AI-based college English layered interactive teaching system and implementation method
By using an AI-based tiered teaching system to provide personalized management for students, the system addresses the issue of teaching adaptability for students with different knowledge levels, improves learning efficiency and teaching quality, and achieves data-driven teaching optimization.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HUAIBEI INST OF TECH
- Filing Date
- 2026-02-05
- Publication Date
- 2026-05-08
AI Technical Summary
The existing college English teaching methods cannot accommodate students with different knowledge levels, resulting in uneven learning outcomes and affecting teaching effectiveness.
This approach combines AI-based stratification with instruction, using an AI-based learning diagnostic system to manage students in different strata, push personalized learning tasks, and optimize the teaching process through real-time interactive feedback and dynamic iteration. It also incorporates statistical analysis and categorized data storage to improve teaching quality.
This approach enables tiered management based on students' varying knowledge levels, improving learning efficiency and teaching quality. It ensures that each student receives appropriate teaching content and feedback, and data analysis facilitates subsequent teaching optimization.
Smart Images
Figure CN121998258A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of college English teaching technology, specifically to an AI-based tiered interactive teaching system for college English and its implementation method. Background Technology
[0002] College English teaching is one of the core public basic courses in higher education. Its goal is to help students transition from exam-oriented English in high school to practical English skills that are suitable for academic research, career development and intercultural communication.
[0003] In the current college English teaching process, there are large differences in the level of students in a class. Uniform teaching is not suitable for students with different knowledge levels, which will result in uneven learning progress among students and thus affect subsequent teaching. Summary of the Invention
[0004] To address this issue, the present invention provides an AI-based tiered interactive teaching system and implementation method for college English, which combines AI-based tiered teaching with instruction to solve the problem that uniform teaching is not suitable for students with different knowledge levels.
[0005] To achieve the above objectives, the present invention provides the following technical solution: an AI-based college English tiered interactive teaching system and implementation method, comprising a college English tiered teaching system, wherein the output end of the college English tiered teaching system includes an AI learning diagnosis system and a tiered task push system, and the output end of the college English tiered teaching system further includes a real-time interactive feedback system and a dynamic learning iteration system; The output of the college English tiered teaching system also includes an AI-integrated effect statistics system, and the output of the AI-integrated effect statistics system is equipped with a teaching result and evaluation system. The teaching results and evaluation system output terminal is equipped with an AI fusion effect classification system, and the output terminal of the AI fusion effect classification system is connected to an AI teaching data classification and storage system.
[0006] Preferably, the output of the AI learning diagnosis system includes an NLP pre-class preparation result analysis system and a classroom interaction effect recording system.
[0007] Preferably, the output terminal of the NLP pre-class preparation result analysis system includes a vocabulary test module and a grammar exercise module.
[0008] Preferably, the output end of the classroom interaction effect recording system includes an AI digital one-to-one real-time interactive Q&A module and a tiered student classroom learning effect detection module.
[0009] Preferably, the output end of the tiered student classroom learning effectiveness detection module is connected to a post-class vocabulary detection system and a post-class listening detection system.
[0010] Preferably, the output of the tiered student classroom learning effectiveness detection module also includes a post-class grammar detection system, a post-class oral communication detection system, and a post-class writing detection system.
[0011] Preferably, the output terminal of the teaching results and assessment system includes a classroom learning analysis report system, and the output terminal of the classroom learning analysis report system is connected to a teacher teaching strategy adjustment system.
[0012] Preferably, the output of the hierarchical task push system includes a student learning status hierarchical system and a course multi-level classification system.
[0013] Preferably, the output end of the course multi-level classification system is equipped with a multi-level student and course automatic matching system, and the output end of the multi-level student and course automatic matching system is equipped with a classroom task hierarchical push system and an extracurricular content distribution push system.
[0014] Preferably, the student learning status stratification system includes a basic level student module, an intermediate level student module, and an advanced level student module, and the output of the student learning status stratification system also includes a multi-level student comprehension analysis module.
[0015] The beneficial effects of this invention are: AI manages students' knowledge and comprehension levels in a tiered manner, and then teaches different knowledge to students at different learning levels. At the same time, this device uses AI combined with an effect statistics system to collect data on the learning of students at different levels, so as to facilitate better teaching in the future. This invention greatly improves the efficiency of students' learning and also improves the quality of teachers' teaching. Meanwhile, this system uses an AI fusion effect classification system to classify and statistically analyze the fusion effect of teaching results and learning situations. After the statistics are completed, the AI teaching data classification and storage system performs big data analysis on the statistical data, which is convenient for subsequent comparative teaching. Attached Figure Description
[0016] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.
[0017] The structures, proportions, sizes, etc. illustrated in this specification are only for the purpose of assisting those skilled in the art in understanding and reading the content disclosed herein, and are not intended to limit the conditions under which the present invention can be implemented. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in the proportions, or adjustments to the size, without affecting the effects and objectives that the present invention can produce, should still fall within the scope of the technical content disclosed in the present invention.
[0018] Figure 1 This is a schematic diagram of the overall system structure provided by the present invention; Figure 2 This is a schematic diagram of the AI learning assessment system provided by the present invention; Figure 3 A schematic diagram of the classroom interaction effect recording system provided by the present invention; Figure 4 This is a schematic diagram of the teaching results and assessment system provided by the present invention; Figure 5 A schematic diagram of the hierarchical task push system provided by the present invention. Figure 6 This is a schematic diagram of the hierarchical system structure for student learning provided by the present invention.
[0019] The diagram shows: 1. College English Differentiated Instruction System; 2. AI Learning Diagnosis System; 3. Differentiated Task Push System; 4. Real-time Interactive Feedback System; 5. Dynamic Learning Iteration System; 6. AI Integration Effect Statistics System; 7. Teaching Results and Evaluation System; 8. AI Integration Effect Classification System; 9. AI Teaching Data Classification and Storage System; 10. NLP Pre-class Preparation Result Analysis System; 11. Classroom Interaction Effect Recording System; 12. Vocabulary Test Module; 13. Grammar Exercise Module; 14. AI Digital One-on-One Real-time Interactive Q&A Module; 15. Differentiated Student Classroom Learning Effect Detection Module; 16. 17. After-class vocabulary assessment system; 18. After-class listening assessment system; 19. After-class grammar assessment system; 20. After-class oral assessment system; 21. After-class writing assessment system; 22. Classroom learning analysis report system; 23. Teacher teaching strategy adjustment system; 24. Student learning status stratification system; 25. Multi-level course classification system; 26. Multi-level student and course automatic matching system; 27. Classroom task stratified push system; 28. Extracurricular content distribution push system; 29. Basic level student module; 30. Advanced level student module; 31. Multi-level student comprehension analysis module. Detailed Implementation
[0020] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.
[0021] See attached document Figure 1 -Appendix Figure 6 The present invention provides an AI-based college English tiered interactive teaching system and implementation method, including a college English tiered teaching system 1, the output end of the college English tiered teaching system 1 including an AI learning diagnosis system 2 and a tiered task push system 3, the output end of the college English tiered teaching system 1 also includes a real-time interactive feedback system 4 and a dynamic learning iterative system 5; The output of the College English Differentiated Teaching System 1 also includes an AI-integrated effect statistics system 6, and the output of the AI-integrated effect statistics system 6 is equipped with a teaching results and evaluation system 7. The teaching results and evaluation system 7 output terminal is equipped with an AI fusion effect classification system 8, and the output terminal of the AI fusion effect classification system 8 is connected to an AI teaching data classification and storage system 9; In this implementation plan, the College English Differentiated Teaching System 1 diagnoses students at different learning levels through the AI Learning Diagnosis System 2, then pushes learning tasks of different levels to students at different levels through the Differentiated Task Push System 3, then provides real-time feedback on students' learning progress through the Real-time Interactive Feedback System 4, and finally updates and iterates different learning situations through the Dynamic Learning Iteration System 5 to prevent learning regression. Then, the AI Combined Effect Statistics System 6 statistically analyzes the effect of AI teaching, and finally, the teaching results and evaluation system 7 evaluates the statistical results. After the evaluation is completed, the AI Fusion Effect Classification System 8 classifies different fusion effects, and after the classification is completed, the AI Teaching Data Classification and Storage System 9 stores the classified data. In order to achieve the purpose of learning diagnosis, the device adopts the following technical solution: The output end of the AI learning diagnosis system 2 includes an NLP pre-class preparation result analysis system 10 and a classroom interaction effect recording system 11. The output end of the NLP pre-class preparation result analysis system 10 is equipped with a vocabulary test module 12 and a grammar exercise module 13. The NLP pre-class preparation result analysis system 10 analyzes students' pre-class preparation data through natural language processing; the classroom interaction effect recording system 11 records classroom interactions such as answering questions and group discussion voices. To achieve the purpose of interactive recording, this device adopts the following technical solution: The output end of the classroom interaction effect recording system 11 includes an AI digital one-to-one real-time interactive Q&A module 14 and a tiered student classroom learning effect detection module 15. The output end of the tiered student classroom learning effect detection module 15 is connected to a post-class vocabulary detection system 16 and a post-class listening detection system 17. The output end of the tiered student classroom learning effect detection module 15 also includes a post-class grammar detection system 18, a post-class oral detection system 19, and a post-class writing detection system 20. The output end of the teaching results and evaluation system 7 includes a classroom learning situation analysis report system 21. The output end of the classroom learning situation analysis report system 21 is connected to a teacher teaching strategy adjustment system 22. The AI-powered digital one-on-one real-time interactive Q&A module 14 provides one-on-one real-time interactive Q&A for students. The tiered student classroom learning effectiveness detection module 15 detects the classroom learning effectiveness of students at different levels, and conducts a comprehensive test on vocabulary, listening, grammar, speaking and writing after learning. After the test is completed, the classroom learning situation analysis report system 21 generates a report on the analyzed learning situation. Finally, the teacher teaching strategy adjustment system 22 proposes adjustment strategies for the problems shown in the report.
[0022] In order to achieve the purpose of task push, the device adopts the following technical solution: The output end of the hierarchical task push system 3 includes a student learning status hierarchical system 23 and a course multi-level classification system 24. The output end of the course multi-level classification system 24 is equipped with a multi-level student and course automatic matching system 25. The output end of the multi-level student and course automatic matching system 25 is equipped with a classroom task hierarchical push system 26 and an extracurricular content diffusion push system 27. Students are stratified based on their learning progress. The course is also categorized into three levels: basic, intermediate, and advanced, using a multi-level course classification system 24. The system analyzes the comprehension of students at different levels using a multi-level student comprehension analysis module 31 to facilitate subsequent teaching. Then, the system automatically matches students with courses using a multi-level student-course matching system 25. After matching, various types of classroom tasks are pushed to students. Finally, extracurricular extension content is pushed to students.
[0023] The system operation process of this invention is as follows: The College English Differentiated Teaching System 1 diagnoses students at different learning levels through the AI Learning Diagnosis System 2, then pushes different levels of learning tasks to students at different levels through the Differentiated Task Push System 3, then provides real-time feedback on students' learning progress through the Real-Time Interactive Feedback System 4, and finally updates and iterates different learning situations through the Dynamic Learning Iteration System 5 to prevent learning regression. Then, the AI-based effect statistics system 6 statistically analyzes the effectiveness of AI teaching, and finally, the teaching results and evaluation system 7 evaluates the statistical results. After evaluation, the AI fusion effect classification system 8 classifies different fusion effects, and after classification, the AI teaching data classification and storage system 9 stores the classified data. The NLP pre-class preparation result analysis system 10 analyzes students' pre-class preparation data through natural language processing. The classroom interaction effect recording system 11 records, for example, answers to questions and group discussion voice recordings. The system includes interactive classroom recording, an AI-powered one-on-one real-time interactive Q&A module 14 for one-on-one real-time Q&A with students, a tiered student classroom learning effectiveness assessment module 15 to assess the learning effectiveness of students at different levels, comprehensively evaluating vocabulary, listening, grammar, speaking, and writing skills after learning, a classroom learning analysis report system 21 to generate a report on the analyzed learning situation, and a teacher teaching strategy adjustment system 22 to propose adjustment strategies for the problems shown in the report. Students are tiered based on their learning situation, and courses are categorized into basic, intermediate, and advanced levels through a multi-level course classification system 24. Furthermore, a multi-level student comprehension analysis module 31 analyzes the comprehension of students at different levels to facilitate subsequent teaching, and a multi-level student-course automatic matching system 25 to automatically match students with courses. After matching, various types of classroom tasks are pushed to students, and finally, extracurricular extension content is pushed to students.
[0024] The above description is merely a preferred embodiment of the present invention. Any person skilled in the art can modify the present invention or modify it into an equivalent technical solution using the technical solutions described above. Therefore, any simple modifications or equivalent substitutions made based on the technical solutions of the present invention fall within the scope of protection claimed by the present invention.
Claims
1. An AI-based tiered interactive teaching system for college English and its implementation method, characterized in that: include The College English Differentiated Teaching System (1) includes an AI Learning Diagnosis System (2) and a Differentiated Task Push System (3) at its output end. The College English Differentiated Teaching System (1) also includes a Real-time Interactive Feedback System (4) and a Dynamic Learning Iteration System (5) at its output end. The output end of the college English tiered teaching system (1) also includes an AI-integrated effect statistics system (6), and the output end of the AI-integrated effect statistics system (6) is equipped with a teaching result and evaluation system (7). The teaching results and evaluation system (7) has an AI fusion effect classification system (8) at its output end, and the AI fusion effect classification system (8) is connected to an AI teaching data classification and storage system (9) at its output end.
2. The AI-based tiered interactive teaching system and implementation method for college English as described in claim 1, characterized in that: The AI learning diagnosis system (2) outputs an NLP pre-class preparation result analysis system (10) and a classroom interaction effect recording system (11).
3. The AI-based tiered interactive teaching system and implementation method for college English as described in claim 2, characterized in that: The output of the NLP pre-class preparation result analysis system (10) includes a vocabulary test module (12) and a grammar exercise module (13).
4. The AI-based tiered interactive teaching system and implementation method for college English according to claim 2, characterized in that: The output of the classroom interaction effect recording system (11) includes an AI digital one-to-one real-time interactive Q&A module (14) and a tiered student classroom learning effect detection module (15).
5. The AI-based tiered interactive teaching system and implementation method for college English as described in claim 4, characterized in that: The output of the tiered student classroom learning effectiveness detection module (15) is connected to the after-class vocabulary detection system (16) and the after-class listening detection system (17).
6. The AI-based tiered interactive teaching system and implementation method for college English according to claim 4, characterized in that: The output of the tiered student classroom learning effectiveness detection module (15) also includes a post-class grammar detection system (18), a post-class oral language detection system (19), and a post-class writing detection system (20).
7. The AI-based tiered interactive teaching system and implementation method for college English according to claim 2, characterized in that: The output of the teaching results and assessment system (7) includes a classroom learning analysis report system (21), and the output of the classroom learning analysis report system (21) is connected to a teacher teaching strategy adjustment system (22).
8. The AI-based tiered interactive teaching system and implementation method for college English according to claim 4, characterized in that: The output of the hierarchical task push system (3) includes a student learning status hierarchical system (23) and a course multi-level classification system (24).
9. The AI-based tiered interactive teaching system and implementation method for college English according to claim 8, characterized in that: The course multi-level classification system (24) outputs a multi-level student and course automatic matching system (25), and the multi-level student and course automatic matching system (25) outputs a classroom task hierarchical push system (26) and an extracurricular content dissemination push system (27).
10. The AI-based tiered interactive teaching system and implementation method for college English according to claim 8, characterized in that: The student learning status stratification system (23) includes a basic level student module (28), an advanced level student module (29), and an advanced level student module (30). The output of the student learning status stratification system (23) also includes a multi-level student comprehension analysis module (31).