English auxiliary teaching method based on text resource integration

Abstract

The invention discloses an English aided teaching method based on text resource integration. The English aided teaching method comprises the following steps: S1, determining a teaching target and a subject; s2, screening and classifying text resources, S3, constructing a clear logic framework, analyzing logic relationships among various types of information, and constructing a clear framework based on the logic relationships to organize the integrated text resources; s4, integrating the text resources from different sources, and integrating the same and similar viewpoint texts into one text according to the established logic framework for the collected and analyzed texts; s5, teaching activities are designed; and S6, teaching is carried out, and evaluation and feedback are carried out. According to the method, irrelevant or low-quality information can be eliminated through the process of screening and classifying the text resources, and the most representative and authoritative content is reserved, so that the effectiveness of teaching is improved; and text resources with different sources and viewpoints are integrated, so that students have opportunities to touch diverse cultural viewing angles and ideas.

Description

Technical Field

[0001] The present invention relates to the technical field of English teaching, and in particular to an English auxiliary teaching method based on text resource integration. Background Art

[0002] At present, English teaching generally adopts a combination of traditional textbooks and multimedia teaching, focusing on the teaching of basic knowledge such as grammar and vocabulary. However, with the advent of the information age, the amount of information faced by students has increased dramatically. How to select high-quality learning materials from massive text resources has become a major challenge facing English teaching. At the same time, traditional teaching methods often focus on the inculcation of knowledge, while neglecting the cultivation of students' language application ability and cross-cultural communication ability, resulting in students' difficulty in flexibly applying the knowledge they have learned in practical applications.

[0003] Although English teaching methods are constantly enriched, the integration and utilization of text resources are still insufficient. On the one hand, teachers lack the tools and methods to efficiently screen and classify text resources, which leads to a disconnect between teaching content and actual needs; on the other hand, the text resources in the teaching process are often single, lacking multiple perspectives and in-depth analysis, making it difficult to stimulate students' learning interest and critical thinking ability. Therefore, there is an urgent need for an English-assisted teaching method based on text resource integration to improve the pertinence and effectiveness of teaching. Summary of the invention

[0004] To this end, the present invention provides an English-assisted teaching method based on text resource integration to solve the problem that the integration and utilization of text resources in existing English teaching are still insufficient.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] An English auxiliary teaching method based on text resource integration includes the following steps:

[0007] S1. Clarify the course teaching objectives and determine the theme of each stage or each teaching;

[0008] S2. Screen and classify text resources, collect text resources related to the topic from a wide range of channels, screen out information that is closely related to the topic, representative and authoritative; classify according to the content and nature of the information;

[0009] S3. Build a clear logical framework, analyze the logical relationship between various types of information, and build a clear framework to organize the integrated text resources based on the logical relationship;

[0010] S4. Integrate text resources from different sources, and integrate the previously collected and analyzed texts into one text based on the established logical framework, with texts with the same or similar viewpoints;

[0011] S5. Design teaching activities. According to the English theme and the above integrated text resources, design targeted activities;

[0012] S6. Implement teaching and conduct assessment and feedback.

[0013] According to the English-assisted teaching method based on text resource integration of claim 1, it is characterized in that the method for screening text resources is as follows:

[0014] Perform keyword matching: set a keyword list related to the topic, use text processing tools to segment and tag the collected text, match the segmentation results with the keyword list, and filter out texts closely related to the topic based on the keyword matching results;

[0015] Semantic analysis: Use the semantic analysis model in natural language processing (NLP) technology to deeply understand the text, analyze the text's topic sentences, core ideas, and relevance to the topic, and screen out texts that are closely related to the topic, have clear ideas, and are representative and authoritative.

[0016] Further: The specific steps for keyword matching are as follows:

[0017] 1) Keyword setting: According to the integration theme, set a series of keywords closely related to the theme;

[0018] 2) Text preprocessing: Use text processing tools to preprocess the collected text, including removing irrelevant information and text conversion;

[0019] 3) Word segmentation and part-of-speech tagging: Segment the preprocessed text into independent vocabulary units; perform part-of-speech tagging to mark the part of speech for each vocabulary unit;

[0020] 4) Keyword matching: Match the word segmentation results with the set keyword list, and record the frequency and position of each keyword in the text;

[0021] 5) Importance calculation: Based on the frequency and position of the keywords in the text, the TF-IDF algorithm is used to calculate the importance of the keywords;

[0022] 6) Filter text: According to the keyword matching results and importance calculation, set a TF-IDF value to filter out texts closely related to the topic.

[0023] Further: The steps of semantic analysis are as follows:

[0024] 1) Text preprocessing: Similar to the keyword matching method, the text is first preprocessed, including removing irrelevant information and converting it into small text.

[0025] 2) Semantic model loading: Select a semantic analysis model and load the pre-trained model weights;

[0026] 3) Text encoding: The preprocessed text is input into the semantic model, and the model encodes the text into high-dimensional vector representations. These vectors contain the semantic information of the text;

[0027] 4) Semantic similarity calculation: For each text, calculate its similarity with the topic description or the preset semantic center vector;

[0028] 5) Extraction of topic sentences and core ideas: Using the output of the semantic model, combined with text structure and context information, extract the topic sentences and core ideas of the text;

[0029] 6) Text screening: Based on the results of semantic similarity calculation and the extraction of topic sentences and core ideas, screen out texts that are closely related to the topic, have clear ideas, and are representative and authoritative.

[0030] Further: the logical framework adopts a general-specific-general structure, a time sequence structure, a spatial layout structure, an importance ranking structure, and a hierarchical structure.

[0031] Further: The specific steps to build a logical framework are as follows:

[0032] (1) Clarify the purpose: It is necessary to clarify the purpose of constructing the logical framework and what kind of English teaching activity is being designed;

[0033] (2) Collect information: Based on all relevant information collected and analyzed previously;

[0034] (3) Analyze logical relationships: Carefully analyze the logical relationships between these pieces of information; identify which pieces of information are causal, which are contrasting, and which are parallel;

[0035] (4) Determine the structure: Based on logical relationships, choose an appropriate structure to organize information;

[0036] (5) Develop a framework: Based on the selected structure, develop a detailed framework; the framework should include titles, subtitles, paragraph divisions, and key points; ensure that the framework is clear, organized, and able to present information logically.

[0037] Further: The steps to integrate the previously collected and analyzed texts according to the viewpoints are as follows:

[0038] (1) Extract opinion sentences from the previously collected and analyzed text resources; perform sentiment analysis on opinion sentences to determine their sentiment tendency; perform comparative analysis on the extracted different opinions to identify their similarities and differences; use clustering algorithms to group similar opinions again to more clearly understand the distribution and trends of different opinions;

[0039] (2) Based on comparative analysis, the above texts belonging to the same group of opinions are integrated. For the same group of opinion groups, text summarization technology is used to extract the key information and consensus points in the group; natural language generation technology is used to integrate these key information and consensus points to form a more comprehensive and objective discussion;

[0040] (3) The integrated text is then filled into the logical framework to display the analysis results; the quality of the generated discourse is evaluated using a combination of automatic evaluation indicators and manual evaluation; the algorithm is optimized and adjusted based on the evaluation results to improve the accuracy and efficiency of subsequent integration.

[0041] Further: according to the evaluation results of step S6, timely feedback is given to students, problems are pointed out and suggestions for improvement are put forward; according to the evaluation results and feedback, teaching strategies and resource selection are adjusted in a timely manner to improve teaching effectiveness.

[0042] The present invention has the following advantages:

[0043] By setting clear teaching objectives and themes, teachers can select and integrate text resources more specifically to ensure that teaching content is closely related to students' actual needs and learning objectives. The process of screening and classifying text resources helps to eliminate irrelevant or low-quality information and retain the most representative and authoritative content, thereby improving the effectiveness of teaching.

[0044] Diverse sources of text resources provide students with rich language input, helping to broaden their vocabulary, grammatical structure and expression; integrating text resources from different sources and viewpoints gives students the opportunity to be exposed to diverse cultural perspectives and ideas, thereby enhancing their understanding and respect for different cultures.

[0045] Other features and advantages of the present invention will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practicing the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more intuitively illustrate the prior art and the present application, exemplary drawings are given below. It should be understood that the specific shapes and structures shown in the drawings should not generally be regarded as limiting conditions for implementing the present application; for example, those skilled in the art are capable of easily making conventional adjustments or further optimizations to the addition / reduction / attribution division, specific shapes, positional relationships, connection methods, dimensional ratios, etc. of certain units (components) based on the technical concepts and exemplary drawings disclosed in the present application.

[0047] Figure 1 A flowchart of an English-assisted teaching method based on text resource integration is provided as an embodiment of the present application. DETAILED DESCRIPTION

[0048] The following is an explanation of the implementation of the present invention by specific specific examples. People familiar with this technology can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. It should be understood that these embodiments are only to further illustrate the present invention and cannot be understood as limiting the scope of protection of the present invention. Technical engineers in this field can make some non-essential improvements and adjustments to the present invention based on the contents of the above invention; based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] See also Figure 1 , an English auxiliary teaching method based on text resource integration, comprising the following steps:

[0050] S1. Determine the teaching objectives and themes, and clarify the course teaching objectives, such as improving students' listening, speaking, reading, writing, and cross-cultural communication skills, etc. Then, based on the teaching objectives, determine the theme of each stage or each teaching session.

[0051] S2. Screen and classify text resources. Collect text resources related to the topic from a wide range of channels such as textbooks, reference books, online resources, news reports, academic papers, etc., and screen out information that is closely related to the topic, representative and authoritative; classify according to the content and nature of the information, such as factual information, opinion comments, case studies, data statistics, etc.

[0052] The method for filtering text resources is as follows:

[0053] (1) Perform keyword matching. The steps of keyword matching are as follows:

[0054] 1) Keyword setting: According to the integrated theme, set a series of keywords closely related to the theme. For example, for the theme of "global climate change", keywords can include "global climate change", "greenhouse gas emissions", "environmental protection policy", "climate warming", "emission reduction measures", etc.;

[0055] 2) Text preprocessing: Use text processing tools (such as Python's NLTK library or spaCy library) to preprocess the collected text, including removing irrelevant information such as punctuation, numbers, special characters, and converting the text to lowercase;

[0056] 3) Word segmentation and part-of-speech tagging: Segment the preprocessed text and split the text into independent vocabulary units; perform part-of-speech tagging to mark the part of speech (such as noun, verb, adjective, etc.) for each vocabulary unit, which helps with subsequent keyword matching and semantic analysis;

[0057] 4) Keyword matching: Match the word segmentation results with the set keyword list, and record the frequency and position of each keyword in the text;

[0058] 5) Importance calculation: Calculate the importance of keywords in the text based on the frequency and position of keywords in the text (such as the title, the beginning of the text, the end, and other key positions); for example, the TF-IDF (term frequency-inverse document frequency) algorithm can be used to calculate the importance of keywords;

[0059] 6) Filter text: Based on the keyword matching results and importance calculation, set a threshold (such as the number of keyword occurrences, TF-IDF value, etc.) to filter out texts that are closely related to the topic.

[0060] For example: Text classification based on TF-IDF is as follows:

[0061] TF-IDF calculation: For each text, calculate the term frequency (TF) of each word in the text; for each word, calculate its inverse document frequency (IDF) in the entire text collection;

[0062] TF-IDF value = TF*IDF, which is used to measure the importance and discrimination of a word in a text;

[0063] Text vector representation: The text is represented as a TF-IDF vector, where each dimension corresponds to a word and the value of the vector is the TF-IDF value of the word;

[0064] Classification algorithm: Use K-means, SVM (support vector machine), naive Bayes and other classification algorithms to classify text vectors;

[0065] The algorithm assigns texts to different categories based on the similarity of their vectors or their distribution in feature space.

[0066] (2) Analyze the semantics. The steps of semantic analysis are as follows:

[0067] 1) Text preprocessing: Similar to the keyword matching method, the text is first preprocessed, including removing irrelevant information and converting to lowercase.

[0068] 2) Semantic model loading: Select a suitable semantic analysis model (such as BERT, GPT, etc.) and load the pre-trained model weights;

[0069] 3) Text encoding: The preprocessed text is input into the semantic model, and the model encodes the text into high-dimensional vector representations. These vectors contain the semantic information of the text;

[0070] 4) Semantic similarity calculation: For each text, its similarity with the topic description or the preset semantic center vector can be calculated; for example, cosine similarity can be used to calculate the angle between vectors, and the smaller the angle, the higher the similarity;

[0071] 5) Extraction of topic sentences and core ideas: Using the output of the semantic model, combined with the text structure and context information, extract the topic sentences and core ideas of the text; for example, you can find sentences with high semantic importance in the text as topic sentences;

[0072] 6) Text screening: Based on the results of semantic similarity calculation and the extraction of topic sentences and core ideas, screen out texts that are closely related to the topic, have clear ideas, and are representative and authoritative.

[0073] S3. Construct a clear logical framework. Constructing a logical framework is a key step in integrating and organizing text resources. It helps to convey information clearly and makes it easier to understand and absorb the content.

[0074] The specific steps for building a logical framework are as follows:

[0075] (1) Clarify the purpose: It is important to clarify the purpose of constructing a logical framework; what kind of English teaching activity is it designed for? Clarifying the purpose will help determine the overall direction and focus of the framework.

[0076] (2) Collect information: Based on all relevant information collected, organized and analyzed previously.

[0077] (3) Analyze logical relationships: Carefully analyze the logical relationships between the information; identify which information is causal, which is comparative, which is parallel, etc.; this helps to understand the internal connections between the information and lays the foundation for building a framework.

[0078] (4) Determine the structure: Based on logical relationships, choose an appropriate structure to organize information; common structures include general-specific-general structure, chronological structure, spatial layout structure, importance ranking structure, etc.

[0079] (5) Develop a framework: Based on the selected structure, develop a detailed framework; the framework should include titles, sub-titles, paragraph divisions, key points, etc.; ensure that the framework is clear, organized, and able to present information logically.

[0080] S4. Integrate text resources from different sources, and integrate the texts collected and analyzed previously into one text based on the established logical framework, with texts containing the same or similar viewpoints.

[0081] The steps to integrate based on viewpoints are as follows:

[0082] (1) For the text resources collected and analyzed above, we can extract the opinion sentences in the text; perform sentiment analysis on the opinion sentences to determine their sentiment tendency (positive, negative, neutral); conduct comparative analysis on the extracted different opinions to identify their similarities and differences; use clustering algorithms (such as K-means, hierarchical clustering, etc.) to group similar opinions again, so as to have a clearer understanding of the distribution and trends of different opinions.

[0083] (2) On the basis of comparative analysis, the above texts belonging to the same group of opinions are integrated. For the same group of opinion groups, text summarization technology is used to extract the key information and consensus points in the group; natural language generation technology (such as the GPT series of models) is used to integrate these key information and consensus points to form a more comprehensive and objective discussion; in the process of discussion generation, attention is paid to maintaining the fluency and logic of the language.

[0084] (3) The integrated text is then filled into the logical framework to display the analysis results; the quality of the generated argument is evaluated using a combination of automatic evaluation indicators (such as BLEU, ROUGE, etc.) and manual evaluation; the algorithm is optimized and adjusted based on the evaluation results to improve the accuracy and efficiency of subsequent integration.

[0085] For example, if you need to develop a topic about the development of artificial intelligence, you can collect predictions and opinions on the future development of artificial intelligence from different experts and scholars. In the article, you can first compare the similarities and differences between these different views, and then try to integrate the reasonable elements between them to form a statement that is both diverse and consistent.

[0086] S5. Design teaching activities based on the English theme and the integrated text resources mentioned above.

[0087] For example, a debate or group discussion can be used to further discuss the integrated viewpoints, while allowing students to use AI tools to assist, thereby further expanding students' vocabulary and stimulating their enthusiasm and initiative.

[0088] S6. Implement teaching and conduct evaluation and feedback. In class, teachers should flexibly use various teaching methods to guide students to actively participate in classroom activities and improve their language proficiency; assign appropriate homework, such as reading articles, writing exercises, etc., to consolidate the knowledge learned in class.

[0089] Regularly evaluate students' learning outcomes through tests, homework, classroom performance, etc.; provide students with timely feedback based on the evaluation results, point out their problems and make suggestions for improvement; adjust teaching strategies and resource selection in a timely manner based on the evaluation results and feedback to improve teaching effectiveness.

[0090] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements 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-assisted teaching method based on text resource integration, characterized in that: The following steps are involved: S1. Clarify the course teaching objectives and determine the theme of each stage or each teaching; S2. Screen and classify text resources, collect text resources related to the topic from a wide range of channels, screen out information that is closely related to the topic, representative and authoritative; classify according to the content and nature of the information; S3. Build a clear logical framework, analyze the logical relationship between various types of information, and build a clear framework to organize the integrated text resources based on the logical relationship; S4. Integrate text resources from different sources, and integrate the previously collected and analyzed texts with the same viewpoint into one text according to the established logical framework; S5. Design teaching activities. According to the English theme and the above integrated text resources, design targeted activities; S6. Implement teaching and conduct assessment and feedback.

2. The English-aided teaching method based on text resource integration according to claim 1 is characterized in that: The method for filtering text resources is as follows: (1) Keyword matching: set a keyword list related to the topic, use text processing tools to segment and tag the collected text, match the segmentation results with the keyword list, and filter out texts closely related to the topic based on the keyword matching results; (2) Semantic analysis: Use the semantic analysis model in natural language processing (NLP) technology to deeply understand the text, analyze the text's topic sentences, core ideas, and relevance to the topic, and screen out texts that are closely related to the topic, have clear ideas, and are representative and authoritative.

3. The English-aided teaching method based on text resource integration according to claim 2 is characterized in that: The specific steps for keyword matching are as follows: 1) Keyword setting: According to the integration theme, set a series of keywords closely related to the theme; 2) Text preprocessing: Use text processing tools to preprocess the collected text, including removing irrelevant information and text conversion; 3) Word segmentation and part-of-speech tagging: Segment the preprocessed text into independent vocabulary units; perform part-of-speech tagging to mark the part of speech for each vocabulary unit; 4) Keyword matching: Match the word segmentation results with the set keyword list, and record the frequency and position of each keyword in the text; 5) Importance calculation: Based on the frequency and position of the keywords in the text, the TF-IDF algorithm is used to calculate the importance of the keywords; 6) Filter text: According to the keyword matching results and importance calculation, set a TF-IDF value to filter out texts closely related to the topic.

4. The English-aided teaching method based on text resource integration according to claim 2 is characterized in that: The steps of semantic analysis are as follows: 1) Text preprocessing: Similar to the keyword matching method, the text is first preprocessed, including removing irrelevant information and converting it into small text. 2) Semantic model loading: Select a semantic analysis model and load the pre-trained model weights; 3) Text encoding: The preprocessed text is input into the semantic model, and the model encodes the text into high-dimensional vector representations. These vectors contain the semantic information of the text; 4) Semantic similarity calculation: For each text, calculate its similarity with the topic description or the preset semantic center vector; 5) Extraction of topic sentences and core ideas: Using the output of the semantic model, combined with text structure and context information, extract the topic sentences and core ideas of the text; 6) Text screening: Based on the results of semantic similarity calculation and the extraction of topic sentences and core ideas, screen out texts that are closely related to the topic, have clear ideas, and are representative and authoritative.

5. The English-aided teaching method based on text resource integration according to claim 1 is characterized in that: The logical framework adopts a general-specific-general structure, a time sequence structure, a spatial layout structure, an importance ranking structure, and a hierarchical structure.

6. The English-aided teaching method based on text resource integration according to claim 1, characterized in that: The specific steps to build a logical framework are as follows: (1) Clarify the purpose: It is necessary to clarify the purpose of constructing the logical framework and what kind of English teaching activity is being designed; (2) Collect information: Based on all relevant information collected and analyzed previously; (3) Analyze logical relationships: Carefully analyze the logical relationships between the information; identify which information is causal, which is contrasting, and which is parallel; (4) Determine the structure: Based on logical relationships, choose an appropriate structure to organize information; (5) Develop a framework: Based on the selected structure, develop a detailed framework; the framework should include titles, subtitles, paragraph divisions, and key points; ensure that the framework is clear, organized, and able to present information logically.

7. The English-aided teaching method based on text resource integration according to claim 1 is characterized in that: The steps to integrate the collected and analyzed texts according to the viewpoints are as follows: (1) Extract opinion sentences from the previously collected and analyzed text resources; perform sentiment analysis on opinion sentences to determine their sentiment orientation; perform comparative analysis on the extracted different opinion sentences to identify their similarities and differences; Use clustering algorithms to group similar opinions again to more clearly understand the distribution and trends of different opinions; (2) Based on comparative analysis, these texts belonging to the same group of opinions are integrated. For the same group of opinion groups, text summarization technology is used to extract key information and consensus points in the group; Use natural language generation technology to integrate these key information and consensus points to form a more comprehensive and objective discussion; (3) Then fill the integrated text into the logical framework to display the analysis results; The quality of the generated discourse is evaluated using a combination of automatic evaluation indicators and manual evaluation; the algorithm is optimized and adjusted based on the evaluation results to improve the accuracy and efficiency of subsequent integration.

8. The English-aided teaching method based on text resource integration according to claim 1, characterized in that: According to the evaluation results of step S6, timely feedback is given to students, their existing problems are pointed out and suggestions for improvement are put forward; according to the evaluation results and feedback, the teaching strategy and resource selection are adjusted in a timely manner to improve the teaching effect.

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