wherein an item is extracted from the plurality of items based on the estimation result and recommended to a corresponding user terminal. A language learning method executed by a language learning device that provides a language learning environment to a plurality of user terminals connected via a communication network,
The language learning device manages each registration information of the plurality of users,
The language learning device stores and manages a plurality of learning contents including words and phrases classified according to the grammar and examples of the language,
The language learning device stores and manages a plurality of language information including the word and the phrase, each of which is set attribute information such as a learning level applied to the language learning environment,
The language learning device accumulates and manages each user's attribute information of words and phrases included in the learning content selected by the user's terminal in the language learning environment as a learning history,
The language learning device aggregates the attribute information set in the word and the phrase included in the learning content based on the learning history, analyzes the aggregation result to determine a learning level for each user,
The language learning device extracts appropriate words and phrases from the plurality of words and phrases based on the determined learning level for each user, and generates learning content suitable for each user. Recommended for the corresponding user ’s device,
A language learning method comprising: The step of managing the language information includes the step of setting and managing attribute information such as the learning level for a plurality of pieces of grammatical information based on the grammar of the language and a plurality of pieces of expression information based on examples of the language. ,
The step of managing the learning history includes the step of further accumulating and managing each attribute information of the grammar and the expression included in the learning content selected by the user terminal as the learning history for each user. ,
The step of determining the learning level of the user includes aggregating the attribute information of the grammatical information and the expression information, and analyzing the aggregation result and the aggregation result of the word and the phrase to learn the learning level for each user. Including the step of determining
In the step of recommending the learning content, the word, the phrase, the grammar, and the expression are extracted from the language information management unit based on the determination result of the learning level for each user, and learning suitable for each user is performed. The language learning method according to claim 13, further comprising a step of generating content and recommending the content to a corresponding user terminal. The step of managing the learning content includes the step of storing a plurality of learning content that includes the word, the phrase, the grammar, and the expression and requests the user to pronounce and answer,
The step of managing the learning history includes the word, the phrase, the grammar, and the expression included in the user's pronunciation and answer for the learning content selected by the user's terminal in the language learning environment. 15. The language learning method according to claim 13, further comprising a step of accumulating and managing the number of learnings as the learning history for each user terminal. Managing the content includes providing a tool for creating the learning content corresponding to a learning environment of the language to the user terminal using the word, the phrase, the grammar, and the expression;
The step of managing the learning history includes using the word, the phrase, the grammar, and the expression usage history included in the learning content created by the user terminal using the tool as the learning history. Including further accumulating and managing by person,
The step of determining the learning level of the user includes the step of inferring a preference of language expression for each user based on the usage history,
In the step of recommending the learning content, the word, the phrase, the grammar, and the expression are extracted based on the estimated preference of the language expression for each user, and the learning content for each user is selected. The language learning method according to any one of claims 13 to 15, further comprising a step of generating and recommending the corresponding user terminal. The step of determining the learning level of the user totals the attribute information set in the word, the phrase, the grammar, and the expression included in the learning content based on the learning history, and calculates the total result. Analyzing and determining the progress of the learning level for each user,
The step of recommending the learning content includes extracting the word, the phrase, the grammar, and the expression based on the determined progress of the learning level for each user and determining the progress of the learning level for each user. The language learning method according to claim 13, further comprising a step of generating learning content suitable for the user and recommending the content to a corresponding user terminal. The step of determining the learning level of the user includes the step of adjusting the learning range and learning contents in the learning environment of the language for each user based on the learning level for each user,
In the step of recommending the learning content, the learning content suitable for each user is extracted by extracting the word, the phrase, the grammar, and the expression based on the learning range adjusted for each user and the learning content. The language learning method according to claim 13, further comprising a step of generating and recommending the corresponding user terminal.   The step of determining the learning level of the user includes a step of creating a past learning process for each user based on the learning history for the user and providing the learning level to the corresponding user terminal. The language learning method according to any one of claims 13 to 17, wherein: The step of determining the learning level of the user aggregates the attribute information set in the word, the phrase, the grammar, and the expression for each user based on the learning history for each user, Analyzing the results to determine learning trends for multiple users,
The language learning device extracts user registration information corresponding to the same learning tendency based on the determined learning tendency of the plurality of users from the registration information and recommends it to a user terminal corresponding as a learning companion The language learning method according to claim 13, wherein the language learning method is performed. The step of managing the linguistic information stores a plurality of words, phrases, grammars and expressions classified according to grammars and examples of languages other than the language to be learned, and the learning level etc. for the words, phrases, grammars and expressions Including setting and managing each attribute information of
The step of managing the content includes the step of accumulating and managing participatory content in which the user inputs text in the other language with respect to the learning content,
The step of managing the learning history further includes using each attribute information of the word, phrase, grammar, and expression included in the sentence of the other language input in the participation type content by the user terminal as the learning history. Including the stage of accumulating and managing by person,
The step of determining the learning level of the user aggregates the attribute information set in the word and the phrase included in the sentence of the other language input in the participatory content based on the learning history. Analyzing the aggregation results and determining a learning level for each user,
The step of recommending the learning content includes extracting the word, the phrase, the grammar, and the expression of the learning language based on the determination result of the learning level for each user to determine the learning language suitable for each user. 21. The language learning method according to claim 13, further comprising a step of generating learning content and recommending it to a corresponding user terminal. The step of managing the learning history includes the step of accumulating and managing the attribute information of the word searched by the terminal of the user as the learning history for each user,
The step of determining the learning level of the user includes a step of counting the number of searches of the word for each user based on the learning history for the user,
The language learning device displays a dictionary including the words in order of the number of search times for each user based on a result of counting the number of times of searching for the word for each user on a corresponding user terminal. The language learning method according to any one of claims 13 to 21.   The step of displaying the dictionary includes extracting phrases and sentences using the word searched by the user's terminal from the language information based on attribute information of words included in the phrases and sentences, and extracting the phrases and sentences extracted The language learning method according to any one of claims 13 to 22, further comprising a step of displaying on a corresponding user terminal. The step of managing the learning content includes a step of classifying a plurality of items used by the user in the participatory content according to type, and accumulating and managing the plurality of items according to the classification,
The step of recommending the learning content is to infer a target of interest for each user based on a learning history accumulated for each user by the sentence in the other language input in the participation type content, The language learning method according to any one of claims 13 to 23, further comprising: extracting an item from the plurality of items based on the recommendation and recommending the item to a corresponding user terminal.