A teaching management method based on English online education

Abstract

This application discloses a teaching management method based on online English education, relating to the field of teaching resource management technology. The method includes segmenting a user's target teaching resource into several sub-contents related to questionable knowledge points. If the user's specific questionable sub-content is determined to be at the beginning of the sub-content set, supplementary detailed explanation content is matched from the resource library to obtain supplementary explanation content one. If the user stops watching the remaining content of the target teaching resource, a supplementary explanation mode one is established. If the user continues watching, and the progress of the continued-watched sub-content accounts for at least half of the total progress of the remaining sub-content, a supplementary explanation mode two is established. If the user's specific questionable sub-content is determined to be not at the beginning of the sub-content set, and the questionable sub-contents in the sub-content set are all sequentially adjacent, supplementary explanation content two is matched from the resource library, and a non-initiating supplementary explanation mode is established. This invention provides a teaching management method based on online English education that can improve the effective utilization rate of resources.

Description

Technical Field

[0001] This application relates to the field of teaching resource management technology, and in particular to a teaching management method based on online English education. Background Technology

[0002] With the rapid development of internet technology, online English education has become a trend and a mainstream learning method. This educational model breaks the limitations of time and space, allowing learners to access high-quality English teaching resources anytime, anywhere. However, to achieve effective online English education, it is necessary to rely on a series of advanced technologies to support aspects such as teaching management, curriculum design, student interaction, and learning outcome assessment.

[0003] In traditional technology, when users have questions while selecting one type of teaching resource for learning, it directly affects their learning progress of subsequent content. In such cases, users need to return to the main page to search for related content, which wastes their learning time and reduces their learning experience satisfaction and efficiency. Summary of the Invention

[0004] To overcome the shortcomings of the existing technology, this application provides a teaching management method based on online English education.

[0005] This application provides a teaching management method based on online English education, the method comprising:

[0006] Step S1: Divide the target teaching resource that the user retrieves and watches into several sub-contents of questionable knowledge points to obtain a sub-content set. If it is determined that the user's specific questionable sub-content is located at the beginning of the sub-content set, output preprocessing case one.

[0007] Step S2: Based on the preprocessing situation one, auxiliary detailed explanation content is matched from the resource library to obtain auxiliary explanation content one. The remaining content of the target teaching resource is statistically analyzed to see if the user continues to watch. If the user stops watching, the auxiliary explanation content one is extended to two additional trigger content forms to obtain extended form content one and extended form content two, so that the user can perform three auxiliary detailed explanations. Then, the auxiliary explanation mode one is output.

[0008] Step S3: If the user continues to watch, and the progress of the sub-content being watched accounts for at least half of the total progress of the remaining sub-content, then the auxiliary solution content one is further refined and extended to obtain extended and refined content, which is provided for the user to provide a second auxiliary explanation, and the auxiliary solution mode two is output.

[0009] Step S4: If it is determined that the user's specific question sub-content is located at a non-first end of the sub-content set, and the question sub-content in the sub-content set is not adjacent in time and the proportion of question sub-content is not less than the preset judgment threshold, then the first auxiliary solution mode is implemented.

[0010] Step S5: If it is determined that the user's specific question sub-content is located at a non-first end of the sub-content set, and the question sub-contents in the sub-content set are all adjacent in time, auxiliary detailed explanation content is matched from the resource library to obtain auxiliary explanation content two, so that the user can perform a second auxiliary detailed explanation, and the non-entry auxiliary explanation mode is output.

[0011] Preferably, the target teaching resources that the user searches for and watches are obtained, and the target teaching resources are divided into several knowledge points to obtain a knowledge point set. When the user has questions during the learning process of the target teaching resources, the questioned knowledge points are marked from the knowledge point set accordingly.

[0012] Based on the questionable knowledge points, mark the entry knowledge points that are preceding and adjacent to the questionable knowledge points in the knowledge point set;

[0013] The questionable knowledge points are divided into several sub-content sets;

[0014] If it is determined that the user's specific question sub-content is located at the beginning of the sub-content set, then it is necessary to combine the entry knowledge points to provide a secondary detailed explanation of the question knowledge points, and output preprocessing case one.

[0015] Preferably, according to the first preprocessing scenario, the entry sub-content that is sequentially adjacent to the first terminal content of the sub-content set is extracted from the entry knowledge point, and the entry sub-content and the first terminal content of the sub-content set are combined to form the sub-content to be explained in detail.

[0016] The degree of connection between the sub-content to be explained and other sub-content is evaluated to obtain a connection degree of 1.

[0017] Preferably, a resource library is obtained, and auxiliary detailed explanation content is matched from the resource library according to the first degree of connection to obtain auxiliary explanation content one. The auxiliary explanation content one has the same degree of connection with the other sub-contents in the sub-content set except for the first terminal content, and the content format of the auxiliary explanation content is the same as the content format of the knowledge point.

[0018] The remaining content of the target teaching resource is statistically analyzed to determine whether the user continues to watch it. If the user stops watching, the supplementary content one is extended into two additional trigger content formats to obtain extended content one and extended content two.

[0019] Preferably, when the user views the auxiliary content one at most twice and continues to view the other sub-contents in the sub-content set excluding the first sub-content, the detailed explanation result is output as successful.

[0020] If a user watches the supplementary explanation content one at least three times and still has questions, an invalid explanation result is output. Based on the invalid explanation result, extended content one is triggered to allow the user to perform a second supplementary explanation, and the second explanation result is output. If the second explanation result is still invalid, extended content three is triggered to allow the user to perform a third supplementary explanation, and the supplementary explanation mode one is switched to.

[0021] Preferably, if the user continues to watch, and the progress of the sub-content being watched accounts for at least half of the total progress of the remaining sub-content, then the auxiliary content is further refined and extended to obtain the extended and refined content. The content format of the extended and refined content is the same as that of the auxiliary content.

[0022] If the user continues to view the sub-content set without any questions after viewing the supplementary explanation, the result "Detailed explanation successful" will be output.

[0023] If a user still has questions after watching the first supplementary explanation and continues to watch the sub-content set, the extended and detailed content will be triggered to provide the user with a second supplementary explanation, and the output will switch to the second supplementary explanation mode.

[0024] Preferably, a preset percentage determination threshold is set. If it is determined that the user's specific question sub-content is not at the beginning of the sub-content set, and the question sub-content in the sub-content set is not adjacent in time and the number of question sub-content is not less than the percentage determination threshold, then it is necessary to combine the entry knowledge point to provide auxiliary content for secondary detailed explanation of the question knowledge point and output preprocessing situation three.

[0025] Based on the preprocessing scenario three, implement the first auxiliary solution mode.

[0026] Preferably, if it is determined that the user's specific question sub-content is located at a non-first end of the sub-content set, and the question sub-contents in the sub-content set are all adjacent in time, then output preprocessing case two;

[0027] Based on the second preprocessing scenario, the degree of connection between the question sub-content and other sub-content is evaluated to obtain the second degree of connection.

[0028] Based on the second degree of connectivity, auxiliary detailed explanation content is matched from the resource library to obtain auxiliary explanation content two. Auxiliary explanation content two is provided to the user for secondary auxiliary detailed explanation, and non-entry auxiliary explanation mode is output.

[0029] Compared with the prior art, the present invention has the following characteristics and beneficial effects:

[0030] By marking the specific knowledge points where users have questions, to determine whether the user's misunderstanding stems from a single point of confusion or from the lack of connection to adjacent knowledge points, two main scenarios are differentiated: Scenario 1 involves a direct correlation with the relevant knowledge points (requiring further explanation in conjunction with those points); Scenario 2 involves no direct correlation with the relevant knowledge points (not requiring further explanation). To improve the efficiency of subsequent explanations, a tailored content explanation model is developed for users with distinct personalities. This expands the variety of content formats available and enhances user satisfaction. For Scenario 1, two models are developed: one provides explanations in three different formats, triggering different formats based on the user's understanding; the other provides explanations in only one format. For preprocessing scenario two, a model is developed: if the user's question sub-contents are all sequentially adjacent, resources are directly matched from the resource library based on the correlation and connection between the question sub-contents and other sub-contents to provide auxiliary explanations for the user. By judging the above-mentioned differentiated scenarios and developing corresponding content explanation models for different scenarios, we can fully consider providing diverse content formats for personalized users, improve the effective utilization of resources, and enhance user experience satisfaction. Attached Figure Description

[0031] Figure 1 This embodiment is a flowchart illustrating the steps of a teaching management method based on online English education. Detailed Implementation

[0032] The present invention will be further described in detail below with reference to the following embodiments.

[0033] Reference Figure 1 A teaching management method based on online English education, comprising the following steps:

[0034] Step S1: Divide the target teaching resource that the user retrieves and watches into several sub-contents of questionable knowledge points to obtain a sub-content set. If it is determined that the user's specific questionable sub-content is located at the beginning of the sub-content set, output preprocessing case one.

[0035] Step S2: Based on preprocessing condition one, auxiliary detailed explanation content is matched from the resource library to obtain auxiliary explanation content one. The remaining content of the target teaching resource is statistically analyzed to determine whether the user continues to watch. If the user stops watching, the auxiliary explanation content one is extended into two additional trigger content forms to obtain extended form content one and extended form content two, so that the user can perform three auxiliary detailed explanations. Then, the auxiliary explanation mode one is output.

[0036] Step S3: If the user continues to watch, and the progress of the sub-content being watched accounts for at least half of the total progress of the remaining sub-content, then the auxiliary solution content one is further refined and extended to obtain extended and refined content, which is used for the user to provide a second auxiliary explanation, and the auxiliary solution mode two is output.

[0037] Step S4: If it is determined that the user's specific question sub-content is not at the beginning of the sub-content set, and the question sub-content in the sub-content set is not adjacent in time and the proportion of question sub-content is not less than the preset judgment threshold, then the first auxiliary solution mode is implemented.

[0038] Step S5: If it is determined that the user's specific question sub-content is located at a non-first end of the sub-content set, and the question sub-contents in the sub-content set are all adjacent in time, auxiliary detailed explanation content is matched from the resource library to obtain auxiliary explanation content two, so that the user can perform a second auxiliary detailed explanation, and the non-entry auxiliary explanation mode is output.

[0039] Specifically, by marking the specific knowledge points where users have questions, to determine whether the user's misunderstanding stems from a single knowledge point or from the lack of connection between the questioning knowledge point and adjacent, preceding knowledge points, two main scenarios are distinguished: Scenario 1 involves a connection to the preceding knowledge point (requiring further detailed explanation in conjunction with the preceding knowledge point); Scenario 2 involves no direct connection to the preceding knowledge point (not requiring further detailed explanation in conjunction with the preceding knowledge point). To improve the efficiency of subsequent detailed explanations, targeted content explanation modes are developed for users with distinct personalities, expanding the diversity and choice of resource content formats and improving user experience satisfaction. Specifically, for Scenario 1, two modes are developed: one mode provides detailed explanations in three different content formats, triggering different content formats based on the user's understanding; the other mode provides detailed explanations in only one content format. For preprocessing scenario two, a model is developed: if the user's question sub-contents are all sequentially adjacent, resources are directly matched from the resource library based on the correlation and connection between the question sub-contents and other sub-contents to provide auxiliary explanations for the user. By judging the above-mentioned differentiated scenarios and developing corresponding content explanation models for different scenarios, we can fully consider providing diverse content formats for personalized users, improve the effective utilization of resources, and enhance user experience satisfaction.

[0040] The specific step S1 includes the following sub-steps:

[0041] The system retrieves the target teaching resources that the user is searching for and viewing, divides the target teaching resources into several knowledge points to obtain a knowledge point set, and marks the questionable knowledge points from the knowledge point set when the user has questions during the learning process of the target teaching resources.

[0042] Based on the questionable knowledge points, mark the entry knowledge points that are preceding and adjacent to the questionable knowledge points in the knowledge point set.

[0043] The questionable knowledge points are divided into several sub-contents to obtain a set of sub-contents.

[0044] If it is determined that the user's specific question sub-content is located at the beginning of the sub-content set, then it is necessary to combine the entry knowledge points to provide a secondary detailed explanation of the question knowledge points, and output preprocessing case one.

[0045] Specifically, this could include: a set of knowledge points (e.g., if a course video involves multiple knowledge points, these points are extracted separately, such as A, B, C, D, and E); a questionable knowledge point (e.g., C); a key knowledge point (e.g., B); a set of sub-contents (e.g., if the explanation of a knowledge point requires examples, definitions, etc., to help users understand and master the knowledge point; if the sub-contents related to knowledge point C are c1, c2, c3, c4, c5, c6, and c7); and a preprocessing scenario 1 (e.g., if a user has questions about c1, it is highly likely that the process of introducing knowledge point C from knowledge point B has led to unclear understanding; in this case, the subsequent detailed explanation of sub-content c1 needs to be combined with knowledge point B to avoid significant separation in the user's understanding of knowledge points B and C).

[0046] The specific step S2 includes the following sub-steps:

[0047] Based on preprocessing scenario one, extract the entry sub-content that is sequentially adjacent to the first terminal content of the sub-content set from the entry knowledge points. Combine the entry sub-content and the first terminal content of the sub-content set to form the sub-content to be explained in detail.

[0048] The degree of connection and coherence between the detailed explanation sub-content and other sub-content is evaluated to obtain a coherence score of 1.

[0049] Obtain the resource library. Based on the degree of connection 1, match the auxiliary detailed content from the resource library to obtain auxiliary content 1. The degree of connection between auxiliary content 1 and other sub-contents in the sub-content set excluding the first terminal content is the same, and the content format of the auxiliary content is the same as the content format of the knowledge point.

[0050] The system tracks whether users continue watching the remaining content of the target teaching resources. If a user stops watching, the supplementary content 1 is extended into two additional trigger content formats, resulting in extended content format 1 and extended content format 2.

[0051] If a user views the supplementary content one at most twice, and continues to view the other sub-contents in the sub-content set excluding the first sub-content, then the detailed explanation will be successfully explained.

[0052] If a user watches the supplementary explanation content one at least three times and still has questions, an invalid explanation result is output. Based on the invalid explanation result, extended content one is triggered to allow the user to perform a second supplementary explanation, and the second explanation result is output. If the second explanation result is still invalid, extended content three is triggered to allow the user to perform a third supplementary explanation, and the supplementary explanation mode one is switched to.

[0053] Specifically, this could involve identifying the entry point sub-content (if knowledge point B includes sub-contents b1, b2, and b3, where b3 and c1 are sequentially adjacent, and b3 is learned first before c1 is learned sequentially, thus b3 is the entry point sub-content), the sub-content to be explained (i.e., b3 and c1), and a degree of coherence (e.g., using existing semantic analysis techniques: Natural Language Processing (NLP): Using NLP techniques, especially text similarity calculation, keyword extraction, and semantic role labeling, the text content in knowledge point descriptions can be analyzed to find the semantic connections between them. For example, by calculating the cosine similarity between two knowledge point descriptions, their semantic similarity can be quantified. Or a knowledge graph: constructing or... Using existing knowledge graphs, knowledge points are treated as nodes, and the relationships between them are treated as edges. Through traversal and querying of the knowledge graph, the relationships between knowledge points can be visually displayed, and their tightness can be assessed. Here, it refers to the degree of connection between sub-contents: that is, the degree of connection between b3 and c1 and c2, c3, c4, c5, c6, and c7 (if G1), auxiliary content one (if R1 and r1, where the degree of connection between R1 and r1 and c2, c3, c4, c5, c6, and c7 is also G1, indicating that R1 and r1 can be used to provide detailed explanations for users who do not understand the content of b3 and c1 clearly; the level of detail of R1 and r1 is greater than that of b3 and c1). The level of detail in the content), if the user stops watching (e.g., the user is impatient when there are questions, cannot patiently continue watching the following content, and believes that the understanding of the following content will be greatly affected), extended content format one and extended content format two (for example, if the content format of supplementary content one is purely text-based, then the content format is changed according to the user's personalization, such as changing it to a picture presentation or a game presentation, to reduce the boredom of the content, and the level of detail of extended content format one is greater than that of supplementary content one, and the level of detail of extended content format two is greater than that of extended content format one), detailed explanation success results (e.g., based on the user's viewing habits of teaching resources, when the user watches supplementary content one repeatedly) If the user continues to view content c2, c3, c4, c5, c6, and c7 after no more than three viewings, it indicates that the user has understood c1. The user may view supplementary content one no more than twice, and these two opportunities are used to limit the user's content reception buffer. The user will then switch to supplementary content mode one (meaning that the user still does not fully understand the c1 sub-content after the content reception buffer limit has been exceeded. At this time, supplementary content one needs to be further refined, which results in extended content one. If the user's result after viewing supplementary content one is invalid, extended content one will be immediately shown to the user for viewing. If the user still does not fully understand after viewing, extended content two will be triggered to allow the user to provide a detailed explanation of the c1 sub-content three times).

[0054] The specific step S3 includes the following sub-steps:

[0055] If the user continues to watch, and the progress of the sub-content being watched accounts for at least half of the total progress of the remaining sub-content, then the auxiliary content will be further refined and extended to obtain extended and refined content. The content format of the extended and refined content is the same as that of the auxiliary content.

[0056] If the user continues to view the sub-content set without any questions after viewing the supplementary explanation, the result "Detailed explanation successful" will be output.

[0057] If a user still has questions after watching the first supplementary explanation and continues to watch the sub-content set, the extended and detailed content will be triggered to provide the user with a second supplementary explanation, and the output will switch to the second supplementary explanation mode.

[0058] Specifically, for example, extend and refine the content (if the user continues to watch, it means that the user's personalization is not obvious, they are relatively patient, and they are trying to understand the content of c2, c3, c4, c5, c6, and c7 by reverse reasoning. At this time, the auxiliary content one only needs to be refined and the original content format is maintained), switch to auxiliary content mode two (that is, when the user continues to watch c2, c3, c4, c5, c6, and c7 after watching auxiliary content one, there is a question about c1 (this can be judged by whether the user repeatedly pulls back the progress bar or submits question text during the process of continuing to watch c2, c3, c4, c5, c6, and c7)).

[0059] The specific step S4 includes the following sub-steps:

[0060] If a user's specific question sub-content is determined to be located at a non-first end of the sub-content set, and the question sub-content in the sub-content set is not adjacent in time and the number of question sub-content is not less than the percentage threshold, then it is necessary to provide a secondary detailed explanation of the question knowledge point in conjunction with the entry knowledge point, and output preprocessing case three.

[0061] Based on preprocessing scenario three, we will implement the first approach to auxiliary solution.

[0062] Specifically, if the preset percentage judgment threshold is 3 / 10, and the user's specific question sub-contents are c2, c4, and c6, and c2, c4, and c6 are located at the non-first end of the sub-content set, and the question sub-contents in the sub-content set are all non-adjacent in time, and the proportion of c2, c4, and c6 is 3 / 7 which is greater than 3 / 10, then it can be determined that the user's question in this case is most likely due to a misunderstanding in the process of introducing the content of the entry sub-content b3, and it is necessary to provide a second detailed explanation of the question knowledge points in conjunction with the entry knowledge points), the entry auxiliary explanation mode one is implemented (the explanation is the same as the three auxiliary detailed explanations specifically formulated for preprocessing case one, and will not be explained in detail here).

[0063] The specific step S5 includes the following sub-steps:

[0064] If it is determined that the user's specific question sub-content is not at the beginning of the sub-content set, and the question sub-contents in the sub-content set are all adjacent in time, then output preprocessing case two.

[0065] Based on preprocessing scenario two, the degree of connection between the question sub-content and other sub-content is evaluated to obtain connection degree two.

[0066] Based on the second degree of connection, auxiliary detailed explanation content is matched from the resource library to obtain auxiliary explanation content two. Auxiliary explanation content two is provided to users for secondary auxiliary detailed explanation, and non-entry auxiliary explanation mode is output.

[0067] Specifically, in preprocessing scenario two (the user's specific question sub-contents are c4, c5, and c6, which are not at the beginning of the sub-content set, and the question sub-contents in the sub-content set are all adjacent in time), the degree of connection two (referring to the degree of connection between c4, c5, and c6 and c1, c2, c3, and c7 if it is G2), and the non-entry auxiliary solution mode (if the auxiliary solution content two is r2, r3, and r4, where the degree of connection between r2, r3, and r4 and c1, c2, c3, and c7 is also G2, it means that r2, r3, and r4 can be used to provide detailed explanations for users who do not understand the content of c4, c5, and c6 clearly, and provide the explanations of r2, r3, and r4 to users for secondary auxiliary explanations. The content format of r2, r3, and r4 is the same as that of c4, c5, and c6, and the degree of detail of r2, r3, and r4 is greater than that of c4, c5, and c6).

[0068] The above are all preferred embodiments of the present application, and are not intended to limit the scope of protection of the present application. Therefore, any equivalent changes made based on the structure, shape, and principle of the present application should be included in the scope of protection of the present application.

Claims

1. A teaching management method based on online English education, characterized in that, Includes the following steps: Step S1: Divide the target teaching resource that the user retrieves and watches into several sub-contents of questionable knowledge points to obtain a sub-content set. If it is determined that the user's specific questionable sub-content is located at the beginning of the sub-content set, output preprocessing case one. Step S2: Based on the preprocessing situation one, auxiliary detailed explanation content is matched from the resource library to obtain auxiliary explanation content one. The remaining content of the target teaching resource is statistically analyzed to see if the user continues to watch. If the user stops watching, the auxiliary explanation content one is extended to two additional trigger content forms to obtain extended form content one and extended form content two, so that the user can perform three auxiliary detailed explanations. Then, the auxiliary explanation mode one is output. Step S3: If the user continues to watch, and the progress of the sub-content being watched accounts for at least half of the total progress of the remaining sub-content, then the auxiliary solution content one is further refined and extended to obtain extended and refined content, which is provided for the user to provide a second auxiliary explanation, and the auxiliary solution mode two is output. Step S4: If it is determined that the user's specific question sub-content is located at a non-first end of the sub-content set, and the question sub-content in the sub-content set is not adjacent in time and the proportion of question sub-content is not less than the preset judgment threshold, then the first auxiliary solution mode is implemented. Step S5: If it is determined that the user's specific question sub-content is located at a non-first end of the sub-content set, and the question sub-contents in the sub-content set are all adjacent in time, auxiliary detailed explanation content is matched from the resource library to obtain auxiliary explanation content two, so that the user can perform a second auxiliary detailed explanation, and the non-entry auxiliary explanation mode is output.

2. The teaching management method based on online English education according to claim 1, characterized in that, Step S1 includes: The system obtains the target teaching resources that the user searches for and watches, divides the target teaching resources into several knowledge points to obtain a knowledge point set, and marks the questionable knowledge points from the knowledge point set when the user has questions during the learning process of the target teaching resources. Based on the questionable knowledge points, mark the entry knowledge points that are preceding and adjacent to the questionable knowledge points in the knowledge point set; The questionable knowledge points are divided into several sub-content sets; If it is determined that the user's specific question sub-content is located at the beginning of the sub-content set, then it is necessary to combine the entry knowledge points to provide a secondary detailed explanation of the question knowledge points, and output preprocessing case one.

3. The teaching management method based on online English education according to claim 2, characterized in that, Step S2 includes: According to the first preprocessing scenario, the entry sub-content that is sequentially adjacent to the first terminal content of the sub-content set is extracted from the entry knowledge point, and the entry sub-content and the first terminal content of the sub-content set are combined to form the sub-content to be explained in detail. The degree of connection between the sub-content to be explained and other sub-content is evaluated to obtain a connection degree of 1.

4. The teaching management method based on online English education according to claim 3, characterized in that, Step S2 also includes: Obtain the resource library, and according to the first degree of connection, match the auxiliary detailed explanation content from the resource library to obtain the first auxiliary explanation content. The auxiliary explanation content has the same degree of connection with the other sub-contents in the sub-content set except for the first terminal content, and the content format of the auxiliary explanation content is the same as the content format of the knowledge point. The remaining content of the target teaching resource is statistically analyzed to determine whether the user continues to watch it. If the user stops watching, the supplementary content one is extended into two additional trigger content formats to obtain extended content one and extended content two.

5. The teaching management method based on online English education according to claim 4, characterized in that, Step S2 also includes: If the user views the auxiliary content one at most twice, and continues to view the other sub-contents in the sub-content set excluding the first sub-content, then the detailed explanation will be successfully explained. If a user watches the supplementary explanation content one at least three times and still has questions, an invalid explanation result is output. Based on the invalid explanation result, extended content one is triggered to allow the user to perform a second supplementary explanation, and the second explanation result is output. If the second explanation result is still invalid, extended content three is triggered to allow the user to perform a third supplementary explanation, and the supplementary explanation mode one is switched to.

6. The teaching management method based on online English education according to claim 5, characterized in that, Step S3 includes: If the user continues to watch, and the progress of the sub-content being watched accounts for at least half of the total progress of the remaining sub-content, then the auxiliary content will be further refined and extended to obtain the extended and refined content. The content format of the extended and refined content is the same as that of the auxiliary content. If the user continues to view the sub-content set without any questions after viewing the supplementary explanation, the result "Detailed explanation successful" will be output. If a user still has questions after watching the first supplementary explanation and continues to watch the sub-content set, the extended and detailed content will be triggered to provide the user with a second supplementary explanation, and the output will switch to the second supplementary explanation mode.

7. The teaching management method based on online English education according to claim 6, characterized in that, Step S4 includes: If the user's specific question sub-content is determined to be located at a non-first end of the sub-content set, and the question sub-content in the sub-content set is not adjacent in time and the number of question sub-content is not less than the percentage threshold, then it is necessary to provide a secondary detailed explanation of the question knowledge point in conjunction with the entry knowledge point and output the preprocessing situation three. Based on the preprocessing scenario three, implement the first auxiliary solution mode.

8. The teaching management method based on online English education according to claim 7, characterized in that, Step S5 includes: If it is determined that the user's specific question sub-content is not at the beginning of the sub-content set, and the question sub-contents in the sub-content set are all adjacent in time, then output preprocessing case two; Based on the second preprocessing scenario, the degree of connection between the question sub-content and other sub-content is evaluated to obtain the second degree of connection. Based on the second degree of connectivity, auxiliary detailed explanation content is matched from the resource library to obtain auxiliary explanation content two. Auxiliary explanation content two is provided to the user for secondary auxiliary detailed explanation, and non-entry auxiliary explanation mode is output.

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