Intelligent auxiliary method and system for nursing teaching training

Abstract

The embodiment of the invention provides an intelligent auxiliary method and system for nursing teaching training, and can solve the problem that a traditional teaching mode is limited by teaching scenes. The method comprises the steps that a page interaction request of a user for a nursing teaching training main page link is acquired, the page interaction request comprises a link address, and the link address is associated with two-dimensional code identification information, so that intelligent terminal equipment under the jurisdiction of the user obtains the link address based on two-dimensional code analysis and sends the link address to the nursing teaching training main page; different types of teaching and training contents of the nursing teaching and training main page are associated with different link addresses; counting the number of browsing requests of the user for different knowledge point sub-pages of the teaching and training content in the nursing teaching and training main page; and according to the browsing request times of different knowledge points in the same nursing teaching and training main page, sorting and displaying different knowledge point entries in the nursing teaching and training main page, so that the entries of the knowledge points with relatively high browsing times are displayed in the front of the nursing teaching and training main page to which the entries belong.

Description

Technical Field

[0001] The present application relates to the field of smart medical technology, and in particular to an intelligent auxiliary method and system for nursing teaching and training. Background Art

[0002] The hospital's nursing training is service-demand oriented. In hospital nursing teaching, it is necessary to select appropriate teaching methods to improve the professional and comprehensive capabilities of clinical nursing and cultivate excellent nursing talents, which will help improve the quality of nursing, ensure patient safety, and promote scientific research development.

[0003] Nowadays, nursing training is usually conducted by teachers, who give lectures or demonstrations, using PPT or operation models to teach nurses. The traditional teaching model is affected by the limitations of teaching scenarios, inconvenient access to teaching materials, and monotonous and boring teaching methods, which ultimately leads to poor training results. At the same time, clinical nurses work many night shifts, have high work pressure, and irregular work and rest schedules, which leads to serious memory loss for nurses. One training session is not enough to achieve good results, but repeated training is boring and deprives nurses of rest time. When nurses encounter doubts at work and need to look through training materials, it is not convenient to obtain information, which also brings certain difficulties to the development of clinical business. Summary of the invention

[0004] The embodiments of the present application provide an intelligent auxiliary method and system for nursing teaching and training, which can solve the problems that the traditional teaching model is limited by the teaching scene, the teaching materials are inconvenient to obtain, and the teaching methods are monotonous and boring.

[0005] A first aspect of an embodiment of the present application provides an intelligent auxiliary method for nursing teaching and training, comprising:

[0006] Obtaining a page interaction request from a user for a link to a nursing teaching and training main page, wherein the page interaction request includes a link address, and the link address is associated with QR code identification information, so that a smart terminal device under the user obtains the link address based on the QR code analysis, and different link addresses are associated with different categories of teaching and training content on the nursing teaching and training main page;

[0007] Count the number of users' browsing requests for different knowledge point sub-pages of teaching and training content in the main page of nursing teaching and training;

[0008] According to the number of browsing requests for different knowledge points in the same nursing teaching and training main page, the different knowledge point entrances in the nursing teaching and training main page are sorted and displayed so that the entrances of the knowledge points with more browsing times are displayed first in the nursing teaching and training main page to which they belong.

[0009] Optionally, it also includes:

[0010] Count the number of requests from different users for the main page of nursing teaching training and / or the knowledge point sub-pages, and periodically send the results of the page request counts of different users to the management terminal associated with the users.

[0011] Optionally, it further includes:

[0012] Count the browsing duration of different users for the main page of nursing teaching training and / or the knowledge point sub-pages, and periodically send the results of the total browsing duration of different users to the management terminal associated with the users.

[0013] Optionally, it further includes:

[0014] Obtain the page interaction requests of the target user for different knowledge point sub-pages within the target main page of nursing teaching training, where the page interaction requests include content marking requests;

[0015] Associate the marked content targeted by the content marking request with the target user;

[0016] When the target user accesses the target main page of nursing teaching training each time, centrally display the marked content already associated with the target user.

[0017] Optionally, it further includes:

[0018] When receiving a browsing request from a user for a target knowledge point sub-page within the main page of nursing teaching training, obtain the expected browsing duration of the user;

[0019] When the expected learning duration of the target knowledge point is greater than the expected browsing duration, refine and compress the content of the target knowledge point to the target learning duration, where the target learning duration is less than or equal to the expected browsing duration;

[0020] Display the refined and compressed content of the target knowledge point on the sub-page so that the user can complete the complete learning of the target knowledge point within the expected browsing duration.

[0021] Optionally, when receiving a browsing request from a user for a target knowledge point sub-page within the main page of nursing teaching training, obtaining the expected browsing duration of the user includes:

[0022] When receiving a browsing request from a user for a target knowledge point sub-page within the main page of nursing teaching training, generate an expected browsing duration question message on the page to obtain the expected browsing duration of the user.

[0023] Optionally, when receiving a browsing request from a user for a target knowledge point sub-page within the main page of nursing teaching training, obtaining the expected browsing duration of the user includes:

[0024] Upon receiving a browsing request of a target knowledge point subpage in the nursing teaching training main page from a user, obtaining the learning interval duration of the user;

[0025] When the learning interval is greater than a preset time, obtaining learned related knowledge points that need to be mastered to learn the target knowledge point;

[0026] When the sum of the estimated learning time of the associated knowledge points and the target knowledge points is greater than the estimated browsing time, the contents of the associated knowledge points and the target knowledge points are refined and compressed to a target learning time, and the target learning time is less than or equal to the estimated browsing time;

[0027] The refined and compressed content of the target knowledge point is displayed on a sub-page so that the user can complete the complete learning of the target knowledge point within the expected browsing time.

[0028] A second aspect of the embodiment of the present application provides an intelligent auxiliary device for nursing teaching and training, comprising:

[0029] An acquisition unit is used to acquire a page interaction request of a user for a link to a nursing teaching and training main page, wherein the page interaction request includes a link address, and the link address is associated with QR code identification information, so that a smart terminal device under the user obtains the link address based on the QR code analysis, and different link addresses are associated with different categories of teaching and training content on the nursing teaching and training main page;

[0030] A statistical unit, used to count the number of browsing requests of users for different knowledge point sub-pages of teaching and training content in the nursing teaching and training main page;

[0031] The display unit is used to sort and display the different knowledge point entries in the nursing teaching and training main page according to the number of browsing requests for different knowledge points in the same nursing teaching and training main page, so that the entries of the knowledge points with more browsing times are displayed first in the nursing teaching and training main page to which they belong.

[0032] A third aspect of an embodiment of the present application provides an electronic system, including a memory and a processor, wherein the processor is used to implement the steps of the above-mentioned intelligent assistance method for nursing teaching and training when executing a computer program stored in the memory.

[0033] A fourth aspect of an embodiment of the present application provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned intelligent assistance method for nursing teaching and training are implemented.

[0034] In summary, the intelligent auxiliary method for nursing teaching training provided by the embodiments of the present application obtains a page interaction request of the user for the link of the nursing teaching training main page. The page interaction request includes a link address, and the link address is associated with two-dimensional code identification information, so that the intelligent terminal device under the user can obtain the link address based on the parsing of the two-dimensional code. Different types of teaching and training contents of the nursing teaching training main page are associated with different link addresses; count the number of browsing requests of the user for different knowledge point sub-pages of the teaching and training contents in the nursing teaching training main page; sort and display different knowledge point entrances in the nursing teaching training main page according to the number of browsing requests of different knowledge points in the same nursing teaching training main page, so that the entrances of the knowledge points with more browsing times are displayed earlier in the nursing teaching training main page to which they belong. Thus, based on the browsing request statistics, the system can dynamically adjust the content according to the actual needs of nurses, making the training more personalized and targeted. By scanning the two-dimensional code, nurses can quickly enter the corresponding training module without wasting time searching for information. The sorting and display function enables nurses to give priority to accessing popular or key knowledge points, improving learning efficiency. Traditional training may cause nurses to be unable to concentrate on learning under high work pressure, while this method can make the learning content more dispersed and flexible, facilitating nurses to learn anytime and anywhere and reducing work pressure. The statistical browsing data provides the hospital with an intuitive understanding of nurses' learning preferences and needs, so that the teaching content and methods can be adjusted accordingly. For example, when a certain type of knowledge point is frequently browsed, more relevant content can be provided for nurses to ensure that the training content is always linked to the actual needs.

[0035] Correspondingly, the intelligent auxiliary device, electronic system, and computer-readable storage medium for nursing teaching training provided by the embodiments of the present invention also have the above technical effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic flowchart of a possible intelligent auxiliary method for nursing teaching training provided by the embodiments of the present application;

[0037] Figure 2 It is a schematic structural block diagram of a possible intelligent auxiliary device for nursing teaching training provided by the embodiments of the present application;

[0038] Figure 3 It is a schematic hardware structure diagram of a possible intelligent auxiliary device for nursing teaching training provided by the embodiments of the present application;

[0039] Figure 4 It is a schematic structural block diagram of a possible electronic system provided by the embodiments of the present application;

[0040] Figure 5Schematic structural block diagram of a possible computer-readable storage medium provided by an embodiment of the present application. Detailed implementation manners

[0041] An embodiment of the present application provides a smart assistance method and system for nursing teaching training, which can solve the problems that the traditional teaching mode is limited by the teaching scenario, the acquisition of teaching materials is not convenient, and the teaching method is single and boring.

[0042] The terms "first", "second", "third", "fourth", etc. (if any) in the description and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices. Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments.

[0043] Please refer to Figure 1 , which is a flowchart of a smart assistance method for nursing teaching training provided by an embodiment of the present application, and specifically may include: S110-S130.

[0044] S110, obtaining a page interaction request of a user for a link to a nursing teaching training main page, where the page interaction request includes a link address, and the link address is associated with two-dimensional code identification information, so that the smart terminal device under the user can obtain the link address based on the parsing of the two-dimensional code, and different types of teaching training contents of the nursing teaching training main page are associated with different link addresses.

[0045] It is understandable that when nurses need training, they can scan a QR code through a smart terminal (such as a mobile phone or tablet) to enter the main page of nursing teaching and training. The QR code carries a specific link address, and this link address corresponds to different categories of nursing teaching content. In the traditional training mode, nurses may need to manually enter the website or flip through paper materials to find teaching content. The application of the QR code solves this problem. Just by scanning, they can directly jump to the specified teaching page, improving convenience. Different link addresses represent different training categories (such as drug nursing, postoperative nursing, first aid nursing, etc.), which allows nurses to quickly select relevant training content according to their current work needs or doubts.

[0046] Exemplarily, place a QR code beside each nursing training scenario, office scenario, or teaching material. Nurses use a smart terminal device to scan the QR code, and the smart device obtains the link address by parsing the QR code. The device automatically jumps to the corresponding nursing teaching main page and selects the corresponding learning module according to the category. For example, when a nurse is participating in postoperative nursing training, the system provides a QR code related to postoperative nursing. After the nurse scans it, the system automatically loads the content related to postoperative nursing without any manual operation.

[0047] S120, count the number of browsing requests of the user for different knowledge point sub - pages of the teaching training content within the nursing teaching training main page.

[0048] It is understandable that when nurses browse nursing teaching content, the system will automatically record the browsing times of each sub - page. The browsing times, as an important indicator of user interest, can reflect the degree of attention of nurses to a certain knowledge point. By counting the browsing data, the system can understand which knowledge points are most concerned and have the most practical application needs. Whenever a nurse clicks on a knowledge point sub - page, the system will generate a browsing request record. These browsing requests will be counted in the background to form the basis for data analysis. The browsing times can be used as a basis for measuring whether the teaching content meets the actual needs. If the browsing times of a certain knowledge point are particularly high, it means that this knowledge point may be the content that current nursing staff generally pay attention to or need.

[0049] Exemplarily, set a unique identifier for each teaching knowledge point and monitor the clicks of nurses on each sub - page. Each time a user clicks on a knowledge point page, the background system will record the browsing times of this page. The system will statistically analyze these browsing data in dimensions such as time and frequency to generate a data report. For example, when a nurse browses the content related to "respiratory tract nursing" and clicks on multiple specific nursing measure pages. The system will record the click times of each page. The background data may show that the click times of the page "prevention of complications in respiratory tract nursing" are high, indicating that nurses have a stronger learning need for this part of the content.

[0050] S130. Sort and display the entry points of different knowledge points on the main page of the nursing teaching training according to the number of browsing requests for different knowledge points within the same main page of the nursing teaching training, so that the entry points of the knowledge points with more browsing times are displayed earlier in the corresponding main page of the nursing teaching training.

[0051] It can be understood that by counting the number of browsing requests for each knowledge point, the system can sort these contents according to the browsing times, and the knowledge points with higher frequencies will be preferentially displayed on the page. This method can help nurses preferentially learn the nursing knowledge points that are most needed to master or are currently the most popular. The knowledge points with high browsing frequencies will be preferentially displayed to ensure that nurses can access the most common or important nursing knowledge at the first time. This method makes the learning content more personalized and dynamic. Different nurses have different training needs. According to the content and frequency they browse, the system will recommend knowledge points related to their learning interests and work fields.

[0052] Exemplarily, a dynamic sorting mechanism can be designed on the main page of the nursing teaching. The knowledge points with more browsing times will be automatically ranked in the front. When a nurse enters the page, the system adjusts the display order according to the click volume of each knowledge point to ensure that the key content is presented first. If the system detects that some knowledge points have not been browsed for a long time, it may adjust the display positions of these contents according to actual needs. For example, if most nurses frequently browse the knowledge points related to "first aid skills", the system will rank these knowledge points at the top of the page to ensure that other nurses can also preferentially learn these popular contents. If a certain content (such as "skills of injecting drugs") is not concerned for a long time, the system will move it to the bottom of the page or even make customized recommendations according to the work fields of the nurses.

[0053] Exemplarily, allow users or administrators to adjust the classification of the training content according to different teaching requirements, learning objectives or knowledge structures. This can not only help customize the learning content for specific needs, but also improve the flexibility of teaching management. Users can create new categories or modify existing categories according to needs. For example, nurses can choose different categories such as "basic nursing", "emergency nursing" or "operative nursing" for learning, or customize the course categories according to the department's needs. The system will allow users to classify the course content and provide the permissions to add, delete or adjust categories. This can make it easier for nurses to find the content they need to learn and provide a personalized learning path.

[0054] In summary, the intelligent auxiliary method for nursing teaching and training provided in the above embodiment obtains the page interaction request of the user for the nursing teaching and training main page link, and the page interaction request includes a link address, and the link address is associated with a QR code identification information, so that the intelligent terminal device under the user obtains the link address based on the QR code analysis, and the teaching and training content of different categories of the nursing teaching and training main page associated with different link addresses; the number of browsing requests of users for different knowledge point sub-pages of teaching and training content in the nursing teaching and training main page is counted; according to the number of browsing requests for different knowledge points in the same nursing teaching and training main page, the different knowledge point entrances in the nursing teaching and training main page are sorted and displayed, so that the entrances of the knowledge points with more browsing times are displayed in front of the nursing teaching and training main page. Thus, based on the browsing request statistics, the system can dynamically adjust the content according to the actual needs of the nurses, so that the training is more personalized and targeted. By scanning the QR code, the nurse can quickly enter the corresponding training module without wasting time looking for information. The sorting and display function enables nurses to have priority access to popular or key knowledge points and improve learning efficiency. Traditional training may cause nurses to lose focus on learning under high work pressure, but this method can make the learning content more decentralized and flexible, allowing nurses to learn anytime and anywhere, reducing work pressure. The statistical browsing data provides the hospital with an intuitive understanding of nurses' learning preferences and needs, so that the teaching content and methods can be adjusted in a targeted manner. For example, when a certain type of knowledge point is frequently browsed, more relevant content can be provided to nurses to ensure that the training content is always linked to actual needs.

[0055] In one embodiment, it also includes:

[0056] The number of requests for the nursing teaching and training main page and / or the knowledge point sub-page by different users is counted, and the page request number results of different users are periodically sent to the management terminal associated with the users.

[0057] It is understandable that in addition to counting the frequency of user browsing, the number of page requests for each user can also be tracked. By recording the number of access requests from different users to the main page of nursing teaching training or the sub-page of specific knowledge points, the system can evaluate each user's learning activity, learning interest, and the popularity of the training content. The system not only records the browsed pages, but also the frequency of user requests, such as the number of times a user clicks on a certain page and the number of times a user enters a certain module. This can help the management side understand the frequency of user participation in training and identify active users and less involved users. The management side will regularly receive statistical results of the number of requests from different users. Based on these data, the management side can better understand the progress of training, adjust the training content or training plan in a timely manner, and even intervene.

[0058] Exemplarily, the system records the user's requests each time the user accesses a certain page. Each page request increments the corresponding count. The system sets up scheduled tasks (such as weekly, monthly, etc.) to periodically summarize the request count results of each user and send them to the management terminal. Based on the received request count statistics, the management terminal analyzes which users are actively participating and which users may have a relatively low training participation rate. For example, user A accesses the "Heart Disease Care" page 5 times a week, while user B only accesses it once. The system sends the request counts of these two users to the management terminal to help the training manager identify which users may need more support or intervention. The management terminal finds that user A frequently accesses a specific page, which may indicate that the user is particularly interested in heart disease care or is encountering difficulties in related operations and needs more practice or help.

[0059] In one embodiment, it further includes:

[0060] Statistical analysis of the browsing durations of different users for the main page of the nursing teaching training and / or the sub-pages of knowledge points, and periodically sending the total browsing duration results of different users to the management terminal associated with the user.

[0061] It can be understood that the browsing duration statistics help the system evaluate the depth of user learning. Simple request counts cannot reflect the degree of user investment in learning the content, while the browsing duration can better measure the focus of each user on each knowledge point. The system records the residence time of each user on each page or module. The browsing duration can be used as an indicator of the degree of user investment in learning, especially important when judging whether a user truly understands and masters a certain knowledge point. Similar to the request count statistics, the browsing duration is also periodically summarized and sent to the management terminal. This helps the management terminal understand the learning investment of each user and provides data support for subsequent training arrangements.

[0062] Exemplarily, the system starts a timer when the user accesses a page and stops timing when the user leaves the page or module. The browsing duration of each page is recorded and periodically summarized. The system periodically summarizes the total browsing duration of each user and sends this data to the management terminal at regular intervals. Based on the browsing duration data, the management terminal can understand which users have invested more time in the content and which users may have slower learning progress, and adjust the training content or provide more learning support if necessary. For example, user C stays on the "Surgical Nursing Skills" page for 40 minutes, while user D only stays for 10 minutes. The system separately calculates the browsing durations of these two users on this page and sends the data to the management terminal. Through the browsing duration statistics, the management terminal finds that user C may have a high learning investment but may also have difficulty understanding this knowledge point and may need further tutoring; while user D may have little interest in learning this knowledge point or low learning efficiency and may require an adjustment in the teaching strategy.

[0063] It is understandable that the statistics of the number of requests and the browsing duration provide comprehensive user participation data. The number of requests reflects the learning frequency, while the browsing duration reflects the learning depth. The combination of the two can effectively evaluate the learning status and training effect of each nurse. By periodically receiving reports on the number of requests and the browsing duration, the management side can implement more precise personalized training strategies. If some users frequently access a certain knowledge point but have a short browsing duration, it may mean that they need further learning support or tutoring; if a user has few accesses, consideration can be given to reminding or motivating the user to participate in more training. Through the comprehensive analysis of the browsing duration and the number of requests, the management side can more clearly understand the learning progress, participation status, and learning difficulties of each nurse. Such data support makes training management more efficient and enables quick decision-making, such as adjusting course content, adding tutoring, etc. Regularly obtained statistics on the number of requests and the browsing duration can help training managers discover potential problems. For nurses with low participation, the management side can timely remind or push additional learning resources through reminders or pushes to ensure that each nurse can keep up with the training progress and master key skills.

[0064] Exemplarily, the system automatically generates a learning leaderboard based on the learning situation of users within a certain period to stimulate the learning enthusiasm of nurses. The leaderboard can be generated according to different learning performances, such as learning duration, number of completed courses, learning frequency, etc. In combination with the leaderboard, the system can provide rewards for outstanding nurses. This not only helps to stimulate the learning enthusiasm of nurses but also promotes the depth and breadth of knowledge mastery.

[0065] In one embodiment, it further includes:

[0066] Obtain the page interaction requests of the target user for different knowledge point sub-pages within the target nursing teaching training main page, where the page interaction requests include content marking requests;

[0067] Associate the marked content targeted by the content marking request with the target user;

[0068] In the case where the target user accesses the target nursing teaching training main page each time, centrally display the marked content already associated with the target user.

[0069] It is understandable that during the traditional nursing training process, nurses may need to repeatedly search for important information in training materials. The content marking request allows users to mark the parts they are concerned about or need to review intensively. In this way, nurses can quickly jump to the content they marked during subsequent learning. When users are browsing the nursing teaching page, they can mark a certain knowledge point or page as key content by clicking or other interaction methods. For example, if a user is particularly concerned about the page "Trauma Nursing Skills", they can mark this page, and can quickly find this page every time they browse later. The page interaction request not only includes ordinary click requests, but also the behavior of users actively marking. Users can choose to "mark" a certain page or knowledge point for subsequent review.

[0070] Exemplarily, next to each page or knowledge point, the system provides a "mark" button or interaction item. After the user clicks to mark, the system will add this page or knowledge point to the user's "mark list". Whenever a user makes a mark, the system records the content of the mark and associates it with the target user. The marking request is not just an action, the system stores it as a data point, and users can access the marked content later. For example, when a nurse is learning the page "Drug Allergy Reaction Management" and finds that a certain description about drug allergy symptoms is particularly important, she clicks the "mark" button on the page, and the system will associate this content with the nurse's account. Thereafter, when the nurse enters the training page, the system will display the content she marked before at an appropriate position to ensure that she can conveniently review and master this part of knowledge.

[0071] It is understandable that by associating the marked content with a specific user, the system can provide personalized learning materials for each user. The marked content of each user becomes a part of their personal learning process. The system can track and record their learning needs to enhance the subsequent learning experience. Every time a user marks a knowledge point, the system binds the mark information to the user's account. In this way, the marked content of each user is independent and highly targeted, and can reflect their learning interests and the parts that need in-depth study. These marked data can provide profound insights into the learning needs of each user for the system, so as to optimize the push and display of learning resources.

[0072] Exemplarily, when the user marks content, the system stores the marking data in the user's personal learning profile. When the user logs in, the system displays the marked content according to their personal profile, facilitating the user to view and review. For example, user A marks the video content of "intravenous infusion operation". The system associates this marked content with user A's account. When user A accesses the relevant module in the future, the system automatically displays the marked content. If user A marks multiple different knowledge points during multiple visits, the system records all these marks to form the user's personalized learning path.

[0073] It can be understood that every time the target user logs in and accesses the nursing teaching page, the system displays this content in a prominent position on the page according to their historical marked content, so that the user can access the previously marked key content more quickly and conveniently. This method can reduce the time for the user to search for the marked content and improve learning efficiency. Every time the user accesses the target page, the system automatically displays the content marked by the user on the page to ensure that the user can quickly review, revise or continue to learn this content. The system can recommend similar learning content based on the user's marking history to further assist the user in expanding or reviewing knowledge points.

[0074] Exemplarily, centralized display of marked content: Each time a user logs in, the system scans their historical marks and displays the marked content at the top or prominent position of the target page. The display form can be a list, summary, link, etc. The system can set different display priorities for different users. For example, if certain content has a higher marking frequency or stronger importance, the system can display this marked content in a more prominent position. For example, User B marked a part of "aseptic technique" on the "basic nursing techniques" page. Each time User B enters this page, the system will display the content related to "aseptic technique" she marked at the top of the page and provide a link for the user to click and jump directly. If User C marked multiple articles or video content, the system can integrate these contents into a "my learning path" module and provide a reminder or display when the user logs in each time, facilitating subsequent quick access. Thus, the way of content marking and centralized display enables users to independently select the learning focus according to their own interests and needs, improving learning efficiency and experience. This personalized learning mode also helps to improve the participation and quality of training. Each time a user accesses the training main page, the system will provide a centralized display based on the content they have marked. This ensures that nurses can review and revise the knowledge points they care about in a short time, avoiding the trouble of having to search for materials again. The association and display of marked content not only help nurses with self-study but also provide feedback on users' learning situations to training managers. The management side can analyze which knowledge points are more likely to become learning bottlenecks for nurses by viewing the content marked by users and provide targeted further guidance or resources accordingly. The marking system allows nurses to "store" the content they think is important and avoid having to search for training materials again each time. As the learning process progresses, the marked content will help nurses build their own knowledge bases and reduce learning anxiety. Content marking is not just a one-time learning process; users can update and modify their marked content over time. In this way, nurses' learning paths and knowledge systems will be gradually improved with continuous training, supporting continuous learning and knowledge update.

[0075] According to some embodiments, it further includes:

[0076] When receiving a browsing request from a user for a target knowledge point sub-page within the nursing teaching training main page, obtain the expected browsing duration of the user;

[0077] When the expected learning duration of the target knowledge point is greater than the expected browsing duration, refine and compress the content of the target knowledge point to a target learning duration, where the target learning duration is less than or equal to the expected browsing duration;

[0078] Display the refined and compressed content of the target knowledge point on the sub-page so that the user can complete the complete learning of the target knowledge point within the expected browsing duration.

[0079] It is understandable that since nurses usually look for fragmented time at work to scan the code and study, there often appears a situation where only a part of the knowledge points are mastered during a short study time. Moreover, because it is only partial knowledge points, it is not easy to form memory points and may even easily cause incorrect understanding of the knowledge points. Also, it is not conducive to the connection and understanding of the subsequent content of the knowledge points when studying again next time. The refined and compressed knowledge points in the above solution may lack some specific branches of the knowledge points, but the refined and compressed content will ensure that it is a complete knowledge point with a memory point, or in other words, it can include a complete knowledge link for understanding a certain problem. In order to avoid the understanding break or misunderstanding easily caused by users using fragmented learning time to study knowledge points, and to ensure that users can master a complete knowledge point with a memory point in a short time.

[0080] Exemplarily, when the user opens a certain target knowledge point sub-page, the system asks the user how much time is expected to be spent learning the content of this page through a pop-up window or a message box, etc. Through the user's feedback, the system can understand the user's time arrangement, so as to prepare for subsequent content optimization. When the page is loaded, the system will pop up a question message asking the user about the expected learning duration, so as to collect data and prepare for adjusting the learning content. The expected time input by the user helps the system evaluate whether it is necessary to compress or adjust the page content to meet the needs of short-time learning.

[0081] Exemplarily, when the user clicks to enter the target knowledge point sub-page, the system will automatically generate a question message box asking the user about the expected time to browse and learn the content of this page. The user selects or inputs the expected learning duration according to their actual situation, and the system will record this information and use it for subsequent operations. For example, when user A enters the "Preoperative Nursing Preparation" page, the system pops up a prompt box: "How much time do you expect to take to complete the study?" User A selects "6 minutes" according to their possible free time, and the system records this time and prepares for subsequent processing.

[0082] It is understandable that if the system judges that the expected learning duration of the target knowledge point is longer than the user's expected browsing duration, the system will, on the premise of ensuring the learning effect, refine and compress the content. This compression will ensure that the refined content retains a complete knowledge link and can help users establish effective memory points and understanding in a short time. During the content compression process, the system will not simply delete content, but compress a refined version that can ensure a complete knowledge link according to the relevance of the core knowledge points. Even if the time is short, users can establish a complete framework of the knowledge points through the refined content, avoiding learning breaks or incorrect understanding. The system will pay special attention to the logic of the content to ensure that the front-back relationship and causal chain of each knowledge point can be reasonably displayed.

[0083] Exemplarily, the system refines the page content, identifies the most core concepts and key steps through algorithms, removes redundant information, and ensures that users can still understand the overall structure of the knowledge within a relatively short time. The system presents the compressed content in a concise but complete manner, possibly in the form of a combination of text and graphics. For example, the "Basic Life Support" page originally required 10 minutes to study. The system detected that the user's estimated study duration was 6 minutes, so it refined the page content into a short list of steps, briefly explained each step, and used schematic diagrams to strengthen the understanding of each step, while maintaining the order and logical sequence of the content.

[0084] It can be understood that in order to enable users to complete a complete study within a limited time, the system will display the refined and compressed content to ensure the compactness and logical coherence of the content. By ensuring the integrity of the content, it avoids misunderstandings or memory loss caused by fragmented learning. The system presents the compressed content as a highly coherent and easy-to-understand knowledge structure to help users form a clear knowledge framework in a relatively short time and avoid disconnection between knowledge points. Users will be able to effectively understand and remember the complete knowledge points in a short time, while laying a good foundation for the next study and avoiding incorrect understanding and discontinuous memory of knowledge points.

[0085] Exemplarily, when presenting the compressed content, the system will clearly present the core knowledge points through concise text, charts, flowcharts, or short videos, etc., while strengthening the understanding of each step to ensure its integrity and logic. The system adds elements such as countdown timers and progress bars to the page to remind users of the remaining learning time and provide real-time feedback on the learning progress to help users complete the learning tasks on time. For example, when user B studies the "Respiratory Management" page, the estimated browsing duration is 4 minutes. The system refines the content of this page into 4 key points and presents it in a combination of text and graphics. The progress bar shows the remaining learning time to help users master the content in a timely manner and ensure that they learn the entire knowledge point within 4 minutes. Thus, even if the content is compressed, it can ensure that users have a complete understanding and memory of the knowledge points and avoid misunderstandings caused by fragmented learning. Within a short learning time, users can quickly master the key knowledge, reducing time waste. Users can form a clear knowledge framework through the refined content and lay a solid foundation for subsequent learning.

[0086] According to some embodiments, when receiving a browsing request from a user for a target knowledge point sub-page within the nursing teaching training main page, obtaining the estimated browsing duration of the user includes:

[0087] When receiving a browsing request from a user for a target knowledge point sub-page within the nursing teaching training main page, obtaining the learning interval duration of the user;

[0088] When the learning interval is greater than the preset duration, obtain the learned associated knowledge point subsets required to master the target knowledge point;

[0089] When the sum of the estimated learning durations of the associated knowledge point subsets and the target knowledge point is greater than the estimated browsing duration, refine and compress the content of the associated knowledge point subsets and the target knowledge point to the target learning duration, where the target learning duration is less than or equal to the estimated browsing duration;

[0090] Display the refined and compressed content of the target knowledge point on a sub-page so that the user can complete the complete learning of the target knowledge point within the estimated browsing duration.

[0091] It can be understood that when a user requests to access a sub-page of a target knowledge point, the system will ask the user how much time they expect to spend learning the content of this page. This information will be used for subsequent content refinement and compression work to ensure that users can complete their learning within the time they specify. The user inputs or selects the estimated learning duration, which can be done through a pop-up box or page interaction. The system will record this time and make corresponding content adjustments.

[0092] It can be understood that the system will judge whether it is necessary to consider the already learned associated knowledge points according to the user's learning interval (that is, the time interval from the user's last learning of knowledge in this field to the current learning). A longer learning interval may mean that the user has forgotten some knowledge, and the system needs to review the learned knowledge for the user to enhance the learning effect. The system calculates the time difference from the last learning of knowledge in this field to the current time and judges whether it exceeds the preset duration. If the learning interval is long, the system will identify the learned content related to the target knowledge point and regard this content as associated knowledge points for the user to review and consolidate.

[0093] Exemplarily, the system calculates the time interval from the last learning time to the current access time according to the user's historical learning records. If the interval exceeds the preset duration, the system will extract the learned content (associated knowledge points) related to the target knowledge point from the user's historical learning records. For example, user B last learned "pathological nursing" three months ago. The system judges that this period is too long, so it extracts the basic knowledge points related to "pathological nursing" (such as "nursing of common diseases") to help the user review.

[0094] It is understandable that if the sum of the estimated learning durations of the associated knowledge point and the target knowledge point is greater than the user's estimated browsing duration, the system will compress the content of these two parts to ensure that the overall learning duration of both does not exceed the time set by the user. The system refines the content of the associated knowledge point and the target knowledge point according to the user's estimated browsing duration, removes unnecessary details, and retains the core knowledge points and key steps to ensure learning can be completed within the limited time of the user. The compression process needs to ensure that the core concepts and logical chains of each knowledge point are retained to avoid knowledge gaps or misunderstandings.

[0095] Exemplarily, the system adds the estimated learning durations of the target knowledge point and its associated knowledge point to determine whether it exceeds the user's estimated browsing duration. If it exceeds the estimated duration, the system will refine and compress the content according to importance and relevance to ensure that key knowledge is not lost. For example, User C is learning the "Nursing Technical Points" page with an estimated learning duration of 8 minutes. The system extracts 3 basic knowledge points related to this knowledge point and calculates the overall duration to be 12 minutes. To meet the user's 8-minute learning time, the system compresses the 12-minute content into 5 key points and presents them to the user in a concise graphic form.

[0096] It is understandable that after the content compression and refinement are completed, the system will display the organized knowledge points to the user. The user will be able to complete the learning of this knowledge point within the estimated learning duration, ensuring the integrity and coherence of the learning content. The refined and compressed content is presented in graphic, video, or other concise and effective forms, enabling the user to complete efficient learning within limited time. Even if the content is compressed, the system ensures that the user can master the core knowledge points and understand the knowledge link to avoid information gaps.

[0097] Exemplarily, the system will display the refined knowledge point content in a concise and clear form, avoiding overly long descriptions and details to ensure learning efficiency. The system adds a progress bar or countdown function to the page to prompt the user to complete the target knowledge point within the learning duration. For example, User D is learning "Blood Glucose Monitoring and Management" with an estimated learning duration of 10 minutes. The system refines the content according to the associated knowledge points and presents the key points in a concise graphic form, while providing a progress bar to help the user control the learning time and ensure completion within 10 minutes. Thus, by compressing and refining the content, it is ensured that the user can complete efficient learning in a short time. Even if the learning time is limited, the system still ensures that the user can master the core knowledge and understand the relevant knowledge chain. According to the user's learning habits, time arrangements, and existing learning progress, the system provides customized learning content to improve the learning effect.

[0098] Please refer to Figure 2, an embodiment of the intelligent auxiliary device for nursing teaching and training in the embodiment of the present application may include:

[0099] The acquisition unit 201 is used to acquire a page interaction request of a user for a link to a nursing teaching and training main page, wherein the page interaction request includes a link address, and the link address is associated with QR code identification information, so that a smart terminal device under the user obtains the link address based on the QR code parsing, and different link addresses are associated with different categories of teaching and training content on the nursing teaching and training main page;

[0100] A statistics unit 202 is used to count the number of browsing requests of users for different knowledge point sub-pages of the teaching and training content in the nursing teaching and training main page;

[0101] The display unit 203 is used to sort and display the different knowledge point entries in the nursing teaching and training main page according to the number of browsing requests for different knowledge points in the same nursing teaching and training main page, so that the entries of the knowledge points with more browsing times are displayed first in the nursing teaching and training main page to which they belong.

[0102] In summary, the intelligent auxiliary device for nursing teaching and training provided in the above embodiment obtains the page interaction request of the user for the nursing teaching and training main page link, and the page interaction request includes a link address, and the link address is associated with a QR code identification information, so that the intelligent terminal device under the user obtains the link address based on the QR code analysis, and the teaching and training content of different categories of the nursing teaching and training main page associated with different link addresses; the number of browsing requests of users for different knowledge point sub-pages of teaching and training content in the nursing teaching and training main page is counted; according to the number of browsing requests for different knowledge points in the same nursing teaching and training main page, the different knowledge point entrances in the nursing teaching and training main page are sorted and displayed, so that the entrances of the knowledge points with more browsing times are displayed in front of the nursing teaching and training main page. Thus, based on the browsing request statistics, the system can dynamically adjust the content according to the actual needs of the nurses, so that the training is more personalized and targeted. By scanning the QR code, the nurse can quickly enter the corresponding training module without wasting time looking for information. The sorting and display function enables nurses to have priority access to popular or key knowledge points and improve learning efficiency. Traditional training may cause nurses to lose focus on learning under high work pressure, but this method can make the learning content more decentralized and flexible, allowing nurses to learn anytime and anywhere, reducing work pressure. The statistical browsing data provides the hospital with an intuitive understanding of nurses' learning preferences and needs, so that the teaching content and methods can be adjusted in a targeted manner. For example, when a certain type of knowledge point is frequently browsed, more relevant content can be provided to nurses to ensure that the training content is always linked to actual needs.

[0103] Exemplarily, the search function can allow nurses to quickly find relevant teaching content, operation procedures, or standard specifications in the system by keywords (such as "oral care", "trauma care"). Compared with the resources publicly available on the Internet, the content in the system is more in line with the actual situation of the hospital and is more operable, avoiding inaccurate or inapplicable network information. Obvious search boxes can be set on the main page of the system, each training module, and each sub-page to facilitate users to input keywords for searching at any time. The system can provide a list of relevant content according to the keywords input by the user and sort them according to relevance, importance, and update date. The search results can be divided into different categories, such as "operation manuals", "training videos", "case analyses", etc., to help nurses quickly find the learning materials they need. For example, after user A inputs "oral care", the system returns relevant content such as "Oral Care Operation Standards", "Oral Care Video Tutorial", "Key Points for the Care of Common Oral Diseases", etc.

[0104] Exemplarily, to improve the search experience, the system should not only return relevant content but also ensure the practicality and operability of this content. This means that the search results should have a higher degree of matching, be in line with the actual situation of the hospital, and avoid irrelevant or outdated information. In the search results, the original content of this hospital or the content with more frequent updates will be ranked first to ensure the practicality and timeliness of the content. In addition to keywords, filtering can also be performed according to categories (such as nursing fields, ward categories, etc.), training levels, operation types, etc. to further narrow the search scope and improve accuracy. The system will mark the update time of each search result to ensure that users obtain the latest training materials. For example, when user B searches for "diabetes care", the system first displays the latest diabetes care plan within the hospital, and then displays training videos, case analyses, etc. related to diabetes care, and all content is clearly marked with the update time beside it.

[0105] Above Figure 2 The intelligent auxiliary device for nursing teaching and training in the embodiments of the present application has been described from the perspective of modular functional entities. Next, the intelligent auxiliary device for nursing teaching and training in the embodiments of the present application will be described in detail from the perspective of hardware processing. Please refer to Figure 3 , an embodiment of the intelligent auxiliary device 300 for nursing teaching and training in the embodiments of the present application includes:

[0106] An input device 301, an output device 302, a processor 303, and a memory 304, where the number of processors 303 can be one or more, Figure 3 Taking one processor 303 as an example. In some embodiments of the present application, the input device 301, the output device 302, the processor 303, and the memory 304 can be connected through a bus or other means, where, Figure 3 Taking connection through a bus as an example.

[0107] Among them, the processor 303 is configured to execute the steps of the intelligent auxiliary method for nursing teaching training in the above-mentioned embodiments by calling the operation instructions stored in the memory 304.

[0108] By calling the operation instructions stored in the memory 304, the processor 303 is further configured to execute Figure 1 any one of the corresponding embodiments.

[0109] Please refer to Figure 4 , Figure 4 , which is a schematic diagram of an embodiment of the electronic system provided by the embodiment of the present application.

[0110] As Figure 4 shown, the embodiment of the present application provides an electronic system, including a memory 410, a processor 420, and a computer program 411 stored on the memory 420 and executable on the processor 420. When the processor 420 executes the computer program 411, the steps of the intelligent auxiliary method for nursing teaching training in the above-mentioned embodiments are implemented.

[0111] In the specific implementation process, when the processor 420 executes the computer program 411, it can implement Figure 1 any one of the corresponding embodiments.

[0112] Since the electronic system introduced in this embodiment is the device used to implement an intelligent auxiliary device for nursing teaching training in the embodiment of the present application, based on the method introduced in the embodiment of the present application, those skilled in the art can understand the specific implementation manners and various variations of the electronic system in this embodiment. Therefore, the specific implementation of how this electronic system implements the method in the embodiment of the present application will not be described in detail here. As long as the device used by those skilled in the art to implement the method in the embodiment of the present application belongs to the scope protected by the present application.

[0113] Please refer to Figure 5 , Figure 5 , which is a schematic diagram of an embodiment of a computer-readable storage medium provided by the embodiment of the present application.

[0114] As Figure 5 shown, this embodiment provides a computer-readable storage medium 500, on which a computer program 511 is stored. When the computer program 511 is executed by a processor, the steps of the intelligent auxiliary method for nursing teaching training in the above-mentioned embodiments are implemented.

[0115] In the specific implementation process, when the computer program 511 is executed by a processor, it can implement Figure 1 any one of the corresponding embodiments.

[0116] It should be noted that in the above embodiments, the descriptions of the respective embodiments have their own emphases. For parts not described in detail in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0117] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0118] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the processes and / or blocks in the flowchart and / or block diagram can also be implemented. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the specified functions in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0119] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means implements the specified functions in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0120] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the specified functions in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0121] The embodiments of the present application also provide a computer program product, which includes computer software instructions. When the computer software instructions run on a processing device, the processing device is caused to execute as Figure 1The process in the intelligent auxiliary method for nursing teaching training in the corresponding embodiment.

[0122] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are wholly or partially generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired manner (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or a wireless manner (such as infrared, wireless, microwave, etc.). The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that includes one or more integrated available media. The available medium may be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (SSD)).

[0123] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above may refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0124] In several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections between each other may be indirect couplings or communication connections through some interfaces, devices, or units, and may be in electrical, mechanical, or other forms.

[0125] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0126] In addition, in each embodiment of the present application, each functional unit can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0127] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0128] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of each embodiment of the present application.

Claims

1. An intelligent auxiliary method for nursing teaching and training, characterized in that: include: Obtaining a page interaction request from a user for a link to a nursing teaching and training main page, wherein the page interaction request includes a link address, and the link address is associated with QR code identification information, so that a smart terminal device under the user obtains the link address based on the QR code analysis, and different link addresses are associated with different categories of teaching and training content on the nursing teaching and training main page; Count the number of users' browsing requests for different knowledge point sub-pages of teaching and training content in the main page of nursing teaching and training; According to the number of browsing requests for different knowledge points in the same nursing teaching and training main page, the different knowledge point entrances in the nursing teaching and training main page are sorted and displayed so that the entrances of the knowledge points with more browsing times are displayed first in the nursing teaching and training main page to which they belong.

2. The method according to claim 1, characterized in that Also includes: The number of requests for the nursing teaching and training main page and / or the knowledge point sub-page by different users is counted, and the page request number results of different users are periodically sent to the management terminal associated with the users.

3. The method according to claim 1, characterized in that Also includes: The browsing time of different users on the nursing teaching and training main page and / or knowledge point sub-page is counted, and the total browsing time results of different users are periodically sent to the management terminal associated with the users.

4. The method according to claim 1, characterized in that: Also includes: Obtaining a target user's page interaction request for different knowledge point sub-pages within a target nursing teaching and training main page, wherein the page interaction request includes a content tagging request; Associating the marked content targeted by the content marking request with the target user; Each time the target user visits the target nursing teaching and training main page, the tagged contents associated with the target user are displayed collectively.

5. The method according to claim 1, characterized in that Also includes: Upon receiving a browsing request from a user for a target knowledge point subpage in the nursing teaching and training main page, obtaining an estimated browsing time of the user; When the estimated learning time of the target knowledge point is longer than the estimated browsing time, the content of the target knowledge point is refined and compressed to the target learning time, and the target learning time is less than or equal to the estimated browsing time; The refined and compressed content of the target knowledge point is displayed on a sub-page so that the user can complete the complete learning of the target knowledge point within the expected browsing time.

6. The method according to claim 5, characterized in that When receiving a browsing request of a target knowledge point subpage in the nursing teaching training main page from a user, obtaining an estimated browsing time of the user includes: When receiving a browsing request of a target knowledge point sub-page in the nursing teaching and training main page from a user, an estimated browsing time question message is generated in the page to obtain the estimated browsing time of the user.

7. The method according to claim 5, characterized in that When receiving a browsing request of a target knowledge point subpage in the nursing teaching training main page from a user, obtaining an estimated browsing time of the user includes: Upon receiving a browsing request of a target knowledge point subpage in the nursing teaching training main page from a user, obtaining the learning interval duration of the user; When the learning interval is greater than a preset time, obtaining learned related knowledge points that need to be mastered to learn the target knowledge point; When the sum of the estimated learning time of the associated knowledge points and the target knowledge points is greater than the estimated browsing time, the contents of the associated knowledge points and the target knowledge points are refined and compressed to a target learning time, and the target learning time is less than or equal to the estimated browsing time; The refined and compressed content of the target knowledge point is displayed on a sub-page so that the user can complete the complete learning of the target knowledge point within the expected browsing time.

8. An intelligent auxiliary device for nursing teaching and training, characterized in that: include: An acquisition unit is used to acquire a page interaction request of a user for a link to a nursing teaching and training main page, wherein the page interaction request includes a link address, and the link address is associated with QR code identification information, so that a smart terminal device under the user obtains the link address based on the QR code analysis, and different link addresses are associated with different categories of teaching and training content on the nursing teaching and training main page; A statistical unit, used to count the number of browsing requests of users for different knowledge point sub-pages of teaching and training content in the nursing teaching and training main page; The display unit is used to sort and display the different knowledge point entries in the nursing teaching and training main page according to the number of browsing requests for different knowledge points in the same nursing teaching and training main page, so that the entries of the knowledge points with more browsing times are displayed first in the nursing teaching and training main page to which they belong.

9. An electronic system, comprising a memory and a processor, characterized in that: The processor is used to implement the steps of the intelligent auxiliary method for nursing teaching and training as described in any one of claims 1 to 7 when executing the computer program stored in the memory.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the intelligent auxiliary method for nursing teaching and training as described in any one of claims 1 to 7 are implemented.

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