English word memorizing system based on memory curve

Abstract

The invention discloses an English word memorizing system based on a memory curve, and the system comprises a login module which is used for carrying out registration and login operation, obtaining personal information, and recommending learning contents and plans; the learning module is used for executing a learning and memorizing process and recording a learning progress and a memorizing condition; the memory curve updating module is used for generating an initial memory curve and dynamically updating memory curve parameters; the plan generation module is used for automatically generating a personalized review plan; the review module is used for regularly sending review reminding according to the review plan; and the feedback module is used for obtaining feedback and suggestions of the user and carrying out optimization and improvement. According to the method, the review time is intelligently arranged based on the memory curve, the natural law of human memory and forgetting is followed, the learning content and the review plan are customized according to the individual difference of learners, the learning motivation is enhanced, the learners are endowed with more autonomy, the self-management and self-driving capabilities are cultivated, and a foundation is laid for lifelong learning.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent education, and more specifically, particularly relates to an English word memory system based on a memory curve. Background Art

[0002] With the increasing development of globalization, English has become a common language in the world. In this context, English learning has become particularly important for people in some non-native English-speaking countries. People are beginning to pay more and more attention to English learning, especially for some parents who value their children's future development. They will let their children participate in various English training from an early age to complete their personal development better and more comprehensively.

[0003] Learning any language, especially English, is nothing more than learning four professional skills, namely listening, speaking, reading and writing. In the field of English learning, there is a saying that goes, "He who reads wins the world." This shows the importance of English reading ability to English learning. So how to improve English reading ability? This requires English students to improve their English vocabulary and their grasp of English context.

[0004] However, there are some problems with the existing technology: in the context of exam-oriented education, students need to master a large number of English words in order to cope with exams, so rote memorization becomes a seemingly effective strategy, resulting in some students lacking effective learning strategies and not knowing how to memorize words efficiently. They simply repeat the spelling and meaning of the words without adopting more effective methods to deepen their memory. Therefore, we propose an English word memorization system based on a memory curve. Summary of the invention

[0005] In view of the problems existing in the prior art, the purpose of the present invention is to provide an English word memory system based on a memory curve, which can significantly improve the efficiency of word memory by intelligently arranging review time based on the memory curve and following the natural laws of human memory and forgetting.

[0006] To achieve the above object, the present invention provides the following technical solution: an English word memory system based on a memory curve, comprising: a login module: used for performing registration and login operations, obtaining user personal information and learning goals, and recommending learning content and plans based on preset rules;

[0007] Learning module: output vocabulary information, execute learning and memory process, and record learning progress and memory status according to the vocabulary and memory curve selected by the user;

[0008] Memory curve update module: generates the initial memory curve and dynamically updates the memory curve parameters based on the user's learning performance;

[0009] Plan generation module: automatically generates a personalized review plan based on the user's memory curve and current learning progress;

[0010] Review module: according to the review plan, regularly send review reminders and provide vocabulary review panel;

[0011] Feedback module: obtain user feedback and suggestions to optimize and improve module content.

[0012] Optionally, the login module provides a user interaction interface for the user terminal. The specific workflow of the login module is:

[0013] 1) Display the registration form through the user interaction interface, verify the user input information, and encrypt and store the user information in the database;

[0014] 2) Display the login interface, verify the account and password entered by the user, and jump to the user's homepage;

[0015] 3) Obtain user personal information and learning goals, and provide vocabulary selection;

[0016] 4) Recommend learning content and plans based on user learning goals, and provide a plan adjustment panel;

[0017] 5) Output the user's initial learning plan.

[0018] Optionally, the workflow of the learning module is specifically as follows:

[0019] 1) Obtain the initial learning plan and apply the initial memory curve;

[0020] 2) Execute the learning and memory process through the user interface;

[0021] 3) Check the user's vocabulary and conduct memory tests;

[0022] 4) Record the user's daily learning progress and vocabulary mastery;

[0023] 5) Display the review panel and flash it regularly to remind the user according to the review plan.

[0024] Optionally, the learning and memorizing process is specifically as follows:

[0025] Generate a learning interface based on the user interaction interface, and display the vocabulary information to be learned to the user in sequence. The user performs vocabulary interaction through the interface buttons, and the displayed vocabulary is uploaded to the database and marked as learned vocabulary;

[0026] The vocabulary information includes definitions, pronunciations and example sentences;

[0027] The learning interface includes a vocabulary list, a vocabulary details page, a pronunciation button, example sentence display, marking and adding;

[0028] The vocabulary interaction includes marking the vocabulary as mastered vocabulary and adding it to the vocabulary book.

[0029] Optionally, the checking of the user's vocabulary mastery is specifically as follows:

[0030] Generate test set: obtain learned vocabulary, extract mastered vocabulary and vocabulary from vocabulary book in proportion, and generate memory test questions;

[0031] Answer submission: The user enters the answer and clicks the submit button to submit the answer to the learning module;

[0032] Result feedback: judge and output the correctness of the user's answer, and perform built-in tagging on the vocabulary;

[0033] The memory test questions include multiple choice, fill-in-the-blank and judgment;

[0034] Specifically, the built-in mark is: the vocabulary mark of a correct answer is increased by one, reducing the probability of test set extraction; the vocabulary mark of an incorrect answer is decreased by one, increasing the probability of test set extraction.

[0035] Optionally, the working process of the memory curve updating module is specifically as follows:

[0036] 1) Generate an initial curve: Generate an initial memory curve according to a preset algorithm, wherein the memory curve is set based on the memory of past rules;

[0037] 2) Collect learning data: collect users’ learning performance data in real time, including learning time, vocabulary mastery or new words added, test scores and number of reviews;

[0038] 3) Data analysis: Analyze learning data through intelligent algorithms to evaluate the user's mastery of vocabulary and the degree of forgetting;

[0039] 4) Dynamic parameter adjustment: According to the analysis results, dynamically adjust the parameters of the memory curve, including the location of the forgetting point and the duration of the review interval;

[0040] 5) Apply the updated curve: Output the updated memory curve to the plan generation module.

[0041] Optionally, the intelligent algorithm is based on a machine learning algorithm, specifically:

[0042] Set the feature vector ;

[0043] in For the duration of study;

[0044] For test scores;

[0045] For the number of review times;

[0046] is the time interval, which represents the time difference between the user's learning and review of the same vocabulary at different time points;

[0047] There is a A random forest of trees, each tree For samples The prediction result is , then the prediction of each tree can be expressed as:

[0048] ;

[0049] in, Indicates The prediction function of a decision tree;

[0050] According to the memory curve, closer time intervals are given larger weights, while farther time intervals are given smaller weights, so an exponential decay function is used to set the weights, specifically:

[0051] ;

[0052] in, Indicates time interval;

[0053] is the attenuation coefficient, which is used to control the attenuation speed of the weight;

[0054] Combining the weights and predictions of each tree, the final prediction is expressed as:

[0055] ;

[0056] Output the final result to get the user's mastery of vocabulary and the extent of forgetting.

[0057] Optionally, the dynamic parameter adjustment criterion is specifically:

[0058] If the mastery level is lower than the threshold, the position of the forgetting point is moved forward, shortening the time interval between the first review and learning, and shortening the time interval between adjacent reviews in subsequent reviews;

[0059] If the mastery level is higher than the threshold, the position of the forgetting point is extended, the time interval between the first review and learning is extended, and the time interval between adjacent reviews is extended in subsequent reviews.

[0060] Optionally, the workflow of the plan generation module is specifically as follows:

[0061] 1) Obtain and analyze the user's memory curve and set the memory cycle;

[0062] 2) Identify the vocabulary that needs to be learned and record the time and duration of each learning session in a learning log;

[0063] 3) Develop review plan tasks based on the memory cycle.

[0064] Optionally, the review module specifically includes:

[0065] The review module generates a review interface through a user terminal, allowing the user to view the review plan and export it as a file;

[0066] Track the user's review progress in real time and display it in the form of charts;

[0067] Send review reminders according to the review plan, including SMS, email and in-app notifications.

[0068] The technical effects and advantages of the present invention are as follows: by intelligently arranging review time based on the memory curve, the natural laws of human memory and forgetting are followed, and the efficiency of word memory is significantly improved. The embodiment of the present invention provides a personalized learning experience, customizes learning content and review plans according to individual differences of learners, and enhances learning motivation. At the same time, it guides learners to adopt meaningful learning methods, optimize learning strategies, and improve learning effects. In addition, it also gives learners more autonomy, cultivates self-management and self-driving capabilities, and lays the foundation for lifelong learning.

[0069] Further features and advantages of the present invention will become apparent from the following detailed description of exemplary embodiments of the present invention with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 It is a schematic diagram of the word memory system architecture provided by the present invention;

[0071] Figure 2 It is a flow chart of the learning plan provided by the present invention;

[0072] Figure 3 It is a schematic diagram of the working process of the memory curve updating module provided by the present invention. DETAILED DESCRIPTION

[0073] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0074] like Figures 1 to 3 As shown, an English word memory system based on a memory curve provided by an embodiment of the present invention includes:

[0075] Login module: used for registration and login operations, obtaining user personal information and learning goals, and recommending learning content and plans based on preset rules;

[0076] Learning module: output vocabulary information, execute learning and memory process, and record learning progress and memory status according to the vocabulary and memory curve selected by the user;

[0077] Memory curve update module: generates the initial memory curve and dynamically updates the memory curve parameters based on the user's learning performance;

[0078] Plan generation module: automatically generates a personalized review plan based on the user's memory curve and current learning progress;

[0079] Review module: according to the review plan, regularly send review reminders and provide vocabulary review panel;

[0080] Feedback module: obtain user feedback and suggestions to optimize and improve module content.

[0081] Furthermore, the English word memory system based on the memory curve provided by the embodiment of the present invention obtains user personalized information through the login module, intelligently recommends learning content according to the user's learning goals, improves the pertinence and efficiency of learning, and the plan generation module combines the memory curve to scientifically plan the learning process, helping users to generate effective learning and review plans;

[0082] Secondly, the memory curve update module can dynamically adjust the memory curve parameters to adapt to changes in the user's learning process, ensuring that the learning plan always meets the user's actual memory ability. The plan generation module automatically generates a review plan based on these personalized data to avoid the blindness and inefficiency of traditional review methods.

[0083] Finally, the introduction of the review module and feedback module further enhances the system's interactivity and user engagement. The review module helps users consolidate their memory through regular reminders and review panels, while the feedback module collects user opinions, continuously optimizes system functions and content, and ensures that the system always meets user needs.

[0084] Specifically, the login module provides a user interaction interface for the user terminal. The workflow of the login module is as follows:

[0085] 1) Display the registration form through the user interaction interface, verify the user input information, and encrypt and store the user information in the database;

[0086] 2) Display the login interface, verify the user's account and password, and jump to the user's homepage;

[0087] 3) Obtain user personal information and learning goals, and provide vocabulary selection;

[0088] 4) Recommend learning content and plans based on user learning goals, and provide a plan adjustment panel;

[0089] 5) Output the user's initial learning plan.

[0090] Furthermore, the registration form is displayed and user information is verified through the user interaction interface to ensure the accuracy and security of user information. User information is encrypted and stored in the database to further protect user privacy and enhance user trust. The login module simplifies the user login process and can quickly jump to the user homepage by verifying the account and password, improving the convenience of user use. At the same time, the vocabulary selection is provided according to the user's personal information and learning goals, making the learning content closer to user needs;

[0091] Furthermore, the system recommends learning content and plans based on the user's learning goals and provides a plan adjustment panel. This design reflects the intelligence and personalization of the system, allowing users to adjust their learning plans according to their actual conditions, thereby enhancing the flexibility and autonomy of learning.

[0092] Finally, output the user's initial learning plan to provide the user with a clear learning path, which will help the user better plan and manage their learning time.

[0093] Specifically, the workflow of the learning module is as follows:

[0094] 1) Obtain the initial learning plan and apply the initial memory curve;

[0095] 2) Execute the learning and memory process through the user interface;

[0096] 3) Check the user's vocabulary and conduct memory tests;

[0097] 4) Record the user's daily learning progress and vocabulary mastery;

[0098] 5) Display the review panel and flash it regularly to remind the user according to the review plan.

[0099] Furthermore, the learning module tailors the learning path for users based on the initial learning plan and memory curve, ensuring that the learning content not only meets the actual needs of users but also follows the laws of memory, thus improving learning efficiency;

[0100] Secondly, the learning and memory process is executed through the user interaction interface, making the learning process more intuitive and vivid, which helps to enhance the user's interest and participation in learning. At the same time, the memory test can test the user's mastery of vocabulary and timely discover the weak links in learning;

[0101] Furthermore, the learning module records the user's learning progress and vocabulary mastery in detail, provides users with a clear learning track, displays the review panel and flashes reminders to users at regular intervals according to the review plan, effectively reminding users to review, consolidate learning outcomes, and avoid forgetting.

[0102] Specifically, the learning and memorizing process is as follows:

[0103] Generate a learning interface based on the user interaction interface, and display the vocabulary information to be learned to the user in sequence. The user performs vocabulary interaction through the interface buttons, and the displayed vocabulary is uploaded to the database and marked as learned vocabulary;

[0104] The vocabulary information includes definitions, pronunciations and example sentences;

[0105] The learning interface includes a vocabulary list, a vocabulary details page, a pronunciation button, example sentence display, marking and adding;

[0106] The vocabulary interaction includes marking the vocabulary as mastered vocabulary and adding it to the vocabulary book.

[0107] Furthermore, the learning interface generated through the user interaction interface can intuitively and clearly display vocabulary information, including definitions, pronunciations and examples, to help users fully understand the meaning and usage of vocabulary, and help deepen the user's memory and understanding of vocabulary. Users can perform vocabulary interactions through interface buttons, such as marking mastered vocabulary and adding it to a vocabulary book, uploading the displayed vocabulary to the database and marking it as learned vocabulary;

[0108] Specifically, the checking of the user's vocabulary mastery is as follows:

[0109] Generate test set: obtain learned vocabulary, extract mastered vocabulary and vocabulary from vocabulary book in proportion, and generate memory test questions;

[0110] Answer submission: The user enters the answer and clicks the submit button to submit the answer to the learning module;

[0111] Result feedback: judge and output the correctness of the user's answer, and perform built-in tagging on the vocabulary;

[0112] The memory test questions include multiple choice, fill-in-the-blank and judgment;

[0113] Specifically, the built-in mark is: the vocabulary mark of a correct answer is increased by one, reducing the probability of test set extraction; the vocabulary mark of an incorrect answer is decreased by one, increasing the probability of test set extraction.

[0114] Furthermore, by generating a test set, the mastered vocabulary and vocabulary from the vocabulary book are extracted in proportion, which ensures the comprehensiveness and pertinence of the test content and helps to accurately evaluate the user's mastery of vocabulary. The user only needs to enter the answer and click the submit button to upload the answer to the learning module, which improves the convenience and efficiency of the test. The result feedback link is timely and accurate, and can immediately judge and output the correctness of the user's answer. At the same time, the vocabulary is built-in. This instant feedback mechanism helps users correct mistakes in time and deepen their memory.

[0115] Finally, the design of the built-in marking mechanism dynamically adjusts the probability of vocabulary test set extraction according to the user's answers, realizing personalized testing, which helps users better consolidate what they have learned and improve learning efficiency.

[0116] Specifically, the working process of the memory curve updating module is as follows:

[0117] 1) Generate an initial curve: Generate an initial memory curve according to a preset algorithm, wherein the memory curve is set based on the memory of past rules;

[0118] 2) Collect learning data: collect users’ learning performance data in real time, including learning time, vocabulary mastery or new words added, test scores and number of reviews;

[0119] 3) Data analysis: Analyze learning data through intelligent algorithms to evaluate the user's mastery of vocabulary and the degree of forgetting;

[0120] 4) Dynamic parameter adjustment: According to the analysis results, dynamically adjust the parameters of the memory curve, including the location of the forgetting point and the duration of the review interval;

[0121] 5) Apply the updated curve: Output the updated memory curve to the plan generation module.

[0122] Furthermore, the workflow of the memory curve update module uses intelligent means to achieve accurate analysis of the user's learning situation and dynamic adjustment of the memory curve. First, the initial memory curve is generated according to the preset algorithm, and then the user's learning performance data is collected in real time. Through the intelligent algorithm, this data is deeply analyzed. The module can accurately evaluate the user's mastery of vocabulary and forgetting situation, and based on the analysis results, adjust the parameters of the memory curve, such as the location of the forgetting point and the length of the review interval, to ensure that the review plan is more in line with the user's actual memory situation;

[0123] Finally, the updated memory curve is output to the plan generation module to provide users with a more personalized review plan. This process design not only improves review efficiency, but also enhances the pertinence and interactivity of learning, providing users with a more scientific and efficient learning experience.

[0124] Specifically, the intelligent algorithm is based on a machine learning algorithm, specifically:

[0125] Set the feature vector ;

[0126] in For the duration of study;

[0127] For test scores;

[0128] For the number of review times;

[0129] is the time interval, which represents the time difference between the user's learning and review of the same vocabulary at different time points;

[0130] There is a A random forest of trees, each tree For samples The prediction result is , then the prediction of each tree can be expressed as:

[0131] ;

[0132] in, Indicates The prediction function of a decision tree;

[0133] According to the memory curve, closer time intervals are given larger weights, while farther time intervals are given smaller weights, so an exponential decay function is used to set the weights, specifically:

[0134] ;

[0135] in, Indicates time interval;

[0136] is the attenuation coefficient, which is used to control the attenuation speed of the weight;

[0137] Combining the weights and predictions of each tree, the final prediction is expressed as:

[0138] ;

[0139] Output the final result to get the user's mastery of vocabulary and the extent of forgetting.

[0140] Furthermore, the intelligent algorithm uses the random forest model in machine learning, combined with feature vectors such as learning time, test scores, review times and time intervals, to accurately predict the user's vocabulary mastery.

[0141] By assigning weights to different time intervals through an exponential decay function, the user's memory status is reflected more scientifically. Combined with the memory curve update module, the algorithm can dynamically adjust the memory curve parameters to make the review plan more in line with the user's actual situation, which not only improves the review efficiency, but also enhances the personalization and scientific nature of learning, providing users with a more efficient and accurate English vocabulary learning experience.

[0142] Specifically, the dynamic parameter adjustment criteria are:

[0143] If the mastery level is lower than the threshold, the position of the forgetting point is moved forward, shortening the time interval between the first review and learning, and shortening the time interval between adjacent reviews in subsequent reviews;

[0144] If the mastery level is higher than the threshold, the position of the forgetting point is extended, the time interval between the first review and learning is extended, and the time interval between adjacent reviews is extended in subsequent reviews.

[0145] Furthermore, the dynamic parameter adjustment criteria flexibly adjust the parameters of the memory curve according to the user's mastery of the vocabulary. When the mastery level is lower than the set threshold, it indicates that the user's memory of the vocabulary is not solid. The system will accordingly move the position of the forgetting point forward, shorten the time interval between the first review and learning, and shorten the time interval between adjacent reviews in subsequent reviews to strengthen memory. On the contrary, if the mastery level is higher than the threshold, it indicates that the user has a good memory of the vocabulary. The system will extend the position of the forgetting point and increase the review interval to optimize learning time and efficiency, ensuring that the review plan can not only strengthen memory for weak links, but also avoid unnecessary repeated learning, providing users with a more intelligent and efficient English vocabulary learning experience.

[0146] Specifically, the workflow of the plan generation module is as follows:

[0147] 1) Obtain and analyze the user's memory curve and set the memory cycle;

[0148] 2) Identify the vocabulary that needs to be learned and record the time and duration of each learning session in a learning log;

[0149] 3) Develop review plan tasks based on the memory cycle.

[0150] Furthermore, the plan generation module first obtains and analyzes the user's memory curve, sets the memory cycle according to the user's memory characteristics, and ensures the scientific nature of the review plan;

[0151] Then, identify the vocabulary that needs to be learned and record the time and duration of each study in detail through a study log to provide accurate data support for formulating a review plan;

[0152] Finally, based on the memory cycle and learning log, the module intelligently generates review plan tasks to ensure that users review at the best time and improve learning efficiency. It not only improves the pertinence and effectiveness of the review, but also enhances the autonomy and personalization of learning.

[0153] Specifically, the review module is as follows:

[0154] The review module generates a review interface through a user terminal, allowing the user to view the review plan and export it as a file;

[0155] Track the user's review progress in real time and display it in the form of charts;

[0156] Send review reminders according to the review plan, including SMS, email and in-app notifications.

[0157] Furthermore, through the review interface generated by the user terminal, users can clearly view the review plan and even export it as a file for easy reference and arrangement at any time; this module also tracks the user's review progress in real time and displays it in an intuitive chart form to help users better understand their learning status;

[0158] In addition, the review reminder function is sent regularly according to the review plan, through multiple methods such as SMS, email and in-app notifications, to ensure that users will not miss any review opportunities. This not only improves the convenience and effectiveness of the review, but also enhances the user's participation and learning motivation, providing users with a more intimate and efficient English vocabulary review experience.

[0159] In summary: by intelligently arranging review time based on the memory curve and following the natural laws of human memory and forgetting, the efficiency of word memory is significantly improved. The embodiment of the present invention provides a personalized learning experience, customizes learning content and review plans according to individual differences of learners, and enhances learning motivation. At the same time, it guides learners to adopt meaningful learning methods, optimize learning strategies, and improve learning effects. In addition, it also gives learners more autonomy, cultivates self-management and self-driving capabilities, and lays the foundation for lifelong learning.

[0160] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An English word memory system based on a memory curve, characterized in that: include: Login module: used for registration and login operations, obtaining user personal information and learning goals, and recommending learning content and plans based on preset rules; Learning module: output vocabulary information, execute learning and memory process, and record learning progress and memory status according to the vocabulary and memory curve selected by the user; Memory curve update module: generates the initial memory curve and dynamically updates the memory curve parameters based on the user's learning performance; Plan generation module: automatically generates a personalized review plan based on the user's memory curve and current learning progress; Review module: according to the review plan, regularly send review reminders and provide vocabulary review panel; Feedback module: obtain user feedback and suggestions to optimize and improve module content.

2. The English word memory system based on memory curve according to claim 1, characterized in that: The login module provides a user interaction interface for the user terminal. The specific workflow of the login module is: 1) Display the registration form through the user interaction interface, verify the user input information, and encrypt and store the user information in the database; 2) Display the login interface, verify the account and password entered by the user, and jump to the user's homepage; 3) Obtain user personal information and learning goals, and provide vocabulary selection; 4) Recommend learning content and plans based on user learning goals, and provide a plan adjustment panel; 5) Output the user's initial learning plan.

3. The English word memory system based on memory curve according to claim 1, characterized in that: The specific workflow of the learning module is as follows: 1) Obtain the initial learning plan and apply the initial memory curve; 2) Execute the learning and memory process through the user interface; 3) Check the user's vocabulary and conduct memory tests; 4) Record the user's daily learning progress and vocabulary mastery; 5) Display the review panel and flash it regularly to remind the user according to the review plan.

4. The English word memory system based on memory curve according to claim 3, characterized in that: The learning and memory process is specifically as follows: Generate a learning interface based on the user interaction interface, and display the vocabulary information to be learned to the user in sequence. The user performs vocabulary interaction through the interface buttons, and the displayed vocabulary is uploaded to the database and marked as learned vocabulary; The vocabulary information includes definitions, pronunciations and example sentences; The learning interface includes a vocabulary list, a vocabulary details page, a pronunciation button, example sentence display, marking and adding; The vocabulary interaction includes marking the vocabulary as mastered vocabulary and adding it to the vocabulary book.

5. The English word memory system based on memory curve according to claim 3, characterized in that: The specific test of the user's vocabulary mastery is as follows: Generate test set: obtain learned vocabulary, extract mastered vocabulary and vocabulary from vocabulary book in proportion, and generate memory test questions; Answer submission: The user enters the answer and clicks the submit button to submit the answer to the learning module; Result feedback: judge and output the correctness of the user's answer, and perform built-in tagging on the vocabulary; The memory test questions include multiple choice, fill-in-the-blank and judgment; Specifically, the built-in mark is: the vocabulary mark of a correct answer is increased by one, reducing the probability of test set extraction; the vocabulary mark of an incorrect answer is decreased by one, increasing the probability of test set extraction.

6. The English word memory system based on memory curve according to claim 3, characterized in that: The working process of the memory curve update module is specifically as follows: 1) Generate an initial curve: Generate an initial memory curve according to a preset algorithm, wherein the memory curve is set based on the memory of past rules; 2) Collect learning data: collect users’ learning performance data in real time, including learning time, vocabulary mastery or new words added, test scores and number of reviews; 3) Data analysis: Analyze learning data through intelligent algorithms to evaluate the user's mastery of vocabulary and the degree of forgetting; 4) Dynamic parameter adjustment: According to the analysis results, dynamically adjust the parameters of the memory curve, including the location of the forgetting point and the duration of the review interval; 5) Apply the updated curve: Output the updated memory curve to the plan generation module.

7. The English word memory system based on memory curve according to claim 6, characterized in that: The intelligent algorithm is based on a machine learning algorithm, specifically: Set the feature vector ; in For the duration of study; For test scores; For the number of review times; is the time interval, which represents the time difference between the user's learning and review of the same vocabulary at different time points; There is a A random forest of trees, each tree For samples The prediction result is , then the prediction of each tree can be expressed as: ； in, Indicates The prediction function of a decision tree; According to the memory curve, closer time intervals are given larger weights, while farther time intervals are given smaller weights, so an exponential decay function is used to set the weights, specifically: ； in, Indicates time interval; is the attenuation coefficient, which is used to control the attenuation speed of the weight; Combining the weights and predictions of each tree, the final prediction is expressed as: ； Output the final result to get the user's mastery of vocabulary and the extent of forgetting.

8. The English word memory system based on memory curve according to claim 6, characterized in that: The dynamic parameter adjustment criteria are specifically: If the mastery level is lower than the threshold, the position of the forgetting point is moved forward, shortening the time interval between the first review and learning, and shortening the time interval between adjacent reviews in subsequent reviews; If the mastery level is higher than the threshold, the position of the forgetting point is extended, the time interval between the first review and learning is extended, and the time interval between adjacent reviews is extended in subsequent reviews.

9. The English word memory system based on memory curve according to claim 1, characterized in that: The specific workflow of the plan generation module is as follows: 1) Obtain and analyze the user's memory curve and set the memory cycle; 2) Identify the vocabulary that needs to be learned and record the time and duration of each learning session in a learning log; 3) Develop review plan tasks based on the memory cycle.

10. The English word memory system based on memory curve according to claim 1, characterized in that: The review module is specifically: The review module generates a review interface through a user terminal, allowing the user to view the review plan and export it as a file; Track the user's review progress in real time and display it in the form of charts; Send review reminders according to the review plan, including SMS, email and in-app notifications.

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