Teaching management method based on English online education

Abstract

The invention discloses a teaching management method based on English online education, and relates to the technical field of teaching resource management, and the method comprises the steps: carrying out the segmentation of a plurality of sub-contents of question knowledge points of a target teaching resource retrieved and watched by a user, and if the specific question sub-contents of the user are located at the head end of a sub-content set, carrying out the segmentation of the sub-contents; if the user does not watch the target teaching resource, matching the auxiliary detailed solution content from the resource library to obtain an auxiliary solution content I, if the user stops watching the residual content of the target teaching resource, formulating an auxiliary solution switching mode I, and if the user continues watching and the ratio of the progress of the continuously watched sub-content to the total progress of the residual sub-content is at least half, formulating an auxiliary solution switching mode II, if it is judged that the specific question sub-content of the user is located at the non-head end of the sub-content set and the time sequences of the question sub-content in the sub-content set are all adjacent, matching second auxiliary solution content from the resource library, and formulating a non-cut-in auxiliary solution mode. The English online education-based teaching management method provided by the invention can improve the effective utilization rate of resources.

Description

Technical Field

[0001] The present application relates to the technical field of teaching resource management, and in particular to a teaching management method based on English online education. Background Art

[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 constraints of time and space, allowing learners to receive high-quality English teaching resources anytime and anywhere. However, effective online English education requires a range of advanced technologies to support teaching management, course design, student interaction, and learning outcome evaluation.

[0003] In traditional technology, when a user has questions while searching for one of the teaching resources for learning, it will directly affect the learning progress of the subsequent content. In this case, the user needs to return to the main page to search for related content in the question part, which wastes the user's learning time and reduces the user's learning experience satisfaction and learning efficiency. Summary of the Invention

[0004] In order to overcome the above-mentioned deficiencies of the prior art, the present application provides a teaching management method based on English online education.

[0005] This application provides a teaching management method based on English online education, the method comprising: Step S1: Segment the target teaching resource retrieved and viewed by the user into several sub-contents of the questionable knowledge point to obtain a sub-content set. If it is determined that the specific questionable sub-content of the user is at the beginning of the sub-content set, output pre-processing condition 1. Step S2: According to the pre-processing condition 1, auxiliary detailed explanation content is matched from the resource library to obtain auxiliary explanation content 1, and statistics are collected on whether the user continues to watch the remaining content of the target teaching resource. If the user stops watching, the auxiliary explanation content 1 is extended with two additional trigger content forms to obtain extended form content 1 and extended form content 2, so that the user can perform three auxiliary detailed explanations, and the output is switched to auxiliary explanation mode 1; Step S3: If the user continues to watch the sub-content, and the progress of the sub-content being watched accounts for at least half of the total progress of the remaining sub-content, the auxiliary explanation content 1 is further refined and extended to obtain extended and refined content for the user to perform a secondary auxiliary explanation, and the output is switched to the auxiliary explanation mode 2; Step S4: If it is determined that the user's specific question sub-content is not at the beginning of the sub-content set, the question sub-contents in the sub-content set are not adjacent in time sequence, and the proportion of the question sub-contents is not less than the preset determination threshold, then the auxiliary solution mode 1 is implemented; In step S5, if it is determined that the user's specific question sub-content is located at a non-head end of the sub-content set, and the question sub-contents in the sub-content set are adjacent in time sequence, auxiliary detailed explanation content is matched from the resource library to obtain auxiliary explanation content 2, so that the user can provide secondary auxiliary detailed explanation, and a non-entry auxiliary explanation mode is output.

[0006] Preferably, a target teaching resource retrieved and viewed by a user is obtained, and the target teaching resource is divided into several knowledge points to obtain a knowledge point set. When the user has questions in the process of learning the target teaching resource, the questionable knowledge points are marked accordingly from the knowledge point set. According to the questionable knowledge point, marking the entry knowledge points that are located before and adjacent to the questionable knowledge point in time sequence from the knowledge point set; Divide the questionable knowledge point into several sub-contents to obtain a sub-content set; If it is determined that the user's specific question sub-content is located at the beginning of the sub-content set, it is necessary to provide a secondary detailed explanation of the question knowledge point with auxiliary content in combination with the entry knowledge point, and output the pre-processing situation one.

[0007] Preferably, according to the first preprocessing scenario, the entry sub-content that is sequentially adjacent to the first sub-content of the sub-content set is extracted from the entry knowledge point, and the entry sub-content and the first sub-content in the sub-content set are combined into the sub-content to be explained in detail; The correlation and connection degree between the sub-content to be explained in detail and other sub-contents is evaluated to obtain a connection degree of one.

[0008] 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, wherein the auxiliary explanation content one has the same degree of connection with other sub-contents in the sub-content set excluding the header sub-content, and the content format of the auxiliary explanation content is the same as the content format of the entry knowledge point; Statistics are collected on whether the user continues to watch the remaining content of the target teaching resource. If the user stops watching, the auxiliary content one is extended with two additional trigger content forms to obtain extended form content one and extended form content two.

[0009] Preferably, when the user has watched the auxiliary explanation content 1 for at most two repetitions and continues to watch other sub-contents in the sub-content set excluding the first sub-content, a detailed explanation success result is output; When the user has watched the auxiliary explanation content one for at least three times and still has questions, the invalid result of the first detailed explanation is output. According to the invalid result of the first detailed explanation, the extended form content one is triggered to provide the user with a second auxiliary detailed explanation, and the second detailed explanation result is output. If the second detailed explanation result is still invalid, the extended form content three is triggered to provide the user with a third auxiliary detailed explanation, and the output enters the auxiliary explanation mode one.

[0010] Preferably, if the user continues to watch, and the progress of the sub-content that the user continues to watch accounts for at least half of the total progress of the remaining sub-content, the auxiliary explanation content is subjected to secondary content refinement and extension to obtain extended and refined content, and the content format of the extended and refined content is the same as that of the auxiliary explanation content; When the user continues to watch the sub-content set without any questions after watching the auxiliary explanation content 1, the detailed explanation success result is output; When the user continues to watch the sub-content set after watching the auxiliary explanation content one and still has questions, the extended and detailed content is triggered to provide the user with a second auxiliary explanation, and the output enters the auxiliary explanation mode two.

[0011] Preferably, a ratio determination threshold is preset. If it is determined that the user's specific question sub-content is located at a non-head end of the sub-content set, and the temporal sequence of the question sub-contents in the sub-content set is non-adjacent, and the number of question sub-contents is not less than the ratio determination threshold, it is necessary to provide a secondary detailed explanation of the question knowledge point with auxiliary content in combination with the entry knowledge point, and output the third pre-processing situation. According to the pre-processing situation three, the auxiliary solution mode one is implemented.

[0012] Preferably, if it is determined that the user's specific question sub-content is located at a non-head end of the sub-content set, and the question sub-contents in the sub-content set are all adjacent in time sequence, then the second pre-processing situation is output; According to the second pre-processing condition, the correlation and cohesion between the question sub-content and the other sub-content are evaluated to obtain a second cohesion degree; According to the second degree of connection, auxiliary explanation content is matched from the resource library to obtain auxiliary explanation content 2, and the auxiliary explanation content 2 is provided to the user for secondary auxiliary explanation, and a non-entry auxiliary explanation mode is output.

[0013] Compared with the prior art, the present invention has the following characteristics and beneficial effects: By marking the specific knowledge points that users have questions about, in order to determine whether the user's misunderstanding is simply the questioned knowledge point or the misunderstanding is caused by the content connection and connection with the entry knowledge point that is chronologically preceding and adjacent to the questioned knowledge point, we distinguish between two main situations: one is the situation where the questioned knowledge point has a correlation with the entry knowledge point (subsequently, it is necessary to combine the entry knowledge point to provide auxiliary content for the questioned knowledge point in a secondary detailed explanation), which is pre-processing situation one; the other is the situation where the questioned knowledge point has no direct correlation with the entry knowledge point (subsequently, it is not necessary to combine the entry knowledge point to provide auxiliary content for the questioned knowledge point in a secondary detailed explanation), which is pre-processing situation two. In order to improve the efficiency of subsequent secondary detailed explanations, targeted content detailed explanation models are developed for users with obvious personalization to expand the diversity and selectivity of resource content forms and improve user experience satisfaction. In other words, two models are developed for pre-processing situation one: one model is to provide content detailed explanations in three different content forms, and to trigger different content forms based on the user's understanding. The other model is to provide content detailed explanations in one content form. A model is formulated for the second preprocessing situation, that is, if the sub-contents of the user's question are adjacent in time sequence, resources are directly matched from the resource library based on the correlation and connection between the sub-content of the question and other sub-contents, so as to achieve auxiliary detailed explanation for the user. Through the judgment of the above-mentioned distinctive situations and the formulation of corresponding different content detailed explanation models for different situations, full consideration is given to providing diverse content forms for personalized users, thereby improving the effective utilization of resources and user experience satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 This is a flowchart of a teaching management method based on English online education mainly embodied in this embodiment. DETAILED DESCRIPTION

[0015] The present invention is further described in detail below with reference to the following examples.

[0016] Reference Figure 1 , a teaching management method based on English online education, the method comprising the following steps: Step S1 : dividing the target teaching resource retrieved and viewed by the user into several sub-contents of the questionable knowledge point to obtain a sub-content set. If it is determined that the user's specific questionable sub-content is at the beginning of the sub-content set, outputting pre-processing condition 1.

[0017] Step S2, according to preprocessing situation one, match the auxiliary detailed explanation content from the resource library to obtain auxiliary explanation content one, and count whether the user continues to watch the remaining content of the target teaching resource. If the user stops watching, the auxiliary explanation content one is extended with 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, and the output enters auxiliary explanation mode one.

[0018] 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, the auxiliary explanation content 1 is further refined and extended to obtain extended and refined content for the user to perform secondary auxiliary explanation, and the output is switched to auxiliary explanation mode 2.

[0019] 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-contents in the sub-content set are not adjacent in time sequence, and the proportion of the question sub-contents is not less than the preset judgment threshold, enter the auxiliary solution mode 1.

[0020] In step S5, if it is determined that the user's specific question sub-content is located at a non-head end of the sub-content set, and the question sub-contents in the sub-content set are adjacent in time sequence, auxiliary detailed explanation content is matched from the resource library to obtain auxiliary explanation content 2, so that the user can provide secondary auxiliary detailed explanation, and a non-entry auxiliary explanation mode is output.

[0021] Specifically, by marking the specific knowledge points that the user has questions about, in order to determine whether the user does not understand the questioned knowledge point alone or because the misunderstanding is caused by the content connection and connection degree with the entry knowledge point that is chronologically before and adjacent to the questioned knowledge point, two main situations are distinguished. One is the situation where the questioned knowledge point has a correlation with the entry knowledge point (subsequently, it is necessary to combine the entry knowledge point to provide auxiliary content for the questioned knowledge point in a secondary detailed explanation), which is pre-processing situation one; the other is the situation where the questioned knowledge point has no direct correlation with the entry knowledge point (subsequently, it is not necessary to combine the entry knowledge point to provide auxiliary content for the questioned knowledge point in a secondary detailed explanation), which is pre-processing situation two. In order to improve the efficiency of subsequent secondary detailed explanation, targeted content detailed explanation models are formulated for users with obvious personalization to expand the diversity and selectivity of resource content forms and improve user experience satisfaction. That is, two models are formulated for pre-processing situation one: one model is to provide content detailed explanations in three different content forms, and to trigger different content forms according to the user's understanding. The other model is to provide content detailed explanations in one content form. A model is formulated for the second preprocessing situation, that is, if the sub-contents of the user's question are adjacent in time sequence, resources are directly matched from the resource library based on the correlation and connection between the sub-content of the question and other sub-contents, so as to achieve auxiliary detailed explanation for the user. Through the judgment of the above-mentioned distinctive situations and the formulation of corresponding different content detailed explanation models for different situations, full consideration is given to providing diverse content forms for personalized users, thereby improving the effective utilization of resources and user experience satisfaction.

[0022] The specific step S1 includes the following sub-steps: The target teaching resources that the user searches 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 in the process of learning the target teaching resources, the questionable knowledge points are marked accordingly from the knowledge point set.

[0023] According to the questioned knowledge point, the entry knowledge points that are located before and adjacent to the questioned knowledge point in time sequence are marked from the knowledge point set.

[0024] The questionable knowledge point is divided into several sub-contents to obtain a sub-content set.

[0025] If it is determined that the user's specific question sub-content is located at the beginning of the sub-content set, it is necessary to provide a secondary detailed explanation of the question knowledge point with auxiliary content in combination with the entry knowledge point, and output the pre-processing situation one.

[0026] Specifically, there are knowledge point sets (for example, if a course teaching video involves multiple knowledge points, then the multiple knowledge points will be extracted separately, if they are A, B, C, D, and E respectively), question knowledge points (if it is C), entry knowledge points (that is, B), sub-content sets (for example, the explanation of a knowledge point needs to be enriched with examples, definitions, etc. to facilitate users to understand and master the knowledge point. If the sub-content related to knowledge point C is c1, c2, c3, c4, c5, c6, c7), preprocessing situation one (for example, when the user has questions about c1, it is very likely that the process of introducing knowledge point B to knowledge point C has caused the user to have unclear understanding. In this case, the subsequent expanded and detailed explanation of the sub-content of c1 needs to be combined with knowledge point B to avoid the user's large-scale separation of content understanding of knowledge point B and knowledge point C).

[0027] The specific step S2 includes the following sub-steps: According to the first preprocessing condition, the entry sub-content that is sequentially adjacent to the first sub-content of the sub-content set is extracted from the entry knowledge point, and the entry sub-content and the first sub-content in the sub-content set are combined into the sub-content to be explained in detail.

[0028] The correlation and connection between the detailed explanation sub-content and other sub-contents are evaluated to obtain a connection degree of one.

[0029] Obtain a resource library, and match auxiliary detailed explanation content from the resource library based on the first degree of connection to obtain auxiliary explanation content one. The auxiliary explanation content one has the same degree of association and connection with other sub-contents in the sub-content set excluding the first sub-content, and the content format of the auxiliary explanation content is the same as the content format of the entry knowledge point.

[0030] Statistics are collected on whether the user continues to watch the remaining content of the target teaching resource. If the user stops watching, the auxiliary content one is extended with two additional trigger content forms to obtain extended form content one and extended form content two.

[0031] When the user watches the auxiliary explanation content 1 for at most two times and continues to watch other sub-contents in the sub-content set excluding the first sub-content, a detailed explanation success result is output.

[0032] When the user has watched the auxiliary explanation content one for at least three times and still has questions, the invalid result of the first detailed explanation is output. According to the invalid result of the first detailed explanation, the extended form content one is triggered to provide the user with a second auxiliary detailed explanation, and the second detailed explanation result is output. If the second detailed explanation result is still invalid, the extended form content three is triggered to provide the user with a third auxiliary detailed explanation, and the output enters the auxiliary explanation mode one.

[0033] Specifically, such as cutting into sub-content (if the sub-contents included in knowledge point B are b1, b2, and b3, among which b3 and c1 are adjacent in time sequence, and b3 is learned first, and then c1 content is learned in a connected manner, so b3 is the cutting-in sub-content), the sub-content to be explained in detail (i.e. b3 and c1), the degree of connection is one (such as using semantic analysis technology in the existing technology: Natural Language Processing (NLP): Using NLP technology, especially text similarity calculation, keyword extraction and semantic role labeling methods, the text content in the knowledge point description can be analyzed to find the semantic connection between them. For example, by calculating the cosine similarity between the descriptions of two knowledge points, the semantic similarity between them can be quantified. Or knowledge graph: construct or Using the existing knowledge graph, knowledge points are used as nodes, and the relationships between them are used as edges. By traversing and querying the knowledge graph, the relationship between knowledge points can be intuitively displayed and its closeness can be evaluated. Here, it refers to the degree of association and connection between sub-contents: that is, the degree of association and connection between b3 and c1 and c2, c3, c4, c5, c6, and c7. If it is G1), auxiliary content one (if it is R1 and r1, where the degree of association and 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 users with detailed content explanations for content b3 and c1 that is not clearly understood. The content detail of R1 and r1 is greater than that of b3 and c1. the degree of detail of the content), if the user stops watching (for example, the user is impatient when there are questions and can no longer patiently continue to watch the following content, and believes that the understanding of the following content will also be greatly affected), extended form content one and extended form content two (for example, the content form of auxiliary content one is a pure text form, then according to the user's personalization, the content form is transformed, if it is transformed into a picture form or a game form to reduce the boringness of the content, and the detail of extended form content one is greater than that of auxiliary content one, and the detail of extended form content two is greater than that of extended form content one), detailed explanation of successful results (for example, according to the user's habit of watching teaching resources, when the user repeats watching auxiliary content one for the number of times When the user has watched the sub-content of c1 for no more than three times and continues to watch the contents of c2, c3, c4, c5, c6 and c7, it means that the user has understood c1, and the number of times the auxiliary explanation content one has been watched is no more than two times, and these two opportunities are used for the buffer limitation conditions for the user to receive the content), the auxiliary explanation mode 1 is entered (it means that the user still does not understand the sub-content of c1 well after the buffer limitation conditions for the content reception have passed. At this time, the auxiliary explanation content needs to be refined again and again, that is, the extended form content 1 is obtained. After the result of the user watching the auxiliary explanation content 1 is invalid, the extended form content 1 is immediately displayed to the user for viewing. If the user still does not understand it well after viewing it, the extended form content 2 is triggered for the user to receive three detailed explanations of the sub-content of c1).

[0034] The specific step S3 includes the following sub-steps: If the user continues to watch, and the progress of the sub-content he continues to watch accounts for at least half of the total progress of the remaining sub-content, the auxiliary content will be refined and extended twice to obtain extended and refined content, and the content form of the extended and refined content is the same as the content form of the auxiliary content.

[0035] When the user continues to watch the sub-content set without any questions after watching the auxiliary explanation content one, the detailed explanation success result is output.

[0036] When the user continues to watch the sub-content set after watching the auxiliary explanation content one and still has questions, the extended and detailed content is triggered to provide the user with a second auxiliary explanation, and the output enters the auxiliary explanation mode two.

[0037] Specifically, such as extending and refining the content (if the user continues to watch, it means that the user's personalization is not obvious, and he is relatively patient, and tries to understand and reversely infer the contents of c2, c3, c4, c5, c6, and c7. At this time, the auxiliary explanation content one only needs to be refined and the original content format can be maintained), and enter the auxiliary explanation mode two (that is, when the user continues to watch c2, c3, c4, c5, c6, and c7 after watching the auxiliary explanation content one, there is a question about c1 (which can be judged based on whether the user repeatedly pulls back the progress bar and submits the question text while continuing to watch c2, c3, c4, c5, c6, and c7)).

[0038] The specific step S4 includes the following sub-steps: A preset ratio determination threshold is set. If it is determined that the user's specific question sub-content is located at a non-head end of the sub-content set, and the temporal sequence of the question sub-contents in the sub-content set is non-adjacent, and the number of question sub-contents is not less than the ratio determination threshold, it is necessary to provide a secondary detailed explanation of the question knowledge point with auxiliary content in combination with the entry knowledge point, and output preprocessing situation three.

[0039] According to the pre-processing situation three, the auxiliary solution mode one is implemented.

[0040] Specifically, if the preset proportion judgment threshold is 3 / 10, and pre-processing situation three (the user's specific question sub-contents are c2, c4, and c6, and c2, c4, and c6 are located at non-head ends of the sub-content set, and the time sequence of the question sub-contents in the sub-content set are non-adjacent, among which the number of c2, c4, and c6 accounts for 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 content introduction process of the entry sub-content b3, and it is necessary to provide a secondary detailed explanation of the question knowledge point with auxiliary content in combination with the entry knowledge point), the entry auxiliary explanation mode one is implemented (the explanation is the same as the three auxiliary detailed explanations specifically formulated for pre-processing situation one, and no further explanation is given here).

[0041] The specific step S5 includes the following sub-steps: If it is determined that the user's specific question sub-content is located at a non-head end of the sub-content set, and the question sub-contents in the sub-content set are all adjacent in time sequence, then the second pre-processing situation is output.

[0042] According to the second pre-processing situation, the correlation and cohesion between the question sub-content and other sub-contents are evaluated to obtain the second cohesion degree.

[0043] According to the second degree of connection, auxiliary explanation content is matched from the resource library to obtain auxiliary explanation content 2, and the auxiliary explanation content 2 is provided to the user for secondary auxiliary explanation, and a non-entry auxiliary explanation mode is output.

[0044] Specifically, such as the pre-processing situation two (the user's specific question sub-content is c4, c5, c6, cc4, c5, c6 are located at the non-head end of the sub-content set, and the question sub-content in the sub-content set are adjacent in time sequence), the second degree of connection (referring to the correlation and connection degree between c4, c5, c6 and c1, c2, c3, c7 is G2), the non-entry auxiliary solution mode (if the auxiliary solution content two is r2, r3, r4, among which the correlation and connection degree between r2, r3, r4 and c1, c2, c3, c7 is also G2, it means that r2, r3, r4 can be used to provide users with detailed content explanations for the unclear understanding of c4, c5, c6 content, and provide the content explanations of r2, r3, r4 to users for secondary auxiliary detailed explanations, r2, r3, r4 have the same content form as c4, c5, c6, and the content refinement of r2, r3, r4 is greater than that of c4, c5, c6).

[0045] 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 English online education, characterized in that: The following steps are involved: Step S1: Segment the target teaching resource retrieved and viewed by the user into several sub-contents of the questionable knowledge point to obtain a sub-content set. If it is determined that the specific questionable sub-content of the user is at the beginning of the sub-content set, output pre-processing condition 1. Step S2: According to the pre-processing condition 1, auxiliary detailed explanation content is matched from the resource library to obtain auxiliary explanation content 1, and statistics are collected on whether the user continues to watch the remaining content of the target teaching resource. If the user stops watching, the auxiliary explanation content 1 is extended with two additional trigger content forms to obtain extended form content 1 and extended form content 2, so that the user can perform three auxiliary detailed explanations, and the output is switched to auxiliary explanation mode 1; Step S3: If the user continues to watch the sub-content, and the progress of the sub-content being watched accounts for at least half of the total progress of the remaining sub-content, the auxiliary explanation content 1 is further refined and extended to obtain extended and refined content for the user to perform a secondary auxiliary explanation, and the output is switched to the auxiliary explanation mode 2; Step S4: If it is determined that the user's specific question sub-content is not at the beginning of the sub-content set, the question sub-contents in the sub-content set are not adjacent in time sequence, and the proportion of the question sub-contents is not less than the preset determination threshold, then the auxiliary solution mode 1 is implemented; In step S5, if it is determined that the user's specific question sub-content is located at a non-head end of the sub-content set, and the question sub-contents in the sub-content set are adjacent in time sequence, auxiliary detailed explanation content is matched from the resource library to obtain auxiliary explanation content 2, so that the user can provide secondary auxiliary detailed explanation, and a non-entry auxiliary explanation mode is output.

2. A teaching management method based on English online education according to claim 1, characterized in that: Step S1 includes: Obtaining the target teaching resource that the user searches and views, dividing the target teaching resource into several knowledge points to obtain a knowledge point set, and when the user has questions in the process of learning the target teaching resource, marking the questionable knowledge points from the knowledge point set accordingly; According to the questionable knowledge point, marking the entry knowledge points that are located before and adjacent to the questionable knowledge point in time sequence from the knowledge point set; Divide the questionable knowledge point into several sub-contents to obtain a sub-content set; If it is determined that the user's specific question sub-content is located at the beginning of the sub-content set, it is necessary to provide a secondary detailed explanation of the question knowledge point with auxiliary content in combination with the entry knowledge point, and output the pre-processing situation one.

3. A teaching management method based on English online 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 sub-content of the sub-content set is extracted from the entry knowledge point, and the entry sub-content and the first sub-content in the sub-content set are combined into the sub-content to be explained in detail; The correlation and connection degree between the sub-content to be explained in detail and other sub-contents is evaluated to obtain a connection degree of one.

4. A teaching management method based on English online education according to claim 3, characterized in that: Step S2 further includes: Obtaining a resource library, and matching supplementary detailed explanation content from the resource library based on the first degree of cohesion to obtain supplementary explanation content one, wherein the supplementary explanation content one has the same degree of correlation and cohesion with other sub-contents in the sub-content set excluding the header sub-content, and the content format of the supplementary explanation content is the same as the content format of the entry knowledge point; Statistics are collected on whether the user continues to watch the remaining content of the target teaching resource. If the user stops watching, the auxiliary content one is extended with two additional trigger content forms to obtain extended form content one and extended form content two.

5. A teaching management method based on English online education according to claim 4, characterized in that: Step S2 further includes: When the user has watched the auxiliary explanation content 1 for at most two times and continues to watch other sub-contents in the sub-content set excluding the first sub-content, the detailed explanation success result is output; When the user has watched the auxiliary explanation content one for at least three times and still has questions, the invalid result of the first detailed explanation is output. According to the invalid result of the first detailed explanation, the extended form content one is triggered to provide the user with a second auxiliary detailed explanation, and the second detailed explanation result is output. If the second detailed explanation result is still invalid, the extended form content three is triggered to provide the user with a third auxiliary detailed explanation, and the output enters the auxiliary explanation mode one.

6. A teaching management method based on English online education according to claim 5, characterized in that: Step S3 includes: If the user continues to watch, and the progress of the sub-content they continue to watch accounts for at least half of the total progress of the remaining sub-content, the auxiliary explanation content will be refined and extended twice to obtain extended and refined content, and the content format of the extended and refined content is the same as that of the auxiliary explanation content; When the user continues to watch the sub-content set without any questions after watching the auxiliary explanation content 1, the detailed explanation success result is output; When the user continues to watch the sub-content set after watching the auxiliary explanation content one and still has questions, the extended and detailed content is triggered to provide the user with a second auxiliary explanation, and the output enters the auxiliary explanation mode two.

7. A teaching management method based on English online education according to claim 6, characterized in that: Step S4 includes: A percentage determination threshold is preset. 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 not adjacent in time sequence, and the number of question sub-contents is not less than the percentage determination threshold, it is necessary to provide a secondary detailed explanation of the question knowledge point with auxiliary content in combination with the entry knowledge point, and output pre-processing situation three; According to the pre-processing situation three, the auxiliary solution mode one is implemented.

8. The teaching management method based on English online education according to claim 7, characterized in that: Step S5 includes: If it is determined that the user's specific question sub-content is located at a non-head end of the sub-content set, and the question sub-contents in the sub-content set are all adjacent in time sequence, then the second pre-processing condition is output; According to the second pre-processing condition, the correlation and cohesion between the question sub-content and the other sub-content are evaluated to obtain a second cohesion degree; According to the second degree of connection, auxiliary explanation content is matched from the resource library to obtain auxiliary explanation content 2, and the auxiliary explanation content 2 is provided to the user for secondary auxiliary explanation, and a non-entry auxiliary explanation mode is output.

Images