TWM585415U - User-adapted language learning system - Google Patents

Abstract

A user-adapted language learning system includes a storage unit storing a language learning recommendation engine, plural learning outlines, plural language teaching materials, plural linguistics data, and plural user personal parameter data. The learning outlines have plural learning progress, each A language teaching material has a scoring value and a plurality of tags, respectively, the linguistic data corresponds to the language teaching materials, and the user's personal parameter data corresponds to the tags; and a processing unit is used to execute the language learning recommendation engine according to The user's personal parameter data selects the corresponding learning progress from the learning outlines, and the language learning recommendation engine selects the language teaching materials with higher scores according to the learning progress, and the languages with higher scores are selected. The teaching materials and the linguistic materials corresponding to the language teaching materials together form a humanized language learning teaching material.

Description

User-friendly language learning system

This creation is about a language learning system, especially a language learning system suitable for users.

According to the language learning, in the known online language learning platform, the majority of users can be guided by the language proficiency test in a short time, and the preset set of learning outlines and language teaching materials are filled in a duck style. The method is sent to plural users. Although this language learning method can make most users pass the language proficiency test in a short time. However, the above learning outline and language textbooks only improve the short-term memory of most users. Although effective in short-term intensive language learning courses, in the long run, users will quickly learn to fill the duck over time. The content is forgotten. For example, users from engineering, art, and financial backgrounds all use the same set of learning outlines and language teaching materials, or users learn the purpose of emotional expression, travel, and business, but they still use the same set Study outline and language teaching materials. To truly allow users to learn the language in depth, they must allow users to systematically, repeat memory, self-discovery, self-induction and keep interest in adaptive learning. In other words, the conventional online language learning platform cannot adaptively make the language learning process of users more efficient according to different users. Therefore, how to solve the above problems is the direction that researchers in this field should work hard.

One of the purposes of this creation is to provide a user-friendly language learning system that adaptively generates personalized language learning materials according to the background preferences of different users, evaluation results, learning conditions of teaching materials, and user behavior. In order to achieve the above purpose, this creation provides a user-friendly language learning system, including: a server-side device having: a storage unit storing a language learning recommendation engine and a language learning database group, the language learning data The library group includes a learning syllabus database, a language teaching material database, a linguistics database, and a user personal parameter database. The aforementioned learning syllabus database stores plural learning outlines, and these learning outlines have plural learning progress. The aforementioned language textbook database stores plural language textbooks, and these language textbooks each have a scoring value and plural labels. The aforementioned linguistic database stores plural language textbooks. These linguistic data correspond to these language textbooks. The personal parameter database of the user stores a plurality of user personal parameter data, and the user personal parameter data corresponds to the tags; and a processing unit is used to execute the language learning recommendation engine, and the language learning recommendation engine is based on these uses Personal parameter data of the student Progress, and the language learning recommendation engine selects the language textbooks with higher scores according to the learning progress, the language textbooks with higher scores and the languages corresponding to the language textbooks with higher scores are selected The learning materials together form a humanized language learning textbook. With the creation of this design, according to different user personal parameter data, different schedules of learning outlines and language textbooks and linguistic data of different topics can be selected to generate personalized language learning textbooks, thereby achieving a more efficient language learning process. .

The above-mentioned purpose of this creation and its structural and functional characteristics will be explained according to the preferred embodiments of the drawings. Please refer to FIG. 1, which is a block diagram of the first embodiment of a user-friendly language learning system for the author. As shown in the figure, the user-friendly language learning system for the author includes a server device 10. The server device 10 has a storage unit 11 and a processing unit 12. The storage unit 11 stores a language learning recommendation engine 111 and a language learning database group 112. The language learning database group 112 includes a learning outline database 1121, a language teaching material database 1122, and a linguistic database 1123. And a user personal parameter database 1124. The aforementioned learning outline database 1121 stores plural learning outlines, the learning outlines have plural learning progress, the aforementioned language teaching material database 1122 stores plural language teaching materials, and these language teaching materials each have a score value and a plural label. The aforementioned linguistic database 1123 stores plural linguistic data, the linguistic data corresponds to the language teaching materials, and the aforementioned user personal parameter database 1124 stores plural user personal parameter data. The learning progress of the learning outline of the learning outline database 1121 is the learning progress of plural letters, plural vocabulary, plural part-of-speech vocabulary and plural grammar listening, speaking, reading, and writing, for example, based on, Beginner, Advanced, Intermediate, Advanced. The language teaching materials of the language teaching material database 1122 are plural online videos, plural online articles, and plural voice files. The online videos, the online articles, and the voice files each have an original text, and The original texts have plural lexical classification values, plural sentence classification values, plural text paragraph classification values, plural part-of-speech classification values, plural grammar classification values, and plural text topic classification values, respectively. The source of online videos in these language textbooks is, for example, but not limited to Youtube, and the source of online articles in these language textbooks is, for example, but not limited to Wikipedia. The linguistic data of the linguistic database 1123 includes a core word, a vocabulary frequency, a synonym, an antonym, a related word, a root word, a cognate word, and a pseudo-synonym. Any one or any combination of them. The core word is, for example, a core word in a Swadis core word list, and the vocabulary use frequency is, for example, high, medium, and low use frequency words. The vocabulary in the core word list is a high use frequency word. Words other than the list are further divided into medium and low frequency words. The synonyms are, for example, consent and approval, the antonyms are, for example, happiness and sadness, and the related words are, for example, chicken, pork, and vegetables. The same root word For example, enable, capable, agreeable in English. The cognate words are, for example, Chinese students and Korean puppets. The pseudo cognate words, for example, Japanese are barely meaning to study hard, and Chinese barely is far-fetched and unnatural. Meaning, the pseudo-synonym is a vocabulary that looks like a cognate word, but actually has different semantics. The user personal parameter data of the user personal parameter database 1124 includes at least one user background preference data 1124a, at least one user evaluation result data 1124b, at least one user teaching material learning status data 1124c, and at least one user Any of the behavior data 1124d or any combination thereof. The at least one user background preference information 1124a corresponds to the tags of the language teaching materials. The at least one user background preference information 1124a includes at least one learning motivation purpose, at least one learning topic area, at least one interest type, and at least one interest. Any one or any combination of attributes and the length of at least one video or article. The at least one learning motivation purpose includes commercial purpose, living purpose, and travel purpose in this embodiment, but is not limited thereto. In other embodiments, the at least one learning motivation purpose may also include other purposes. The at least one learning theme The field in this embodiment includes the field of cooking, the field of emotional expression, the field of law, and the field of machinery, but is not limited to this. In other embodiments, the at least one learning topic area may also include other topic areas. The at least one type of interest In this embodiment, the record report, drama and music are included, but it is not limited to this. In other embodiments, the at least one interest type may also include other interest types. The at least one interest attribute includes comedy, horror in this embodiment. , Plot, and actor, but is not limited to this. In other embodiments, the at least one interest attribute may also include other interest attributes. The length of the at least one movie or article includes a short movie or article and a long movie in this embodiment. Or articles, but it is not limited to this, in other embodiments, videos of other lengths or Chapter. The commercial, domestic, tourist, cooking, emotional, legal, mechanical, documentary, drama, music, comedy, horror, plot, actor, short film or article, and long film or article are respectively Has a classification value corresponding to those language textbooks. The at least one user evaluation result data 1124b includes at least one characteristic value of listening evaluation results, at least one characteristic value of speaking evaluation results, at least one characteristic value of reading evaluation results, and at least one characteristic value of writing evaluation results. The characteristic values of the evaluation results, the characteristic values of the oral evaluation results, the characteristic values of the reading evaluation results, and the characteristic values of the writing evaluation results correspond to these learning progress respectively. If the hearing evaluation result is better, the characteristic value of the at least one hearing evaluation result is higher; otherwise, if the hearing evaluation result is worse, the characteristic value of the at least one hearing evaluation result is lower. The eigenvalue of the assessment result is higher, otherwise, the verbal assessment result is worse, the at least one utterance assessment result has a lower eigenvalue, and the reading evaluation result is better, the at least one reading assessment result has a higher eigenvalue, otherwise, the reading evaluation If the evaluation result is poor, the characteristic value of the at least one reading evaluation result is low; if the writing evaluation result is good, the characteristic value of the at least one writing evaluation result is high; otherwise, if the writing evaluation result is poor, the characteristic of the at least one writing evaluation result is low The value is lower. And the higher the eigenvalue, the lower the weight, and the lower the eigenvalue, the higher the weight. The at least one user's teaching material learning status data 1124c includes a characteristic value of the number of clicks and a characteristic value of the viewing time of the language teaching materials and the linguistic information. The characteristic value of the number of clicks and the characteristic value of the viewing time are relatively high, so the language teaching materials and the linguistic materials corresponding to the language teaching materials are set to have a higher weight, and have a higher number of clicks and a longer viewing time of the part of the language teaching material. Other language textbooks with the same label are also set to have a higher weight. The at least one user behavior data 1124d includes a retrieval behavior characteristic value, a viewing behavior characteristic value, and a marking behavior characteristic value of the language teaching materials and the linguistic data. The characteristic value of the retrieval behavior and the characteristic value of the viewing behavior are relatively high, so the language teaching materials and the linguistic materials corresponding to the language teaching materials are set to have a higher weight, and have the part with more searches and more views. The language textbooks with the same label are also set to have a higher weight, and one of the marking behaviors is a tag that is more familiar or uninteresting to the user, then the marking behavior has a lower characteristic value, and the other marking behavior is the user The less familiar or interesting mark, the higher the behavioral value of the mark, the lower the weight of the language textbook, the lower the weight of the mark, the higher the value of the textbook In order to have a higher weight, other language textbooks with the same label as those language textbooks with a lower characteristic value of the marked behavior are also set to have a lower weight. Has a high value and behavior characteristics of the tag language such other language teaching materials with the same label is also set to a higher weight. The storage unit 11 may be or may include one or more hard disk drives (HDD), hard disk arrays (Redundant Array of Independent Disks, RAID), solid state disks (Solid State Disk, SSD), and flash memory. Flash memory, Electronically Erasable Programmable Read Only Memory (EEPROM), USB flash drive, SD memory card, CF memory card, XD memory card, and other similar devices or these devices The combination. The processing unit 12 is configured to execute the language learning recommendation engine 111. The language learning recommendation engine 111 selects a corresponding learning progress from the learning outlines according to the user personal parameter data. The processing unit 12 executes the language learning The recommendation engine 111 calculates the vocabulary classification values, the sentence classification values, the text paragraph classification values, the part-of-speech classification values, the grammatical classification values, And other text subject classification values, and the at least one user background preference information 1124a correspond to the commercial use, living use, travel use cooking area, emotional expression area, legal area, machinery area, record report, Drama, music, comedy, horror, plot, actor, short film or article and long film or article classification value, and the at least one hearing evaluation result feature value of the at least one user evaluation result data 1124b, the at least one mouthful The characteristic value of the evaluation result, the characteristic value of the at least one reading evaluation result, and the characteristic of the at least one writing evaluation result. Value, and the clicked-time feature value and the viewing time feature value of the at least one user teaching material learning status data 1124c, and the retrieval behavior feature value, the viewing behavior feature value, and the at least one user behavior data 1124d. The behavior characteristic value is marked, and the score value is generated. And the language learning recommendation engine 111 selects the language textbooks with higher scores according to the learning progress, the language textbooks with higher scores and the linguistics corresponding to the language textbooks with higher scores. The materials together form a humanized language learning textbook. The processing unit 12 may be or may include one or more programmable general-purpose or special-purpose microprocessors (Microprocessors), central processing units (CPUs), and digital signal processors (Digital Signal Processors). (DSP), programmable controller, application specific integrated circuits (ASIC), programmable logic device (programmable logic device (PLD)), and other similar devices or combinations of these devices. The processing unit 12 stores the plurality of original texts of the subtitles of the web videos, the plurality of original texts of the web articles, and the plurality of original texts formed by the speech files after speech recognition into the storage unit 11. The storage unit 11 has a natural language processing module 113. The natural language processing module 113 has a textbook analysis processing unit 1131 and a text analysis and statistics unit 1132. The processing unit 11 analyzes these through the textbook analysis processing unit 1131. The original text generates the words, the sentences, and the text paragraphs, and the processing unit 11 analyzes the words through the text analysis and statistics unit 1132 to generate the part of speech, analyzes the sentences to generate the grammars, and analyzes the texts. Paragraphs produce such textual themes. The words have a lexical classification value, the sentences have a sentence classification value, the text paragraphs have a text paragraph classification value, the part of speech has a part of speech classification value, and the grammars have a grammatic classification. Value, the text topics each have a text topic classification value. The following is a description of a specific embodiment, and please refer to FIG. 3, which is a block diagram of a specific embodiment of a first embodiment of a language learning system suitable for a creative user. As shown in the figure, the user described in this creative The server device 10 of the adaptive language learning system is connected to a user terminal device 20 and a management device 30 through an Internet 40. The user terminal device 20 is operated by at least one user. The management device 30 is operated by at least one manager. This case is to set the user terminal device 20 as one for convenience of explanation, but it is not limited to this. In other embodiments, the user terminal device 20 may also be A plurality of user terminal devices 20. The user terminal device 20 is, for example, a computer or a smart mobile device and has a screen, a speaker, and a microphone. The management terminal device 30 is, for example, a computer. The management-end device 30 is used by the administrator to establish the learning outlines through the Internet 40 in the learning outline database 1121 of the language learning database group 112 of the server-side device 10. In this embodiment, the learning outline systems are It is expressed as the progress of English listening, speaking, reading, and writing, such as the basic, early, advanced, intermediate, and advanced progress of English. Next, the source of these language teaching materials shall be explained, including the first one is that the administrator collects the online videos and the online articles as the language teaching materials through the management terminal device 30, and the second is that the user uses the The user terminal device 20 collects the online videos and the online articles as the language teaching materials, and the third is that the administrator collects the online videos and the online articles through the management terminal device, and The user produces the subtitles of the online videos or the translation of the online articles as the language teaching materials through the user terminal device, and the fourth is the manager or the user through the management terminal device or the user respectively The plurality of voice files collected by the terminal device, and the language teaching materials are all stored in the language teaching material database 1122 of the language learning database group 112 of the server device 10 through the Internet 40. Regardless of the source of the language textbooks, the manager will analyze the original texts to generate the vocabulary classification values, the sentence classification values, the text paragraphs, and the part of speech of the language textbooks. , These grammars and text themes, and classify these online videos and these online articles and these voice files based on part-of-speech, grammar, and text themes, and form parts of speech, grammar, and subject areas corresponding to these language textbooks. label. In addition, according to the sentences and text paragraphs, categorize the online videos, the online articles, and the voice files and form the motivational use, interest type, interest attribute, video or article length corresponding to the language teaching materials. Tag of. In addition to the above-mentioned tags generated by analyzing the original texts, users or administrators can also add tags to these language textbooks. The user terminal device 20 is for a user to register, log in and enter the at least one user background preference data 1124a, and transmit the at least one user background preference data 1124a to the server device 10 through the Internet 40. The language learning database group 112 is stored using the personal parameter database 1124. In this embodiment, the at least one learning motivation purpose of the at least one user background preference data 1124a is represented as a life purpose, and the at least one learning subject area is represented by For the culinary field, the at least one interest type is represented as a drama, the at least one interest attribute is represented as a plot, and the length of the at least one movie or article is represented as a short movie. When a user registers and logs in through the user terminal device 20, the user personal parameter database 1124 of the server device 10 receives user behavior data 1124d, such as the first login, and no corresponding user has yet been generated Evaluation result data 1124b and user teaching material learning status data 1124c, so the processing unit 12 of the server device 10 executes the language learning recommendation engine 111 based on the above user evaluation result data 1124b, user teaching material learning status data 1124c, and The user behavior data 1124d is used as the user's personal parameter data, and corresponding learning progress is selected from such learning outlines, such as listening, speaking, reading, and writing of basic letters or basic vocabulary. But it is not limited to this. In another embodiment, the first login and the corresponding user evaluation result data 1124b and user teaching material learning status data 1124c have not been generated, so the processing unit 12 of the server device 10 executes the language The learning recommendation engine 111 selects the corresponding learning progress from the learning outlines according to the user background preference data 1124a of other users who have the same or similar information. After selecting the corresponding learning progress, the language learning recommendation engine 111 selects a corresponding part of the language teaching materials from the language teaching materials according to the learning progress and the user background preference information 1124a in the user's personal parameter data. The part of the language teaching materials and the linguistic materials corresponding to the part of the language teaching materials together form the personalized language learning teaching material displayed on the screen of the user terminal device 20 through the Internet 40. The number of clicks and viewing time of the personalized language learning textbook of the basic learning progress are recorded in the user's personal parameter database 1124 to form the user's textbook learning status data 1124c. The number of clicks and viewing time can represent the user's response to the Familiarity with some language textbooks and these linguistic materials. A large number of clicks and long viewing time indicates that the tag users in these language textbooks are more familiar. A few clicks and short viewing time indicate the label users in these language textbooks. The stranger. The language learning recommendation engine 111 updates other personalized language textbooks that are relatively unfamiliar and unfamiliar to the user and the linguistic data corresponding to other personalized language textbooks according to the user's textbook learning status data 1124c. The personalized language The learning materials are displayed on the screen of the user terminal device 20 through the Internet 40. And the user can choose to perform listening, speaking, reading, and writing assessment. The hearing assessment result data is, for example, playing a listening question through the speaker of the user terminal device 20, and the user uses the user terminal device on the user terminal device. 20, the spoken evaluation result data is, for example, receiving the user's audio through the microphone of the user terminal device 20, and the user terminal device 20 transmits the audio to a server included in the server device 10 The audio waveform comparison unit (not shown) performs audio waveform comparison. The reading evaluation result data is, for example, selection or filling of answers through the user terminal device 20, and the writing evaluation result data is, for example, The user terminal device 20 answers by typing, and the user terminal device 20 transmits the answer result to the server device 10, and checks the vocabulary, part of speech, and grammar through the natural language processing module 111. The above-mentioned listening, speaking, reading and writing evaluation result data is recorded in the user's personal parameter database 1124 to form the user evaluation result data 1124b, and the language learning recommendation engine 111 is based on the above user evaluation result data 1124b. Select the corresponding learning progress. Those with better evaluation results can choose to upgrade from the basic to the preliminary learning outline. If the evaluation results are poor, they can choose to strengthen the basic learning outline. The selection of these learning outlines can be used to update This personalized language learning textbook. In addition, in addition to the personalized language learning textbook generated by the language learning recommendation engine 111, the user can also search the language textbooks and the linguistic materials through the user terminal device 20, the language textbooks and the The retrieval behavior of the linguistic data and the viewing behavior after the retrieval are recorded in the user's personal parameter database 1124 to form the user behavior data 1124d, and the retrieval behavior and viewing behavior may represent the user to the retrieved language teaching materials And the degree of demand for such linguistic materials, a large number of retrievals and a high number of views indicate that the more demanding and more interesting the language teaching materials of the user are, the higher the retrieval behavior characteristic value and the viewing behavior characteristic value are, the lower the retrieval frequency and the lower the number of views The less required and less interested the language teaching materials are, the lower the retrieval behavior characteristic value and the viewing behavior characteristic value are. In addition, the user may mark the part of the language teaching materials and the linguistic materials corresponding to the part of the language teaching materials through the user terminal device 20. The marking behavior is marked as more interesting and less familiar. Language textbooks and linguistic materials have higher marked behavioral characteristic values, and the marked behaviors can also be less interesting and familiar language textbooks and linguistic materials with lower marked behavioral characteristic values and retrieve behavioral characteristic values The viewing behavior feature value and the marking behavior feature value are calculated or updated by the language learning recommendation engine 111, or the personalized language learning textbook is displayed on the screen of the user terminal device 20 through the Internet 40. Furthermore, when a plurality of users use a plurality of user terminal devices 20, the language learning recommendation engine 111 can also compare the at least one user background preference data 1124a of the users of this embodiment with other users, When comparing other users with the same user background preference data 1124a, the language learning recommendation engine 111 may further adjust the classification value weight of the tags according to the corresponding tags in the personalized language learning textbooks of other users. High, after the language learning recommendation engine 111 calculates, the personalized language learning textbook is updated or generated and displayed on the screen of the user terminal device 20 through the Internet 40. In addition, the language learning recommendation engine 111 may select other language teaching materials with the same label as the part of the language teaching materials to form the personalized language learning teaching material through the tags of the part of the language teaching materials, and use the tags of the other language teaching materials. Then select, for example, the part of the language teaching materials selected by the language learning recommendation engine 111 has a travel tag, and the language learning recommendation engine 111 may select other language teaching materials with a travel tag to form the personalized language learning textbook, and the other languages The textbook also has the tags of tourism, business and music. The language learning recommendation engine 111 may further select other language textbooks with business and music tags to form the personalized language learning textbook. In this way, users can gradually see more language teaching materials. By creating this design, the user's language learning process can be more efficiently adapted to different users. The creation has been described in detail above, but the above is only a preferred embodiment of the creation, and the scope of implementation of the creation cannot be limited. That is to say, all equal changes and modifications made in accordance with the scope of this creative application shall still be covered by the patent of this creative.

10‧‧‧Server Equipment

11‧‧‧Storage Unit

111‧‧‧ language learning recommendation engine

112‧‧‧Language Learning Database Group

1121‧‧‧Learning Outline Database

1122‧‧‧ Language Teaching Materials Database

1123‧‧‧ Linguistics Database

1124‧‧‧User personal parameter database

1124a‧‧‧User background preference data

1124b‧‧‧User evaluation result data

1124c ‧‧‧ User learning materials

1124d‧‧‧User Behavior Data

113‧‧‧ Natural Language Processing Module

1131‧‧‧ Textbook Analysis and Processing Unit

1132‧‧‧Text Analysis Statistics Unit

12‧‧‧ processing unit

20‧‧‧User terminal equipment

30‧‧‧Management Device

40‧‧‧Internet

Figure 1 is a block diagram of an embodiment of a language learning system suitable for creative users; Figure 2 is a block diagram of a user parameter database of a language learning system suitable for creative users; Figure 3 is This is a block diagram of a specific embodiment of a language learning system suitable for a creative user.

Claims (16)

A user-friendly language learning system includes: a server-side device having: a storage unit storing a language learning recommendation engine and a language learning database group, the language learning database group including a learning outline database , A language teaching materials database, a linguistics database and a user's personal parameter database, the aforementioned learning outline database stores plural learning outlines, the learning outlines have plural learning progress, and the aforementioned language teaching material database stores plural languages Textbooks, each language textbook has a scoring value and plural labels, the aforementioned linguistic database stores plural linguistic data, the linguistic data corresponds to these language teaching materials, and the aforementioned user's personal parameter database stores plural uses Personal parameter data of the user; and a processing unit for executing the language learning recommendation engine, the language learning recommendation engine selects corresponding learning progress from the learning outlines according to the user personal parameter data, and the language learning recommendation engine According to the learning progress, select the higher score Such linguistic data language teaching materials, selected the higher scores of such language teaching materials and higher scores corresponding to such language teaching materials together to form a human language learning materials. The user-adapted language learning system described in item 1 of the scope of the patent application, wherein the user personal parameter data includes at least one user background preference data, at least one user evaluation result data, and at least one user teaching material learning Any one or a combination of status data and at least one user behavior data. According to the user-appropriate language learning system described in item 2 of the patent application scope, wherein the at least one user background preference data corresponds to the tags of the language teaching materials, and the at least one user background preference data includes at least one learning Any one or any combination of motivational uses, at least one learning subject area, at least one interest type, at least one interest attribute, and at least one video or article length. The user-appropriate language learning system according to item 3 of the scope of the patent application, wherein the at least one learning motivation purpose includes commercial use, life use, and travel use, and the at least one learning subject area includes cooking field, emotion expression field, law Field and mechanical field, the at least one interest type includes documentary reports, drama and music, the at least one interest attribute includes comedy, horror, plot and actor and the length of the at least one film or article includes short films or articles and long films or articles , The commercial use, domestic use, travel use cooking area, emotional expression area, legal area, machinery area, documentary, drama, music, comedy, horror, plot, actor, short film or article and long film or article are respectively Has a classification value corresponding to those language textbooks. The user-adapted language learning system according to item 2 of the scope of patent application, wherein the at least one user evaluation result data includes at least one characteristic value of hearing evaluation result, at least one characteristic value of speaking evaluation result, and at least one reading The characteristic value of the evaluation result and at least one characteristic value of the writing evaluation result, the characteristic value of the listening evaluation result, the characteristic value of the oral evaluation result, the characteristic value of the reading evaluation result, and the characteristic value of the writing evaluation result respectively correspond to these Learning progress. According to the user-appropriate language learning system described in item 2 of the scope of the patent application, wherein the at least one user textbook learning status data includes the language textbooks and the linguistic data with a click count characteristic value and a viewing time Eigenvalues. According to the user-appropriate language learning system described in item 2 of the scope of the patent application, wherein the at least one user behavior data includes a retrieval behavior characteristic value, a viewing behavior characteristic value, and a viewing behavior characteristic value of the language teaching materials and the linguistic information, and A marker behavior characteristic value. The user-adapted language learning system described in item 1 of the scope of the patent application, wherein the learning progress is the plural, plural, vocabulary, part-of-speech and plural grammar listening, speaking, reading, writing Learning progress. According to the user-appropriate language learning system described in item 1 of the scope of the patent application, the language teaching materials are plural online videos, plural online articles and plural voice files, such online videos, such online articles And these voice files each have an original text, and these original texts have plural vocabulary classification values, plural sentence classification values, plural text paragraph classification values, plural part-of-speech classification values, plural grammar classification values, and plural text topic classification values, respectively. The user-appropriate language learning system described in item 1 of the scope of patent application, wherein the linguistic data includes a core word, a vocabulary frequency, a synonym, an antonym, a related word, a root word, a Any one or any combination of a cognate word and a pseudo-cognate word. The user-friendly language learning system according to item 9 of the scope of the patent application, wherein the processing unit is a plurality of original texts of the subtitles of the web videos, a plurality of original texts of the web articles, and the voice files The plurality of original texts formed after speech recognition are stored in the storage unit. According to the user-appropriate language learning system described in item 9 of the scope of patent application, wherein the storage unit has a natural language processing module, the natural language processing module has a textbook analysis processing unit and a text analysis statistics unit, the The processing unit analyzes the original text to generate plural vocabulary classification values, plural sentence classification values, and plural text paragraph classification values through the textbook analysis processing unit, and the processing unit analyzes the words to generate plural part-of-speech classification values through the text analysis statistics unit, Analyzing the sentences produces plural grammatical classification values and analyzing the text paragraphs produces plural text topic classification values. The user-friendly language learning system according to item 1 of the scope of the patent application, wherein the server device is connected to at least one user terminal device through an Internet. The user-friendly language learning system according to item 13 of the scope of the patent application, wherein the user terminal device stores a plurality of original texts into the storage unit. The user-friendly language learning system according to item 1 of the scope of the patent application, wherein the server device is connected to a management device through an Internet. The user-friendly language learning system according to item 15 of the scope of the patent application, wherein the management device stores a plurality of original texts into the storage unit.