Intelligent teaching system based on artificial intelligence

Abstract

The invention discloses an intelligent teaching system based on artificial intelligence. The system comprises a user information acquisition module, an intelligent analysis module, an English teaching data database, a personalized learning path planning module, an interactive learning module and an evaluation module. The user information acquisition module is connected with the intelligent analysis module, the personalized learning path planning module is connected with the intelligent analysis module and the English teaching material database, the interactive learning module is connected with the personalized learning path planning module, and the evaluation module is connected with the English teaching material database and the interactive learning module. The beneficial effects are that learning efficiency is effectively improved; the learning interest is effectively improved; individual differences are effectively met; and the accuracy of learning effect evaluation is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of teaching systems, and in particular to an intelligent teaching system based on artificial intelligence. Background Art

[0002] In today's era of globalization, English, as an international language, is becoming increasingly important in education. However, traditional English teaching methods face many challenges and problems.

[0003] On the one hand, traditional English teaching is relatively simple in teaching mode. Classroom teaching is mostly based on teacher lectures, and students passively accept knowledge. For example, in vocabulary teaching, teachers usually just write down words, phonetic symbols and definitions on the blackboard, and then lead students to read and recite. This method lacks fun and interactivity, and it is difficult to stimulate students' interest in learning. When teaching grammar, teachers often simply explain grammatical rules, and students have difficulties in understanding and applying them, and cannot well apply grammatical knowledge to actual language expression.

[0004] On the other hand, traditional teaching is difficult to meet the learning progress and ability differences of different students. In a class, students' English foundations vary. Some students may have good listening, speaking, reading and writing skills, while others still have difficulty mastering basic knowledge. However, during the teaching process, teachers can only teach according to a unified syllabus and progress. This leads to students with good foundations feeling that the course content is too simple and their enthusiasm for learning is frustrated; while students with poor foundations may not be able to keep up with the teaching progress and gradually develop a fear of difficulty.

[0005] In addition, traditional English teaching is insufficient in terms of resource utilization. Textbooks are the main teaching resources, but the content of textbooks is updated relatively slowly and cannot timely cover new vocabulary, popular expressions and cultural phenomena. Moreover, the presentation of teaching resources is limited, and there is a lack of diversified multimedia resource integration, such as high-quality original English videos and audios, which is not conducive to students' listening and speaking training.

[0006] At the same time, in terms of teaching evaluation, the traditional method relies too much on test scores. A test paper can only test students' memory of knowledge, but cannot comprehensively evaluate students' language application ability, degree of effort and progress in the learning process. This makes teaching feedback inaccurate and cannot provide an effective basis for subsequent teaching adjustments.

[0007] Furthermore, there is a lack of supervision and guidance for extracurricular learning. When students encounter problems in their independent learning after class, they cannot get answers in time, and the effectiveness and sustainability of their learning are difficult to guarantee. These problems urgently need to be solved by a new English teaching system to achieve more efficient and personalized English teaching. Summary of the invention

[0008] To solve the above problems, especially aiming at the deficiencies existing in the prior art, the present invention provides an intelligent teaching system based on artificial intelligence that can solve the above problems.

[0009] To achieve the above object, the present invention adopts the following technical means:

[0010] An intelligent teaching system based on artificial intelligence, comprising a user information collection module, an intelligent analysis module, an English teaching material database, a personalized learning path planning module, an interactive learning module, and an evaluation module;

[0011] The user information collection module is used to collect information on students' age, English foundation, learning goals, learning habits, and past English learning experiences;

[0012] The intelligent analysis module analyzes the data of the user information collection module by using clustering analysis algorithms, association rule mining algorithms, and machine learning classification algorithms;

[0013] The English teaching material database stores teaching material data covering from basic to professional fields;

[0014] The personalized learning path planning module combines dynamic programming algorithms and greedy algorithms, plans the learning path according to the student information, and recommends and sorts the learning content according to the principles of from easy to difficult, from basic to advanced, and from single knowledge module to comprehensive application;

[0015] The interactive learning module has a question answering and voice interaction function. The question answering function uses real-time communication technology to achieve real-time data transmission, allowing students to obtain questions, submit answers, and get feedback immediately when answering questions; the voice interaction function uses speech recognition technology to have a voice conversation with students and gives feedback on the students' pronunciation, grammar, and the rationality of the answer content during the conversation;

[0016] The evaluation module establishes an evaluation index system including knowledge mastery indicators, ability improvement indicators, and learning process indicators;

[0017] The user information collection module is connected to the intelligent analysis module. The user information collection module transmits the multi-dimensional information of the collected students to the intelligent analysis module. The intelligent analysis module determines the students' learning level and needs through the analysis of the multi-dimensional information of the students;

[0018] The personalized learning path planning module is connected to the intelligent analysis module and the English teaching material database. The intelligent analysis module transmits the analyzed student information results to the personalized learning path planning module. The personalized learning path planning module formulates a personalized learning path for the student, and moreover, the personalized learning path planning module screens and invokes appropriate learning resources from the English teaching material database;

[0019] The interactive learning module is connected to the personalized learning path planning module. The interactive learning module receives the learning tasks pushed by the personalized learning path planning module and provides diverse learning methods and scenarios for the student;

[0020] The evaluation module is connected to the English teaching material database and the interactive learning module. The evaluation module receives the student learning data fed back by the interactive learning module and associates it with the English teaching material database to obtain relevant knowledge standards and references.

[0021] A further solution of the present invention is that the intelligent analysis module constructs student information based on the data analysis results. The student information includes student basic information, an overview of English learning ability, learning preferences, and analysis content of strengths and weaknesses.

[0022] A further solution of the present invention is that the English teaching material database includes a vocabulary database, a special question type database, and a test paper database.

[0023] A further solution of the present invention is that the voice interaction function of the interactive learning module includes various scenarios such as daily conversation practice, role-playing, and topic discussion.

[0024] A further solution of the present invention is that the evaluation module adopts an evaluation method combining regular tests and real-time evaluation. The regular tests cover vocabulary, grammar, listening, speaking, reading, and writing. The real-time evaluation is carried out during the student's daily learning process.

[0025] A further solution of the present invention is that the evaluation module generates a visual evaluation report based on the evaluation results, puts forward suggestions and improvement measures for the student's strengths and weaknesses, and can be used to adjust the learning path and content of the personalized learning path planning module.

[0026] The beneficial effects of the present invention:

[0027] 1. The present invention effectively improves learning efficiency. Personalized learning path: The system comprehensively collects and intelligently analyzes students' information to customize a learning path for each student. This personalized planning avoids students wasting time on content that is not suitable for their own level, ensuring that they always study at an appropriate difficulty gradient. Students with a better foundation can also quickly access more challenging content, accelerating their learning progress and making the entire learning process more efficient. Precise content push: The English teaching material database is rich and well-organized. The personalized learning path planning module can accurately push content according to students' learning situations. Whether it is vocabulary, grammar, listening, speaking, or reading materials, they are closely matched with the students' current learning stage. This enables students to quickly obtain the most valuable knowledge during the learning process, reducing the time cost of searching and screening learning resources, thereby improving learning efficiency.

[0028] 2. The present invention effectively enhances learning interest. Interactive learning module: Functions such as voice interaction, scenario simulation, and gamification learning in the interactive learning module greatly enhance the fun of learning. Voice interaction allows students to have the opportunity to practice real conversations with the system as naturally as using English in daily life. Scenario simulation creates an immersive experience for students through virtual reality or augmented reality technology, making learning no longer boring and enabling students to participate in learning more actively. Diversified resource presentation: The various types of learning resources in the English teaching material database present English knowledge in diverse forms. Compared with traditional single textbooks, these diversified resources can meet the needs of students with different learning styles, attract their attention, and enhance their interest in English learning.

[0029] 3. The present invention effectively meets individual differences. Comprehensive user information collection and analysis: The user information collection module collects multi-dimensional information of students, including age, learning goals, learning habits, etc. The intelligent analysis module constructs students' information based on this information to deeply understand the unique situation of each student. Whether it is students with a fast or slow learning speed, or students with specific learning goals, the system can accurately identify and meet their needs.

[0030] 4. The present invention effectively enhances the accuracy of learning effect evaluation. Multi-dimensional evaluation index system: The multi-dimensional evaluation index system established by the evaluation module covers aspects such as knowledge mastery, ability improvement, and learning process. This comprehensive evaluation method can accurately reflect the true level of students in all aspects of English learning. Different from the traditional evaluation method that only relies on examination results, it can not only understand students' memory of knowledge, but also evaluate students' practical application ability and learning effort degree, and can comprehensively master the development of students' English ability; Real-time feedback and dynamic adjustment: The evaluation module conducts real-time evaluation during the learning process, generates a detailed report based on the results and puts forward improvement suggestions. At the same time, the system can dynamically adjust the personalized learning path and content push according to the evaluation results, can timely discover problems and obtain targeted guidance during the learning process, and the learning plan can also be continuously optimized according to the learning progress, thereby effectively enhancing the learning effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 is the system block diagram of the present invention;

[0032] Reference numerals:

[0033] User information collection module 1, intelligent analysis module 2, English teaching material database 3, personalized learning path planning module 4, interactive learning module 5, evaluation module 6. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0034] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0035] Embodiment 1

[0036] An intelligent teaching system based on artificial intelligence aims to provide efficient and personalized learning experiences for English learners, including user information collection module 1, intelligent analysis module 2, English teaching material database 3, personalized learning path planning module 4, interactive learning module 5, evaluation module 6;

[0037] The user information collection module 1 is connected to the intelligent analysis module 2. The user information collection module 1 transmits the multi-dimensional information of the collected students to the intelligent analysis module 2. The intelligent analysis module 2 determines the learning level and needs of the students through the analysis of the multi-dimensional information of the students;

[0038] The personalized learning path planning module 4 is connected to the intelligent analysis module 2 and the English teaching material database 3. The intelligent analysis module 2 transmits the analyzed student information results to the personalized learning path planning module. The personalized learning path planning module 4 formulates a personalized learning path for the student, and moreover, the personalized learning path planning module 4 screens and invokes appropriate learning resources from the English teaching material database 3;

[0039] The interactive learning module 5 is connected to the personalized learning path planning module 4. The interactive learning module 5 receives the learning tasks pushed by the personalized learning path planning module 4 and provides students with diverse learning methods and scenarios;

[0040] The evaluation module 6 is connected to the English teaching material database 3 and the interactive learning module 5. The evaluation module 6 receives the student learning data fed back by the interactive learning module 5 and is associated with the English teaching material database 3 to obtain relevant knowledge standards and references. These modules cooperate with each other to form a closed-loop intelligent teaching process.

[0041] User information collection module 1

[0042] Located at the front end of the system, it is the starting point for interacting with users. It includes a well-designed online questionnaire interface. The questions in the questionnaire cover students' basic information, such as age, gender, etc., as well as content related to English learning, such as the starting time of learning English, the current self-assessed English level (which can be assisted by simple vocabulary and grammar tests), learning goals (different classification options such as daily communication, exam preparation, business application, etc.), learning habits (preferred learning time, such as being more efficient in the morning or evening; learning style preference, whether visual - preferring to learn by reading written materials, auditory - relying on listening to audio, or kinesthetic - learning through writing, practice, etc.), and past English learning experiences (courses attended, exam scores, difficulties encountered, etc.). In addition, there is an entrance for uploading materials, allowing students to upload previous English homework, exam papers, English learning notes and other materials, and extracting more information from them through image recognition and text analysis technologies, such as writing habits, common error types, etc., so as to comprehensively collect user information.

[0043] Intelligent analysis module 2

[0044] Located at the "brain" position of the system, it starts to work after receiving the data from the user information collection module.

[0045] Data analysis algorithms: Using clustering analysis algorithms, students are classified into different categories based on factors such as age, English foundation, and learning goals. Students with similar characteristics are grouped together. At the same time, association rule mining algorithms are used to explore the internal relationships between different data items, such as the correlation between students' learning habits and learning effects, or the relationship between specific learning goals and required knowledge modules. Classification algorithms in machine learning are used to accurately classify and evaluate students' English levels. Combining data such as vocabulary test results, grammar mastery, and preliminary listening and speaking ability assessments, students are divided into different levels such as primary school, junior high school, and senior high school, and the algorithms are continuously trained and optimized to improve classification accuracy.

[0046] Student information construction: Based on the above data analysis results, a detailed student information is created for each student. The information content includes students' basic information, an overview of English learning abilities (such as vocabulary range, grammar mastery level, and a rough assessment of listening and speaking levels), learning preferences (learning time preferences, learning method tendencies), and an analysis of strengths and weaknesses (for example, excellent performance in vocabulary memorization but insufficient flexibility in grammar application; relatively standard oral pronunciation but lack of logical expression, etc.), providing a comprehensive basis for subsequent personalized learning path planning.

[0047] English teaching material database 3

[0048] 1. Vocabulary database: Vocabulary databases for English words and phrases at the primary school, junior high school, and senior high school levels are set up respectively;

[0049] 2. Special question type database: Import various question types and answer analyses for primary school, junior high school, and senior high school respectively. Listening questions come with the original text and answers. The question types of the test papers are as follows: For primary school, the question types include: Listening question types (words, sentences, short conversations, long conversations, short passages); Written test question types (phonetic discrimination, multiple-choice, word filling, phrase filling, word spelling, word classification, sentence making with words, dialogue completion, blank filling with selected words, English-Chinese and Chinese-English translation, English proverbs, sentence pattern transformation, synonym transformation, sentence translation, writing words according to pictures, writing phrases according to pictures, choosing pictures according to sentences, sentence completion, passage completion, judging the correctness of sentences, correcting wrong questions, task-based reading, reading comprehension, cloze test, written expression);

[0050] 3. Test paper database, including primary school English test paper database, junior high school English test paper database, and senior high school English test paper database.

[0051] Personalized learning path planning module 4

[0052] It works based on the student information constructed by the intelligent analysis module.

[0053] Path planning algorithm: Adopt a combination of dynamic programming algorithm and greedy algorithm. The dynamic programming algorithm considers the long-term goals and sub-goals at each stage of students' English learning from a macro perspective, ensuring the coherence and systematicness of the learning path, and ensuring that students gradually achieve the leap from primary school to high school, from basic to proficient. The greedy algorithm plays a role in each learning stage, selecting the learning content and tasks that are most beneficial to students' improvement at present to achieve a local optimal solution, and thus gradually approaching the overall optimal learning effect. For example, for a student at the primary school level with the goal of daily communication, the system will first plan a learning path starting from simple daily high-frequency vocabulary and basic sentence patterns. As the learning progresses, more complex grammar structures and new vocabulary will be introduced in a timely manner, and the difficulty of listening training will be increased.

[0054] Learning content recommendation and ranking: Recommend content by comprehensively considering the resources in the English teaching material database and the current learning status of students. In terms of vocabulary learning, the recommended vocabulary matches the current vocabulary level of students and is associated with the grammar and reading content being learned, facilitating understanding and memory. For grammar learning, new grammar points are gradually recommended according to the difficulty level and students' mastery, and corresponding examples and exercises are provided. The ranking of learning content follows the principles of from easy to difficult, from primary school to high school, and from single knowledge modules to comprehensive applications. For example, reading materials are recommended to start from short passages with simple vocabulary and sentence patterns. As students' reading ability improves, the length of the articles, vocabulary difficulty, and grammar complexity are gradually increased, and content from different knowledge modules is integrated at an appropriate time to design scenario simulation tasks that include newly learned vocabulary, grammar, and oral expressions to improve students' ability to comprehensively apply knowledge.

[0055] Interactive learning module 5

[0056] Provide a platform for students to actively participate in and practice English.

[0057] Answering questions function: Adopt real-time communication technology to achieve real-time data transmission, enabling students to instantly obtain questions, submit answers, and get feedback when answering questions;

[0058] Voice interaction function: Students can have a voice conversation with the system through the microphone. The system uses advanced speech recognition technology to accurately recognize students' English pronunciation and understand and analyze the speech content. During the conversation, the system gives real-time feedback, including pronunciation correction (pointing out which specific phonetic symbol is pronounced inaccurately and providing a correct pronunciation demonstration), grammar error prompts, and evaluation of the rationality of the answer content. Design a variety of voice interaction scenarios, such as daily conversation practice (carried out around simple topics such as weather, hobbies, etc.), role-playing (simulating various life scenarios such as shopping, ordering food in a restaurant, seeing a doctor in a hospital, etc.), and topic discussion (encouraging students to express their views, guiding discussions, and at the same time evaluating students' view expression, logical thinking, and language application abilities).

[0059] Scenario Simulation and Gamification Learning: Scenario simulation creates an immersive English learning environment for students with the help of virtual reality (VR) or augmented reality (AR) technologies (when device support is available). For example, students can experience a foreign travel scenario firsthand and communicate with virtual characters in English to complete tasks such as asking for directions, booking hotels, and buying tickets, greatly enhancing their learning interest and engagement, and enabling them to naturally apply English knowledge in practice. Gamification learning motivates students to keep learning by designing various English learning games, such as English word puzzles (students piece together scrambled letters into correct words, and the system provides definitions and pronunciations during the process), grammar fill-in-the-blank challenges (difficulty levels are set according to the progress of grammar learning, and each level has a short passage with grammar blanks for students to fill in and pass the levels, and successful completion can earn rewards such as points and virtual medals), and listening quizzes (guessing the answers to riddles based on listening content).

[0060] Evaluation Module 6

[0061] Conduct a comprehensive and dynamic evaluation of students' learning situations.

[0062] Evaluation Index System: Establish a comprehensive evaluation index system, including knowledge mastery indicators, ability improvement indicators, and learning process indicators. Knowledge mastery indicators target students' mastery of English vocabulary, grammar, reading, listening, and other knowledge, and are measured by regular vocabulary tests, the correct rate of grammar exercises, reading comprehension and listening comprehension test scores, etc. Ability improvement indicators focus on students' practical English application abilities, such as the fluency of oral expression (calculating the number of effective words and sentences per unit time), accuracy (counting the number of pronunciation and grammar errors), logic (analyzing the coherence and rationality of the expressed content), and writing ability (evaluating from aspects such as vocabulary diversity, grammar correctness, sentence structure complexity, overall logic and coherence of the article). Learning process indicators focus on students' performance during the learning process, such as learning time investment (statistics of the duration of logging in to the learning platform and the time spent on each learning module through system records), learning task completion rate (calculating the proportion of completed vocabulary learning, grammar practice, listening, and reading tasks recommended by the system), and the frequency and quality of participating in interactive learning (evaluated based on the number of times and performance of participating in voice interaction, scenario simulation, and gamification learning).

[0063] Evaluation Methods and Feedback Mechanisms: Adopt a combination of regular tests (weekly tests, monthly tests, etc.) and real-time evaluations. Regular tests cover various aspects such as vocabulary, grammar, listening, speaking, reading, and writing, and have diverse test forms, including multiple-choice questions, fill-in-the-blank questions, short-answer questions, oral presentations, and writing. Real-time evaluations are conducted during daily learning. For example, after a student completes a grammar exercise, the system immediately gives the answer and analysis and records the answering situation. During oral practice, pronunciation and the content of the expression are evaluated in real time. Based on the evaluation results, a detailed evaluation report is generated and presented to students and teachers (if there are teachers involved in management) in a visual way (such as charts, bar graphs, line graphs, etc.), intuitively showing the changing trends of students on various evaluation indicators. At the same time, specific suggestions and improvement measures are put forward for the strengths and weaknesses of students. For example, if a student makes progress in listening comprehension but lacks fluency in speaking, the report recommends increasing the time and frequency of oral practice and recommends appropriate oral practice methods and resources. For teachers, the evaluation report helps to understand the overall learning situation of the class and adjust teaching strategies and priorities. In addition, the evaluation results are also used to adjust the learning paths and learning content of the personalized learning path planning module to ensure that the learning plan conforms to the actual learning situation and development needs of students.

[0064] Working Principle

[0065] First, the user information collection module 1 is activated, and multi-dimensional information of students, including age, English foundation, learning goals, learning habits, etc., is collected through online questionnaires and analysis of uploaded materials. These data form the basis for subsequent analysis.

[0066] Next, the intelligent analysis module 2 intervenes. It uses algorithms such as cluster analysis, association rule mining, and machine learning classification to process the collected data. Through cluster analysis, students with similar learning characteristics are classified. Association rule mining is used to find potential connections between data. The classification algorithm evaluates the English level of students, and then a student information including the general situation of students' abilities, learning preferences, strengths and weaknesses is constructed.

[0067] Then, the personalized learning path planning module 4 works based on the student information. The learning path is planned by combining dynamic programming and greedy algorithms. Appropriate content is screened from the English teaching material database 3. The vocabulary, grammar, listening, speaking, reading and other materials in the English teaching material database 3 are organized and managed in a hierarchical and associated manner, which is convenient for retrieval and call. When planning, learning content is recommended to students in the order from easy to difficult, from primary school to high school, and from single to comprehensive.

[0068] Meanwhile, the interactive learning module 5 comes into play. Through the question-and-answer function, real-time communication technology is adopted to achieve real-time data transmission, enabling students to instantly obtain questions, submit answers, and receive feedback when answering questions; through the voice interaction function, advanced speech recognition technology is used to conduct voice conversations with students, and pronunciation, grammar, and content rationality are provided with real-time feedback in dialogue scenarios (such as daily conversations, role-playing, topic discussions). Scenario simulation uses VR / AR technology (if supported) to create an immersive environment, and gamified learning improves students' participation and practical abilities by designing various English learning games.

[0069] Finally, the evaluation module 6 keeps running. The evaluation module 6 receives the students' learning data fed back by the interactive learning module 5 and associates it with the English teaching material database 3 to obtain relevant knowledge standards and references. At the same time, according to the evaluation system including knowledge mastery, ability improvement, and learning process indicators, a method combining regular tests and real-time evaluations is adopted to evaluate the students' learning achievements. Visual reports are generated based on the evaluation results, providing improvement suggestions for students and at the same time feeding back to the personalized learning path planning module to adjust the learning path and content push, forming an intelligent teaching closed-loop that is continuously optimized.

[0070] Embodiment 2

[0071] 1. User information collection

[0072] Xiaoming is a 10-year-old primary school student who has just started learning English and has a weak English foundation. He hopes to be able to communicate simply in English through learning. The user information collection module 1 collects his information and transmits it to the intelligent analysis module 2 for analysis. The intelligent analysis module 2 analyzes and learns his starting point and goals.

[0073] 2. Intelligent analysis and path planning

[0074] The intelligent analysis module 2 classifies Xiaoming as a primary-level student. The personalized learning path planning module 4 formulates a personalized learning path for Xiaoming, and moreover, the personalized learning path planning module 4 screens and invokes appropriate learning resources from the English teaching material database 3. For example, vocabulary memorization, sentence pattern practice, situational conversations, short passage reading, level tests, and audio-visual training at the primary school student level.

[0075] 3. Interactive learning and evaluation

[0076] The interactive learning module 5 completes the learning resources transmitted by the personalized learning path planning module 4. The evaluation module 6 obtains the knowledge standards and references related to the learning resources through the English teaching material database 3; at the same time, the evaluation module 6 regularly evaluates Xiaoming's learning situation through simple paper tests and oral tests, and adjusts the subsequent learning content according to the results.

[0077] The examples given in the present invention are illustrative rather than restrictive of the embodiments. For those of ordinary skill in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to enumerate all the embodiments here, and the obvious changes or modifications derived therefrom still fall within the protection scope of the present invention.

Claims

1. An intelligent teaching system based on artificial intelligence, characterized in that: It includes user information collection module, intelligent analysis module, English teaching material database, personalized learning path planning module, interactive learning module and evaluation module; The user information collection module is used to collect information about the student's age, English foundation, learning goals, learning habits and past English learning experience; The intelligent analysis module uses cluster analysis algorithm, association rule mining algorithm and machine learning classification algorithm to analyze the data of the user information collection module; The English teaching material database stores teaching material data covering everything from basic to professional fields; The personalized learning path planning module uses a combination of dynamic programming algorithm and greedy algorithm to plan the learning path according to the student information, and recommends and sorts the learning content according to the principle of from easy to difficult, from basic to advanced, and from single knowledge module to comprehensive application; The interactive learning module has the functions of answering questions and voice interaction. The answering function adopts real-time communication technology to realize real-time data transmission, so that students can instantly obtain questions, submit answers, and get feedback when answering questions; the voice interaction function adopts voice recognition technology to conduct voice dialogue with students, and provide feedback on students' pronunciation, grammar and the rationality of their answers during the dialogue; The evaluation module establishes an evaluation index system including knowledge mastery index, ability improvement index and learning process index; The user information collection module is connected to the intelligent analysis module, and the user information collection module transmits the collected multi-dimensional information of students to the intelligent analysis module, and the intelligent analysis module determines the learning level and needs of students by analyzing the multi-dimensional information of students; The personalized learning path planning module is connected with the intelligent analysis module and the English teaching material database. The intelligent analysis module transmits the student information obtained by analysis to the personalized learning path planning module. The personalized learning path planning module formulates a personalized learning path for the student, and the personalized learning path planning module screens and calls appropriate learning resources from the English teaching material database. The interactive learning module is connected to the personalized learning path planning module, the interactive learning module receives the learning tasks pushed by the personalized learning path planning module, and provides students with a variety of learning methods and scenarios; The evaluation module is connected with the English teaching material database and the interactive learning module. The evaluation module receives the student learning data fed back by the interactive learning module and associates it with the English teaching material database to obtain relevant knowledge standards and references.

2. The intelligent teaching system based on artificial intelligence according to claim 1 is characterized in that: The intelligent analysis module constructs student information based on the data analysis results, and the student information includes basic student information, English learning ability profile, learning preferences, and strengths and weaknesses analysis content.

3. The intelligent teaching system based on artificial intelligence according to claim 1 is characterized in that: The English teaching material database includes a vocabulary database, a special question type database, and a test paper database.

4. The intelligent teaching system based on artificial intelligence according to claim 1 is characterized in that: The voice interaction functions of the interactive learning module include daily conversation practice, role-playing, topic discussion and other scenarios.

5. The intelligent teaching system based on artificial intelligence according to claim 1 is characterized in that: The assessment module adopts an assessment method that combines regular tests and real-time assessments. Regular tests cover vocabulary, grammar, listening, speaking, reading and writing, while real-time assessments are conducted during students' daily learning process.

6. The intelligent teaching system based on artificial intelligence according to claim 1 is characterized in that: The evaluation module generates a visual evaluation report based on the evaluation results, and proposes suggestions and improvement measures based on the strengths and weaknesses of the students, and can be used to adjust the learning path and content of the personalized learning path planning module.

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