Chinese reading teaching network platform

Abstract

In view of the technical problems of low classroom knowledge retention rate and high reading threshold of overseas Chinese learners due to lack of target language application scene, a general reading teaching network platform is disclosed, which is closely coupled with intensive reading course progress through artificial intelligence technology, and an indication set of general reading article generation is constructed based on a dynamic Chinese character list, a learned Chinese character list, an unknown Chinese character list, a forgotten Chinese character list and individualized parameters of a learner, the indication set further including rules such as Chinese character usage range limitation, article length control, suitable reading age matching and theme screening, general reading content conforming to language acquisition rules and accurately adapted to the learning needs of individual learners is generated through calling an AI tool, and is pushed to a target user terminal in a targeted manner. The technical solution optimizes the Chinese character cognitive load in general reading, realizes instant consolidation of intensive reading knowledge, solves the technical defects of traditional general reading content dispersion and low efficiency, and significantly improves the accuracy and effectiveness of Chinese general reading learning.

Description

Technical Field

[0001] This invention belongs to the field of Chinese teaching technology, specifically relating to a method and system for generating and pushing Chinese extensive reading learning materials, and is particularly suitable for a Chinese extensive reading teaching network platform that dynamically adapts to the progress of Chinese intensive reading courses by generating personalized extensive reading content. Background Technology

[0002] In existing technologies, overseas Chinese learners lack target language application scenarios, resulting in the inability to consolidate classroom intensive reading content in a timely manner and a low knowledge retention rate. Although Chinese learners possess basic listening and speaking skills, insufficient Chinese character accumulation creates reading barriers, making it difficult to reinforce knowledge through traditional extensive reading materials. These problems create a negative cycle of "insufficient character knowledge - limited reading ability - difficulty in knowledge consolidation." Traditional extensive reading materials, because they are not dynamically adapted to the learners' existing Chinese character range, suffer from technical defects such as excessively high reading thresholds and a disconnect between content and learning progress. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention discloses a Chinese extensive reading teaching network platform closely coupled with Chinese intensive reading courses. The platform constructs a new character list by acquiring the new characters recently learned by the learner in the intensive reading course; constructs a learned character list by acquiring all Chinese characters previously learned in the intensive reading course; acquires extensive reading article generation parameters and rules; constructs an extensive reading article generation instruction set based on the new character list, the learned character list, and the parameter rules; invokes artificial intelligence tools to generate extensive reading articles according to the instruction set; and pushes the generated extensive reading articles to the target learner's terminal.

[0004] To achieve precise matching of personalized learning needs for Chinese learners, this invention, after generating the first extensive reading article, further detects unfamiliar Chinese characters during the learner's reading process using automatic or semi-automatic methods and adds them to an unfamiliar character list; characters in the unfamiliar character list that belong to the learned character list are transferred to a forgotten character list; when subsequent extensive reading articles are generated, characters from the forgotten character list are included in the article with high priority; the detection of unfamiliar characters is achieved through methods such as eye movement tracking, eye reflection imaging analysis, speech comparison, or user interaction marking. Eye movement tracking includes collecting eye movement parameters and reading distance through a camera, locating paused characters, and determining them as unfamiliar characters after user confirmation; speech comparison includes collecting the reading voice signal and comparing it with standard pronunciation, determining unpronounced or incorrectly pronounced characters as unfamiliar characters. Specifically,

[0005] The Chinese extensive reading teaching network platform disclosed in this invention includes: at least one processor; at least one memory communicatively connected to the at least one processor; the memory stores computer-executable instructions; when executed by the at least one processor, the computer-executable instructions cause the at least one processor to perform the following steps:

[0006] The task of generating general reading articles can be initiated by the user or by at least one processor according to the network platform settings.

[0007] Get the new words that Chinese learners have recently learned in their intensive Chinese reading courses and add them to the new word list;

[0008] Get all the Chinese characters that Chinese learners have previously learned in intensive Chinese reading courses and add them to the list of learned characters;

[0009] Obtain other parameters and rules for generating extensive reading articles for Chinese learner users;

[0010] Based on the list of new characters, the list of learned characters, and the other parameters and rules, an instruction set for generating extensive reading articles is constructed.

[0011] Use the above set of instructions to invoke AI tools to generate general reading articles; and

[0012] The generated general reading articles will be pushed to Chinese learner users.

[0013] Furthermore, the other parameters and rules include at least one of the following:

[0014] Word count of articles for general reading;

[0015] The subject matter of the articles to be read extensively;

[0016] Extensive reading article genres;

[0017] The style of extensive reading articles;

[0018] Suitable age range for extensive reading articles;

[0019] The number of Chinese characters not included in the learned character list can be used in extensive reading articles;

[0020] The percentage of Chinese characters not included in the learned character list is limited in extensive reading articles;

[0021] Content that should not be included in extensive reading articles;

[0022] The number of words in the vocabulary list included in extensive reading articles;

[0023] The priority of including characters from the vocabulary list in extensive reading articles; and

[0024] Besides Chinese characters, other language elements and language points that need to be included in extensive reading articles.

[0025] Furthermore, the method for obtaining other parameters and rules for generating extensive reading articles for Chinese learner users includes:

[0026] The network platform is pre-configured;

[0027] Provided by teachers of intensive reading courses;

[0028] Provided by Chinese learners;

[0029] Provided by parents of Chinese learners;

[0030] Provided by other users;

[0031] Extracting or exporting from intensively studied textbooks; and

[0032] Extract or export from the network resources specified by the Chinese intensive reading course teacher user or the network platform.

[0033] Furthermore, the generation of extensive reading articles further includes generating practice questions that complement the extensive reading articles.

[0034] Furthermore, the steps further include at least one of the following steps:

[0035] Store the aforementioned general reading articles;

[0036] A record of the content pushed to each Chinese learner user;

[0037] Before pushing the generated extensive reading articles to Chinese learner users, the generated extensive reading articles are submitted for manual review and approval;

[0038] Send the generated extensive reading articles to teachers of intensive reading courses;

[0039] Send confirmation of the extensive reading article push to intensive reading course teachers;

[0040] Send push notifications of extensive reading articles to Chinese learner users;

[0041] When displaying extensive reading articles to Chinese learner users, the Chinese characters in the vocabulary list are displayed differently;

[0042] Collect and store information about Chinese learners' reading of extensive reading articles;

[0043] The collected information on Chinese learners reading extensive reading articles will be reported to intensive reading teachers.

[0044] The collected information on the Chinese learner users' reading of extensive reading articles will be reported to the management user;

[0045] The collected information on the Chinese learner's reading of extensive reading articles will be reported to the learner's parents; and

[0046] We collect and store feedback from Chinese learners who read extensive reading articles, making it available for intensive reading teachers and administrators to access.

[0047] Furthermore, the information regarding the Chinese learner user's reading of extensive reading articles includes at least one of the following:

[0048] Number of articles read for general reading purposes;

[0049] Word count of articles read in general reading;

[0050] The percentage of articles already read out of the total number of articles pushed out;

[0051] Reading time for general reading articles;

[0052] The ratio of word count to reading time in extensive reading articles;

[0053] The number of extensive reading exercises completed;

[0054] The accuracy rate of extensive reading practice questions; and

[0055] The settings status of user parameters and usage modes when Chinese learners are reading.

[0056] Furthermore, the step of "calling AI tools to generate general reading articles" further includes the following steps:

[0057] Verify whether the generated extensive reading articles meet all the requirements of the indicator set;

[0058] If any aspects are found to be non-compliant during the verification process, the generated general reading article will be sent back to the AI ​​tool and a set of modification instructions will be provided for those non-compliant aspects.

[0059] AI tools generate modified general reading articles;

[0060] Repeat the above three steps until the verification meets the requirements of the instruction set, or the maximum set number of repetitions is reached, then exit the repetition;

[0061] If the modified extensive reading articles still do not meet the requirements of the specified instruction set upon exit, the intensive reading teacher will be prompted for manual intervention; and

[0062] Submit the revised or manually-intervened extensive reading articles to the next steps.

[0063] Further, at least one processor; at least one memory communicatively connected to the at least one processor; the memory storing computer-executable instructions; characterized in that:

[0064] When the computer-executable instructions are executed by the at least one processor, the at least one processor causes the at least one processor to perform the following steps:

[0065] The task of generating general reading articles can be initiated by the user or by at least one processor according to the network platform settings.

[0066] If the Chinese learner is using the online platform for the first time, create a list of characters the learner has already learned, a list of characters they do not know, and a list of characters they have forgotten, and initialize these lists to be empty.

[0067] Get the new words that Chinese learners have recently learned in the Chinese intensive reading course and compile a list of new words for that Chinese learner;

[0068] Retrieve all the Chinese characters that a Chinese learner user has previously learned in a Chinese intensive reading course and add them to the user's list of learned characters;

[0069] Extract the lists of unfamiliar and forgotten characters from Chinese learner users;

[0070] Get other parameters and rules for generating extensive reading articles for Chinese learner users;

[0071] Based on the aforementioned list of new characters, list of learned characters, list of unfamiliar characters, and list of forgotten characters, as well as the aforementioned other parameters and rules, construct an instruction set for generating extensive reading articles;

[0072] Use the above set of instructions to invoke AI tools and generate articles for general reading.

[0073] The generated extensive reading articles will be pushed to the Chinese learner user.

[0074] When Chinese learners read the above-mentioned extensive reading articles, the system automatically or semi-automatically detects any characters they do not recognize and adds them to their list of unfamiliar characters. It also removes characters that they recognize from the list of unfamiliar characters.

[0075] Add the characters from the list of unfamiliar characters that belong to the list of learned characters above to the list of forgotten characters;

[0076] When encountering characters while reading the aforementioned extensive reading articles, if the online platform automatically or semi-automatically detects that the Chinese learner recognizes a character but it is not listed in their learned character list, it will add that character to the learned character list; and

[0077] Repeat the steps above.

[0078] Furthermore, the other parameters and rules for generating general reading articles include at least one of the following:

[0079] The characters contained in the aforementioned list of new characters will be included in the extensive reading articles with high priority;

[0080] The words included in the forgotten word list will be included in the extensive reading articles with high priority;

[0081] The words in the list of unfamiliar words that are not in the list of forgotten words are included in the extensive reading articles in an appropriate amount or not, depending on their frequency of use.

[0082] Word count of articles for general reading;

[0083] The subject matter of the articles to be read extensively;

[0084] Extensive reading article genres;

[0085] The style of extensive reading articles;

[0086] Suitable age range for extensive reading articles;

[0087] The number of Chinese characters used in extensive reading articles that are not on the aforementioned list of learned characters is limited;

[0088] The number of characters used in extensive reading articles that are not on the previously learned character list is limited.

[0089] Content that should not be included in extensive reading articles;

[0090] The number of words in the vocabulary list included in extensive reading articles;

[0091] The priority of including characters from the vocabulary list in extensive reading articles; and

[0092] Besides Chinese characters, other language elements and language points that need to be included in extensive reading articles.

[0093] Furthermore, when the Chinese learner user reads the extensive reading article, the network platform automatically or semi-automatically detects characters in the text that the Chinese learner user does not recognize, including the following steps;

[0094] Use a camera image sensor to capture eye movement information of Chinese learners while reading;

[0095] The system determines the Chinese character corresponding to the eye movement and pausing based on the angle of eye movement and the reading distance of the Chinese learner detected by the camera.

[0096] The Chinese characters corresponding to pauses are marked as characters that are highly unlikely to be recognized, and at appropriate times, Chinese learner users are prompted to confirm their recognition of these characters using body language, voice, or user interface devices; and

[0097] The confirmed characters were identified as unfamiliar characters.

[0098] Furthermore, it further includes using a camera image sensor to acquire image information of Chinese characters displayed on the screen as reflected by the learner's eyeballs, and to determine or correct the Chinese characters corresponding to eye pauses.

[0099] Furthermore, it includes a training step in which, by using specific template text, during the training process performed by specific users or a group of template users, relevant parameters of the user reading using a specific user terminal device are perceived and collected to improve the accuracy of identifying Chinese characters corresponding to eye pauses.

[0100] Furthermore, the steps further include at least one of the following steps:

[0101] Chinese learners can click on unfamiliar characters, touch unfamiliar characters, or mark unfamiliar characters through user interface devices or other means. The online platform will automatically play the pronunciation of the character and add it to the list of unfamiliar characters.

[0102] Chinese learners can click on unfamiliar characters, touch unfamiliar characters, or mark unfamiliar characters using other methods such as user interface devices. The online platform will automatically display the pinyin of the character and add it to the list of unfamiliar characters.

[0103] Chinese learners can click on unfamiliar characters, touch unfamiliar characters, or mark unfamiliar characters using a user interface device or other means. The online platform will automatically display the meaning of that character in other languages ​​and scripts, and add the character to the list of unfamiliar characters; and

[0104] When a Chinese learner clicks on an unfamiliar character, touches an unfamiliar character, or marks an unfamiliar character using a user interface device, the online platform will automatically play the translation of the character's meaning in other languages ​​and scripts, and add the character to the list of unfamiliar characters.

[0105] Furthermore, the steps further include the following steps;

[0106] This prompts Chinese learners to practice reading aloud and extensively reading articles;

[0107] Use a microphone sensor to acquire the reading voice signal of Chinese learners;

[0108] Compare the pronunciation of Chinese learners with the standard pronunciation of extensive reading texts;

[0109] Based on the pronunciation comparison results, identify language elements in Chinese learners that need to be corrected or improved in pronunciation;

[0110] Characters that cannot be pronounced are identified as unfamiliar characters, and characters that are mispronounced are identified as potentially unfamiliar characters.

[0111] Display or label potentially unfamiliar characters, prompting Chinese learners to use voice or user interface devices or other sensors to confirm their recognition; and

[0112] Once a confirmed character is identified as an unfamiliar character, it is added to the list of unfamiliar characters.

[0113] Furthermore, the other parameters and rules for generating extensive reading articles further include:

[0114] The overall difficulty of generating extensive reading articles is determined based on the number of words in the forgotten word list;

[0115] The overall difficulty of generating extensive reading articles is determined based on the number of characters in the list of unfamiliar characters.

[0116] The overall difficulty of generating extensive reading articles is determined based on the distribution of the commonness or rarity of the characters in the list of unfamiliar characters.

[0117] Based on the reading time or reading speed of the Chinese learner user collected by the online platform, the overall difficulty of the generated extensive reading articles is determined;

[0118] Based on the correct answer rate of the practice questions collected from the online platform by the Chinese learner users, the overall difficulty of the generated extensive reading articles is determined;

[0119] Based on the distribution of the difficulty coefficients of the practice questions answered correctly by the Chinese learner users collected from the online platform, the overall difficulty of generating extensive reading articles is determined;

[0120] Based on the difficulty change request submitted by the Chinese learner user, the overall difficulty of the generated extensive reading article was determined;

[0121] Based on the combination of the above factors, the overall difficulty of generating extensive reading articles is determined; and

[0122] The frequency of generating general reading articles is determined based on any one of the above factors, or the combination of multiple factors.

[0123] By using a list of learned characters that matches the intensive reading textbook and the progress of intensive reading lessons as the available character set for generating extensive reading articles, and limiting the number / percentage of unlearned characters outside this list in the extensive reading articles, the reading threshold can be effectively lowered. This allows students to enter into reading complete Chinese texts earlier, even when their Chinese character accumulation is limited. Furthermore, by repeatedly reinforcing their memory of learned characters in context, a virtuous cycle of mutual promotion between character recognition and reading ability improvement can be formed. This is especially important for overseas students whose Chinese-speaking environment is scarce.

[0124] This invention, while matching the intensive reading process, further precisely matches the individual student's level and gaps, and incorporates these individual language elements into extensive reading articles with high priority for repeated reinforcement. This will further enhance the precision and targeting of this special type of extensive reading learning, thereby improving learning efficiency. Attached Figure Description

[0125] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0126] Figure 1 : A schematic diagram of the system architecture of the Chinese extensive reading teaching network platform of the present invention;

[0127] Figure 2 The flowchart of the invention for generating and pushing extensive reading articles adapted to the intensive reading teaching process;

[0128] Figure 3 The flowchart of the invention for generating and pushing extensive reading articles that dynamically adapts to the intensive reading teaching process and matches the learners' personalized needs;

[0129] Figure 4 The graph showing the change in reading speed generated by the Chinese extensive reading teaching network platform of this invention.

[0130] Figure label:

[0131] 1-Student User Client Module; 2-Teacher User Client Module; 3-Administration User Client Module; 4-User Service Module; 5-Database Module; 6-Content Generation Module; 7-Network. Detailed Implementation

[0132] The technical solutions in the embodiments of the present invention will now be clearly and completely described with reference to the accompanying drawings. It is obvious that the described embodiments are merely some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0133] Figure 1 The diagram shows the system architecture of the Chinese extensive reading teaching network platform of the present invention, which includes: student user terminal module 1, teacher user terminal module 2, management user terminal module 3, user service module 4, database module 5 and content generation module 6. Each module realizes information communication between data through network 7.

[0134] Student client module 1 is configured to provide learners with a login portal and interactive interface, and can be implemented as a web application or client application based on terminal devices. Student client module 1 supports learners in accessing extensive reading materials, engaging in reading interactions, submitting learning feedback, and setting personalized parameters, including but not limited to reading preferences, difficulty adjustment requests, and multimodal prompt settings.

[0135] The teacher user interface module 2 is configured as the operation interface for teachers, supporting functions such as publishing extensive reading materials, viewing learning data, setting generation parameters, and teacher-student interaction. Teachers can input a list of new words, article parameters, and compilation requirements into the content generation module 6 through the teacher user interface module 2, enabling customized management of extensive reading content.

[0136] The management user terminal module 3 is configured as a system management function interface, supporting functions such as user account management, class relationship configuration, operation parameter setting and exception handling, ensuring that the platform executes user permission control and service scheduling according to preset rules.

[0137] User service module 4 is configured to perform automated operation tasks, including user authentication, message push, billing management and permission verification. It achieves user status tracking and service response by calling database module 5.

[0138] Database module 5 stores various types of data required for system operation, including user information, learning records (reading time, exercise scores, Chinese character mastery status, etc.), extensive reading content library, and system configuration parameters, supporting structured queries and dynamic data updates.

[0139] Content generation module 6 is the core unit for generating extensive reading materials. Its core functions include: receiving input parameters, constructing an AI tool call instruction set, executing generation tasks, result verification, and iterative optimization. The content generation module 6 dynamically adjusts the instruction set parameters by comparing the generated results with the expected goals until preset conditions are met or the iteration limit is reached. Finally, it stores the optimized extensive reading article in the database and triggers the push process.

[0140] In the first embodiment, extensive reading content is matched with intensive reading courses through an extensive reading teaching network platform. Specifically, after completing a single lesson in the intensive reading course, the teacher inputs the following parameters into the content generation module 6 through the teacher user terminal module 2: a list of new characters (containing N newly taught Chinese characters, with the number of characters to be included specified as M≤N), article length, subject matter, genre, suitable age group, instructions for calling the list of learned characters, and restrictions on the percentage of unlearned characters. The list of learned characters is a dynamic list of characters that have been learned up to the current intensive reading lesson progress, while the list of new characters is the list of new characters introduced in the current intensive reading lesson; both are closely aligned with the intensive reading lesson's progress. The content generation module 6 integrates the above parameters with system preset rules into an AI tool call instruction set, which includes: mandatory inclusion requirements for new characters, an article length deviation of less than or equal to ±25%, and a percentage of unlearned characters less than or equal to a first preset ratio; wherein, the first preset ratio is preferably between 2% and 12%. When the online platform for extensive reading instruction can respond to students' click / touch requests and provide pronunciation and meaning prompts for unlearned words in real time, it is recommended that students choose 8% of the Chinese as their inherited language, 10% of the Chinese as their inherited language, and 5% of the Chinese as their second language.

[0141] By invoking AI tools such as generative large language models (e.g., ChatGPT, Deepseek, or Gemini, which are just examples and not limitations) to perform extensive reading material generation tasks, the module performs multi-dimensional verification on the output extensive reading materials: 100% coverage of new words, length deviation less than or equal to 25%, and the proportion of unlearned words less than or equal to a first preset proportion. Natural language processing tools are also used to check content compliance. If the results do not meet the standards (i.e., fail the above multi-dimensional verification), the module automatically adjusts the instruction set (e.g., increases the emphasis on new words, refines vocabulary restrictions, etc.) and re-invokes the AI ​​tools. To avoid getting stuck in an infinite loop or an empty loop, an upper limit is set for the number of iterations, for example, a maximum of 5 times. The final generated extensive reading article is confirmed by the teacher user module 2 and then pushed to the target student user by the user service module 4.

[0142] In the second embodiment, the system achieves precise adaptation of content to the learning needs of individual students through personalized learning data. When learners read extensive reading materials, the extensive reading teaching network platform of the present invention detects unfamiliar characters through the student user terminal module 1 using the following mechanisms: (1) Eye movement tracking: The camera collects eye movement parameters and gaze coordinates to locate Chinese characters with a single dwell time greater than or equal to L1 seconds, and Chinese characters that are viewed multiple times with at least one dwell time greater than or equal to L2 seconds. The values ​​of L1 and L2 are detailed below; (2) Voice comparison: The microphone collects reading voice and compares it with the standard pronunciation library to identify unpronounced and incorrectly pronounced characters; (3) User interaction: Supports touch marking or voice feedback to confirm unfamiliar characters. The detected unfamiliar characters are stored in the user's unfamiliar character list set in the database module 5 in real time. The system periodically transfers Chinese characters belonging to the learned character list to the forgotten character list. In subsequent tasks, the content generation module 6 prioritizes the inclusion of characters from the forgotten characters list (e.g., by setting a weight greater than or equal to 0.7 or by grouping them by priority) and dynamically adjusts the article difficulty coefficient (e.g., based on reading time, exercise accuracy, length of the unfamiliar characters list, length of the forgotten characters list, etc.) to achieve personalized content delivery. When a character is detected as not being marked as unfamiliar three times, the system automatically removes it from the forgotten characters list.

[0143] The first method for detecting unfamiliar characters is configured as follows: When learners read extensive reading articles through the interactive interface of the student user terminal module 1, they can mark unfamiliar characters by touch operation or mouse click. The system adds the marked Chinese characters to the user's exclusive list of unfamiliar characters in the database module 5. The marking operation supports an undo function, allowing users to remove incorrectly marked Chinese characters; for the same Chinese character that appears repeatedly in the article, a single marking is sufficient to identify the entire document. Optionally, the marking operation can trigger multimodal auxiliary functions, including automatically playing the pronunciation of the Chinese character or displaying pinyin annotations, playing or displaying foreign language translations of the character's meaning, etc.

[0144] The second method for detecting unfamiliar characters is configured as a speech-based recognition mechanism: the student user module 1 collects the reading speech signal through a microphone sensor, compares it with a standard pronunciation database, and identifies unpronounced or mispronounced characters as suspected unfamiliar characters. The comparison process is executed by an AI speech recognition tool, and the results are stored in the unfamiliar character list after being reviewed and confirmed by the learner. The review interface supports list-style or original text annotation-style display, allowing users to remove incorrectly identified characters.

[0145] The third method for detecting unfamiliar characters is configured as an eye-tracking-based recognition mechanism: The student user module 1 collects eye movement parameters and eye mirror reflection images through a camera sensor, and locates Chinese characters with a single gaze duration greater than or equal to L1 seconds or Chinese characters that have been viewed multiple times and have at least one lingering duration greater than or equal to L2 seconds as high-probability unfamiliar characters.

[0146] The system optimizes detection accuracy through the following steps: (1) Training phase: Show the user training samples containing specific marked characters (such as colored or flashing text), collect eye angle, reflection image and reading distance parameters, and build a user-specific reading model; (2) Usage phase: Analyze the eye movement trajectory in real time based on the training model, and determine the gazed Chinese characters by combining the text mapping information in the reflection image. Among them, the parameters L1 or its initial value used for eye movement tracking can be selected as 1.5 seconds, and L2 or its initial value can be selected as 0.7 seconds. Optionally, L1, L2 or their initial values ​​are determined through the above training steps. Optionally, as user reading habit data accumulates, the network platform further fine-tunes and optimizes the values ​​of L1 and L2, stores the updated values ​​in the user's personalized parameter table, and reduces the misjudgment rate through multiple rounds of learning iteration. Optionally, it supports eye movement commands (such as single blink marking, multiple blink cancellation) to assist in recognition. The training process can be executed separately for specific users, device models or user groups (such as different age groups, eye physiological characteristics).

[0147] The method for detecting unidentified characters includes, but is not limited to, the above embodiments. For example, alternative solutions or combinations of the above methods may also be used, such as brain-computer interface technology, electroencephalogram signal analysis, or optic nerve activity detection.

[0148] The third embodiment is configured as a dynamic classification mechanism for the list of unfamiliar characters: the system classifies unfamiliar characters based on the frequency of Chinese character usage (occurrence rate in social documents) and language proficiency standards (such as the HSK test character list level), sets the inclusion priority of commonly used characters to high (weight greater than or equal to 0.6), and sets the inclusion priority of rare characters to low (weight less than or equal to 0.3), so as to achieve precise reinforcement of the content of extensive reading articles.

[0149] The fourth embodiment is configured as a dynamic adjustment mechanism for the difficulty and frequency of push notifications of extensive reading materials: the system determines the overall difficulty and frequency of push notifications of articles based on the following parameters: (1) length of the list of unfamiliar characters L; (2) percentage of unfamiliar characters R; (3) reading speed W (W = number of words in the article ÷ reading time of the article); (4) accuracy rate of exercises S. When R > 15%, the difficulty reduction mode is triggered (the article length setting is changed to 60% of the original setting; the total proportion of Chinese characters at the median HSK level and higher is updated to 70% of the original proportion; the proportion of Chinese characters at levels lower than the original median HSK level is increased to compensate for the reduction in the higher level. For example: under the original settings, the median level of the word count is HSK 3, and the total number of Chinese characters at HSK 3 and above accounts for 60%. After the update, the total number of Chinese characters at HSK 3 and above will account for 60% x 70% = 42%, and the proportion of HSK 1 and 2 will be updated to 100% - 42% = 58%). When L ≤ 20 and S ≥ 85%, the difficulty increase mode is triggered (the article length is set to 150% of the original length). The proportion of Chinese characters at HSK levels that are at the median level or higher will be updated to 120% of the original proportion. The proportion of Chinese characters at levels lower than the original median HSK level will be reduced to match the increase of the higher level. For example, under the original settings, the median level in terms of the proportion of Chinese characters was HSK Level 3, and the total number of Chinese characters at HSK Level 3 and above accounted for 60%. After the update, the total number of Chinese characters at HSK Level 3 and above will account for 60% x 120% = 72%, and the proportion of HSK Level 1 and 2 will be updated to 100% - 72% = 28%. Learners can submit difficulty adjustment requests (such as "increase difficulty" or "decrease difficulty") through the student user module 1. The system will dynamically adjust the difficulty coefficient according to the request. When the reading speed W of three consecutive articles is higher than the class average speed by 30%, the student will be prompted to provide feedback on whether they need to increase the difficulty of the articles or the number of articles pushed per week. The frequency of general reading articles is determined based on the above parameter combinations (e.g., 3 articles per week when S≥90%, 1 article per week when S<60%).

[0150] The fifth embodiment is configured with an adaptation mechanism that combines students' individual learning needs with the progress of intensive reading courses: The system compares the list of unfamiliar characters with the list of learned characters, sets the highest inclusion priority (weight equal to 1.0) for forgotten characters that belong to the list of learned characters, and determines the inclusion strategy for Chinese characters in the list of unfamiliar characters that do not belong to the list of learned characters based on their appearance time (T) in subsequent intensive reading courses: when T≤1 month, the inclusion priority weight is equal to 0.5, and when T>3 months, they are not included (weight equal to 0).

[0151] The method can be extended to language elements other than Chinese characters, including but not limited to: vocabulary, phrases, fixed collocations, sentence structures, and rhetorical devices. For example, when teaching rhetorical devices such as rhetorical questions and parallelism in intensive reading courses, teachers can set parameters through the teacher user terminal module 2 to require extensive reading articles to include examples of the use of specified rhetorical elements.

[0152] Figure 2 The diagram shows a flowchart of a method for generating and pushing extensive reading articles that is adapted to the intensive reading teaching process, including the following steps:

[0153] S12, the teacher initiates the task of generating extensive reading articles through the teacher user terminal module 2;

[0154] S14, Content generation module 6 obtains a list of newly learned Chinese characters within a specified time period;

[0155] S16, retrieve and update the list of learned characters in database module 5 (including all learned Chinese characters up to the current intensive reading course);

[0156] S18, obtain generation parameters and rules, such as: full coverage of the new character list, usage rate of learned characters greater than or equal to 95%, number of unlearned characters less than or equal to 15 (limited to HSK level 3 and below), length 300-350 characters, suitable for grade 4, theme "watching ice hockey game";

[0157] S20, Construct a set of AI tool call instructions that includes the above parameters and rules;

[0158] S22, utilizes AI tools to generate general reading articles;

[0159] S24, User Service Module 4 will generate an article and push it to the target student group (the class or some students specified by the teacher).

[0160] Figure 3 The diagram shows a flowchart of a method for generating and pushing extensive reading articles that dynamically adapts to the intensive reading teaching process and matches the learners' personalized needs. The method includes the following steps:

[0161] S30, system startup;

[0162] S31, determine if the user is logging in for the first time;

[0163] S32, If it is the first login, the database module 5 initializes the user's personal learning list, including the list of learned characters, the list of unknown characters, and the list of forgotten characters (initialized as an empty table).

[0164] S33, Receive requests to generate general reading articles (which can be initiated by teachers, students or parents);

[0165] S34, Content generation module 6 obtains newly learned Chinese characters from the user and constructs a list of new characters;

[0166] S36, retrieve and update the user's learned character list from database module 5 (including all learned Chinese characters up to the current intensive reading course; for example, when studying Lesson 3 of Book 4 of the intensive reading textbook, the learned character list includes the new characters from Books 1-3 and Lessons 1-2 of Book 4 of the same textbook series).

[0167] S38, retrieve the user's list of unfamiliar characters and list of forgotten characters (the list will be empty if it is the first time it is used or if the user's level is significantly higher than the difficulty of the article).

[0168] S40, obtain the parameters and rules for generating general reading articles;

[0169] S42, Construct an AI tool invocation instruction set based on the above list, parameters and rules;

[0170] S44, uses AI tools to generate general reading articles;

[0171] S46, User Service Module 4 will generate an article and push it to the target user;

[0172] S48, During the user's reading process, an automatic / semi-automatic detection mechanism is used to identify unfamiliar characters and update the list of unfamiliar characters (characters that have been identified as familiar are removed from the list).

[0173] S50, transfer the Chinese characters in the list of unfamiliar characters that belong to the list of learned characters to the list of forgotten characters;

[0174] S52, add Chinese characters in the article that are not marked as unfamiliar and do not belong to the list of learned characters to the list of learned characters (recorded according to the acquisition category of non-intensive reading courses); the process returns to S33 to wait for the next generation request.

[0175] This closed-loop mechanism not only accurately tracks each child's Chinese character recognition trajectory but also drives content evolution through dynamic data flow. Each round of reading feedback feeds back into the AI ​​model in real time, continuously monitoring the individual's learned, forgotten, and unfamiliar character lists, as well as any missing morphemes. These external parameters provide different, evolving inputs to the established AI model. Based on this, the extensive reading texts continuously evolve with the learner's cognitive growth, truly achieving "understanding, remembering, and applying," and realizing "characters inseparable from words, words inseparable from sentences, sentences inseparable from paragraphs, paragraphs inseparable from the entire text, and the entire text reflecting the words and phrases, targeting deficiencies." This invention's extensive reading teaching network platform makes every reading session a starting point for skill enhancement, rather than a passive input endpoint. Language learning is a gradual, snowballing process of accumulation. Over time, quantitative changes transform into qualitative ones. This adaptive extensive reading mechanism is quietly reconstructing the underlying logic of Chinese character acquisition. It no longer relies on the linear progression of fixed textbooks, but instead allows learners to engage in continuous dialogue with Chinese characters in authentic contexts, completing the cognitive leap from recognition to understanding, and from understanding to application through dynamic matching. It transforms Chinese character acquisition into a growth-oriented dialogue—words emerge in context, meaning is solidified through interaction, and memory is reinforced through repetition. Each child possesses a unique cognitive river, its flow, depth, and tributaries all shaped in real-time by their own learning rhythm.

[0176] In a more specific and exemplary embodiment, short texts compiled using the extensive reading teaching platform of this invention enabled students who had learned approximately 430 characters in intensive reading classes to begin reading Chinese. During a one-year (approximately 9-month) school year in Ontario, Canada, their intensive reading classes continued to teach them approximately 160 more characters, bringing the total number of characters learned in intensive reading classes to approximately 590 by the end of the year. By continuously collecting reading speed data from 1244 articles (times) during this period, it was observed that their average reading speed increased from approximately 100 characters per minute at the beginning of the school year to approximately 210 characters per minute at the end. This extensive reading teaching platform, closely adapted to the intensive reading curriculum, promptly incorporates recently learned characters into extensive reading articles, refreshing and consolidating memory, resulting in a significant effect on character recognition consolidation. Furthermore, by comparing the character mastery rates of students in two lessons—one using the extensive reading teaching platform of this invention combined with conventional methods for review and consolidation, and the other using only conventional methods for review and consolidation—the total review time was the same, the difficulty level was comparable, and the number of new characters was similar. Four weeks after learning the new characters, a standardized test (half new characters and half distractors) was administered. For the lesson reinforced using the extensive reading teaching platform of this invention, the character mastery rate was 58.3%. For the lesson reviewed using only conventional methods without this extensive reading teaching platform, the mastery rate was 45.6%. The absolute increase in character mastery rate using this invention was 12.7%, and the relative increase was 27.9%. For detailed changes in the improvement rate, please refer to [link / reference needed]. Figure 4 The graph showing the change in reading speed.

[0177] The above embodiments are merely preferred embodiments of the present invention and are not an exhaustive list of the technical solutions of the present invention. Those skilled in the art can make equivalent substitutions or combinations of the technical elements of the present invention based on the content disclosed in this specification to form other embodiments that do not depart from the essence of the present invention. The scope of protection of the present invention is defined by the appended claims.

[0178] The above provides a detailed description of the Chinese extensive reading teaching network platform provided by this invention. Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are merely for the purpose of helping to understand the method and core ideas of this invention. For those skilled in the art, the technical solutions of this invention are not limited to the solutions defined in the specific embodiments. Technical solutions formed by other modifications that can be obviously implemented based on ordinary technical knowledge in the art are all within the protection scope of this invention.

Claims

1. A Chinese extensive reading teaching online platform, comprising: At least one processor; At least one memory, communicatively connected to the at least one processor; the memory stores computer-executable instructions; characterized in that: When the computer-executable instructions are executed by the at least one processor, the at least one processor causes the at least one processor to perform the following steps: The task of generating general reading articles can be initiated by the user or by at least one processor according to the network platform settings. Get the new words that Chinese learners have recently learned in their intensive Chinese reading courses and add them to the new word list; Get all the Chinese characters that Chinese learners have previously learned in intensive Chinese reading courses and add them to the list of learned characters; Obtain other parameters and rules for generating extensive reading articles for Chinese learner users; Based on the list of new words, the list of learned words, and the other parameters and rules, an instruction set for generating extensive reading articles is constructed. Use the above set of instructions to invoke AI tools to generate general reading articles; and The generated general reading articles will be pushed to Chinese learner users.

2. The Chinese extensive reading teaching network platform as described in claim 1, characterized in that, The other parameters and rules include at least one of the following: Word count of articles for general reading; The subject matter of the articles to be read extensively; Extensive reading article genres; The style of extensive reading articles; Suitable age range for extensive reading articles; The number of Chinese characters not included in the learned character list can be used in extensive reading articles; The percentage of Chinese characters not included in the learned character list is limited in extensive reading articles; Content that should not be included in extensive reading articles; The number of characters in the vocabulary list included in extensive reading articles; The priority of including characters from the vocabulary list in extensive reading articles; as well as Besides Chinese characters, other language elements and language points that need to be included in extensive reading articles.

3. The Chinese extensive reading teaching network platform as described in claim 1, characterized in that, The methods for obtaining other parameters and rules for generating extensive reading articles for Chinese learner users include: The network platform is pre-configured; Provided by teachers of intensive reading courses; Provided by Chinese learners; Provided by parents of Chinese learners; Provided by other users; Extracting or exporting from intensively studied textbooks; and Extract or export from the network resources specified by the Chinese intensive reading course teacher user or the network platform.

4. The Chinese extensive reading teaching network platform as described in claim 1, characterized in that, The generation of extensive reading articles further includes generating practice questions that complement the extensive reading articles.

5. The Chinese extensive reading teaching network platform as described in claim 1, characterized in that, The steps further include at least one of the following steps: Store the aforementioned general reading articles; A record of the content pushed to each Chinese learner user; Before pushing the generated extensive reading articles to Chinese learner users, the generated extensive reading articles are submitted for manual review and approval; Send the generated extensive reading articles to teachers of intensive reading courses; Send confirmation of the extensive reading article push to intensive reading course teachers; Send push notifications of extensive reading articles to Chinese learner users; When displaying extensive reading articles to Chinese learner users, the Chinese characters in the vocabulary list are displayed differently; Collect and store information about Chinese learners' reading of extensive reading articles; The collected information on Chinese learners reading extensive reading articles will be reported to intensive reading teachers. The collected information on the Chinese learner users' reading of extensive reading articles will be reported to the management user; The collected information on the Chinese learner's reading of extensive reading articles will be reported to the learner's parents. as well as We collect and store feedback from Chinese learners who read extensive reading articles, making it available for intensive reading teachers and administrators to access.

6. The Chinese extensive reading teaching network platform as described in claim 5, characterized in that, The information regarding Chinese learner users reading extensive reading articles includes at least one of the following: Number of articles read for general reading purposes; Word count of articles read in general reading; The percentage of articles already read out of the total number of articles pushed out; Reading time for general reading articles; The ratio of word count to reading time in extensive reading articles; The number of extensive reading exercises completed; Accuracy rate of extensive reading practice questions; as well as The settings status of user parameters and usage modes when Chinese learners are reading.

7. The Chinese extensive reading teaching network platform as described in claim 1, characterized in that, The step of "calling AI tools to generate general reading articles" further includes the following steps: Verify whether the generated extensive reading articles meet all the requirements of the indicator set; If any aspects are found to be non-compliant during the verification process, the generated general reading article will be sent back to the AI ​​tool and a set of modification instructions will be provided for those non-compliant aspects. AI tools generate modified general reading articles; Repeat the above three steps until the verification meets the requirements of the instruction set, or the maximum set number of repetitions is reached, then exit the repetition; If the modified extensive reading articles still do not meet the requirements of the specified instruction set upon exit, the intensive reading teacher will be prompted for manual intervention; and Submit the revised or manually-intervened extensive reading articles to the next steps.

8. A Chinese extensive reading teaching online platform, comprising: At least one processor; At least one memory, communicatively connected to the at least one processor; The memory stores computer-executable instructions; characterized in that: When the computer-executable instructions are executed by the at least one processor, the at least one processor causes the at least one processor to perform the following steps: The task of generating general reading articles can be initiated by the user or by at least one processor according to the network platform settings. If the Chinese learner is using the online platform for the first time, create a list of characters the learner has already learned, a list of characters they do not know, and a list of characters they have forgotten, and initialize these lists to be empty. Get the new words that Chinese learners have recently learned in the Chinese intensive reading course and compile a list of new words for that Chinese learner; Retrieve all the Chinese characters that a Chinese learner user has previously learned in a Chinese intensive reading course and add them to the user's list of learned characters; Extract the lists of unfamiliar and forgotten characters from Chinese learner users; Get other parameters and rules for generating extensive reading articles for Chinese learner users; Based on the aforementioned list of new characters, list of learned characters, list of unfamiliar characters, and list of forgotten characters, as well as the aforementioned other parameters and rules, construct an instruction set for generating extensive reading articles; Use the above set of instructions to invoke AI tools and generate articles for general reading. The generated extensive reading articles will be pushed to the Chinese learner user. When Chinese learners read the above-mentioned extensive reading articles, the system automatically or semi-automatically detects any characters they do not recognize and adds them to their list of unfamiliar characters. It also removes characters that they recognize from the list of unfamiliar characters. Add the characters from the list of unfamiliar characters that belong to the list of learned characters above to the list of forgotten characters; When encountering characters while reading the aforementioned extensive reading articles, if the online platform automatically or semi-automatically detects that the Chinese learner recognizes a character but it is not listed in their learned character list, it will add that character to the learned character list; and Repeat the steps above.

9. The Chinese extensive reading teaching network platform as described in claim 8, characterized in that, Other parameters and rules for generating general reading articles include at least one of the following: The characters contained in the aforementioned list of new characters will be included in the extensive reading articles with high priority; The words included in the forgotten word list will be included in the extensive reading articles with high priority; The words in the list of unfamiliar words that are not in the list of forgotten words are included in the extensive reading articles in an appropriate amount or not, depending on their frequency of use. Word count of articles for general reading; The subject matter of the articles to be read extensively; Extensive reading article genres; The style of extensive reading articles; Suitable age range for extensive reading articles; The number of Chinese characters used in extensive reading articles that are not on the aforementioned list of learned characters is limited; The number of characters used in extensive reading articles that are not on the previously learned character list is limited. Content that should not be included in extensive reading articles; The number of characters in the vocabulary list included in extensive reading articles; The priority of including characters from the vocabulary list in extensive reading articles; as well as Besides Chinese characters, other language elements and language points that need to be included in extensive reading articles.

10. The Chinese extensive reading teaching network platform as described in claim 8, characterized in that, When the Chinese learner user reads the extensive reading article, the network platform automatically or semi-automatically detects Chinese learner users' unfamiliar characters in the text, including the following steps; Use a camera image sensor to capture eye movement information of Chinese learners while reading; The system determines the Chinese character corresponding to the eye movement and pausing based on the angle of eye movement and the reading distance of the Chinese learner detected by the camera. The Chinese characters corresponding to pauses are marked as characters that are highly unlikely to be recognized, and at appropriate times, Chinese learner users are prompted to confirm their recognition of these characters using body language, voice, or user interface devices; and The confirmed characters were identified as unfamiliar characters.

11. The Chinese extensive reading teaching network platform as described in claim 10, characterized in that, Further, it includes using a camera image sensor to acquire image information of Chinese characters displayed on the screen as reflected by the learner's eyeballs, and to determine or correct the Chinese characters corresponding to eye pauses.

12. The Chinese extensive reading teaching network platform as described in claim 11, characterized in that, Further, it includes a training step, in which, by using specific template text, during the training process performed by specific users or a group of template users, relevant parameters of the user reading using a specific user terminal device are perceived and collected, in order to improve the accuracy of identifying the Chinese characters corresponding to eye pauses.

13. The Chinese extensive reading teaching network platform as described in claim 8, characterized in that, The steps further include at least one of the following steps: Chinese learners can click on unfamiliar characters, touch unfamiliar characters, or mark unfamiliar characters through user interface devices or other means. The online platform will automatically play the pronunciation of the character and add it to the list of unfamiliar characters. Chinese learners can click on unfamiliar characters, touch unfamiliar characters, or mark unfamiliar characters using other methods such as user interface devices. The online platform will automatically display the pinyin of the character and add it to the list of unfamiliar characters. Chinese learners can click on unfamiliar characters, touch unfamiliar characters, or mark unfamiliar characters using a user interface device or other means. The online platform will automatically display the meaning of that character in other languages ​​and scripts, and add the character to the list of unfamiliar characters; and When a Chinese learner clicks on an unfamiliar character, touches an unfamiliar character, or marks an unfamiliar character using a user interface device, the online platform will automatically play the translation of the character's meaning in other languages ​​and scripts, and add the character to the list of unfamiliar characters.

14. The Chinese extensive reading teaching network platform as described in claim 8, characterized in that, The steps further include the following steps; This prompts Chinese learners to practice reading aloud and extensively reading articles; Use a microphone sensor to acquire the reading voice signal of Chinese learners; Compare the pronunciation of Chinese learners with the standard pronunciation of extensive reading texts; Based on the pronunciation comparison results, identify language elements in Chinese learners that need to be corrected or improved in pronunciation; Characters that cannot be pronounced are identified as unfamiliar characters, and characters that are mispronounced are identified as potentially unfamiliar characters. Display or label potentially unfamiliar characters, prompting Chinese learners to use voice or user interface devices or other sensors to confirm their recognition; and Once a confirmed character is identified as an unfamiliar character, it is added to the list of unfamiliar characters.

15. The Chinese extensive reading teaching network platform as described in claim 8, characterized in that, Other parameters and rules for generating extensive reading articles further include: The overall difficulty of generating extensive reading articles is determined based on the number of words in the forgotten word list; The overall difficulty of generating extensive reading articles is determined based on the number of characters in the list of unfamiliar characters. The overall difficulty of generating extensive reading articles is determined based on the distribution of the commonness or rarity of the characters in the list of unfamiliar characters. Based on the reading time or reading speed of the Chinese learner user collected by the online platform, the overall difficulty of the generated extensive reading articles is determined; Based on the correct answer rate of the practice questions collected from the online platform by the Chinese learner users, the overall difficulty of the generated extensive reading articles is determined; Based on the distribution of the difficulty coefficients of the practice questions answered correctly by the Chinese learner users collected from the online platform, the overall difficulty of generating extensive reading articles is determined; Based on the difficulty change request submitted by the Chinese learner user, the overall difficulty of the generated extensive reading article was determined; Based on the combination of the above factors, the overall difficulty of generating extensive reading articles is determined; and The frequency of generating general reading articles is determined based on any one of the above factors, or the combination of multiple factors.

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