A method and system for video training in an offline environment

Abstract

A kind of offline video training method, comprising: after receiving the login information of student end, verify whether login information meets preset requirement;When login information meets preset requirement, create a session for student end, assign a session identifier;Student end is assigned different access permissions;Customize learning plan for student end, and query training progress;Recommend corresponding training content and answer point information;In networked state, pre-download training content and answer point information to local storage;When detecting network disconnection, automatically switch to offline mode, play pre-downloaded training content and answer point information;When training content and answer point information are played, store the answer result and offline training progress in the ship end;When network is restored, based on session identifier, offline training progress and answer result are stored in the shore end synchronously;Identify weak points and learning preferences, and customize learning plan again.The present application has the effect of greatly expanding the training time and range.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of information technology, and particularly relates to a video training method and system in an offline environment. BACKGROUND

[0002] Currently, crew training usually relies on the Internet, which involves watching training videos online, completing online quizzes and recording learning progress. However, this Internet-dependent training mode encounters challenges when the crew is on a long voyage, because they often cannot access the network during this period, which easily leads to the interruption of training activities and the failure of normal training, thereby resulting in poor training effect. Therefore, improvement is needed. SUMMARY

[0003] In order to solve the above problems, the present application provides a video training method and system in an offline environment.

[0004] The application purpose of the present application is achieved by the following technical scheme:

[0005] A video training method in an offline environment, characterized in that it comprises the following steps:

[0006] After receiving the login information of the student end, it is verified whether the login information meets the preset requirements;

[0007] When the login information meets the preset requirements, a session is created for the student end, and a session identifier is assigned;

[0008] Based on the login information of the student end, different access permissions are assigned to the student end;

[0009] Based on the access permissions, a learning plan is customized for the student end, and the training progress is queried;

[0010] Based on the training progress and the learning plan, corresponding training content and quiz point information are recommended;

[0011] In a networked state, the training content and the quiz point information are pre-downloaded to the local storage;

[0012] When the network is disconnected, the offline mode is automatically switched, and the pre-downloaded training content and quiz point information are played;

[0013] When the training content and the quiz point information are played, the quiz results and the offline training progress are stored in the ship end;

[0014] When the network is restored, based on the session identifier, the offline training progress and the quiz results are stored in the shore end;

[0015] Based on a preset algorithm, knowledge weak points and learning preferences are identified, and the learning plan is re-customized.

[0016] In a preferred embodiment, the step of assigning different access rights to the student terminal based on the login information of the student terminal comprises the steps of:

[0017] Extracting keywords based on the login information of the student terminal, the keywords including the username and the department;

[0018] Matching the keywords with preset permission rules;

[0019] Assigning corresponding access rights to the student terminal based on the matching results;

[0020] The access rights from low to high include training permission, training management permission, and system management permission, corresponding to the roles of training personnel, training management personnel, and system management personnel.

[0021] In a preferred embodiment, the step of customizing a learning plan for the student terminal and querying the training progress based on the access rights comprises the steps of:

[0022] Generating a preliminary learning plan for the training personnel;

[0023] Matching the training needs of the training personnel from a preset offline database;

[0024] Adjusting the preliminary learning plan based on the training needs by the training management personnel, and finalizing the learning plan by the system management personnel;

[0025] The learning plan includes training courses and a learning schedule.

[0026] In a preferred embodiment, the step of pre-downloading training content and answer point information to local storage in a networked state comprises the steps of:

[0027] Pre-downloading training content and related interactive questions to local storage in a networked state;

[0028] The interactive questions include multiple-choice questions, fill-in-the-blank questions, and true-or-false questions;

[0029] Setting a mapping point for each interactive question, the mapping point corresponding to a specific time of the training content and being stored locally.

[0030] In a preferred embodiment, the step of automatically switching to an offline mode and playing the pre-downloaded training content and answer point information when the network is detected to be disconnected comprises the steps of:

[0031] Based on the playing progress and the preset mapping points, pausing the playing of the training content when the mapping point is reached, and popping up the interactive question associated with the mapping point;

[0032] The preset mapping points include a time point of a key knowledge point, a time point of the end of a skill demonstration, and a time point of the end of a theoretical explanation.

[0033] When the training personnel answer the interactive question correctly, the following operations are performed:

[0034] The training content is continued to play to the next mapping point.

[0035] When the training personnel answer the interactive question incorrectly, the following operations are performed:

[0036] Instant feedback is provided to explain the correct answer.

[0037] A review link is jumped to, and the relevant knowledge points are re-explained.

[0038] The content before the current mapping point is repeated, and the interactive question is answered again.

[0039] When the training personnel answer the interactive question incorrectly for multiple times in succession, feedback is given to the training management personnel and the system management personnel, and a learning plan is re-customized.

[0040] In a preferred embodiment, the step of identifying knowledge weak points and learning preferences based on a preset algorithm and re-customizing a learning plan comprises the following steps:

[0041] Based on a preset algorithm, the answer result information and the time information of watching the training content are extracted from the offline training progress and the answer result.

[0042] The answer result information and the time information of watching the training content are analyzed to identify knowledge weak points and learning preferences.

[0043] The answer result information includes accuracy and answer speed.

[0044] The time information of watching the training content includes watching time and pause times.

[0045] The knowledge weak points include questions with accuracy less than a first preset threshold and questions with answer speed less than a second preset threshold.

[0046] The learning preferences include questions with watching time greater than a third preset threshold and questions with pause times greater than a fourth preset threshold.

[0047] Based on the learning preferences and the knowledge weak points, feedback is given to the training management personnel and the system management personnel, and a learning plan is re-customized.

[0048] The above-mentioned second purpose of the present application is achieved by the following technical scheme:

[0049] A video training system in an offline environment comprises:

[0050] receiving module: after receiving the login information of the student terminal, verifying whether the login information meets the preset requirements;

[0051] session creation module: when the login information meets the preset requirements, creating a session for the student terminal and assigning a session identifier to the student terminal;

[0052] assignment module: based on the login information of the student terminal, assigning different access permissions to the student terminal;

[0053] planning module: based on the access permissions, customizing a learning plan for the student terminal and querying the training progress;

[0054] recommendation module: based on the training progress and the learning plan, recommending corresponding training content and answer point information;

[0055] pre-download module: in a network-connected state, pre-downloading the training content and the answer point information to the local storage;

[0056] offline playback module: when detecting that the network is disconnected, automatically switching to offline mode and playing the pre-downloaded training content and answer point information;

[0057] offline storage module: after the training content and the answer point information are played, storing the answer results and the offline training progress on the student terminal;

[0058] online storage module: when the network is restored, based on the session identifier, synchronously storing the offline training progress and the answer results on the shore terminal;

[0059] recognition module: based on a preset algorithm, recognizing knowledge weak points and learning preferences and customizing a new learning plan.

[0060] The above-mentioned fourth purpose of the present application is achieved through the following technical solution:

[0061] A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-mentioned offline video training method.

[0062] The above-mentioned fourth purpose of the present application is achieved through the following technical solution:

[0063] A computer-readable storage medium, which stores a computer program, wherein the computer program is executed by a processor to implement the steps of the above-mentioned offline video training method.

[0064] In summary, the present application includes at least one of the following beneficial technical effects:

[0065] 1. The application verifies the login information of the trainee end and creates a session for them, ensuring the security of the system and the legitimacy of the user's identity. This step not only prevents unauthorized access, but also provides protection for basic user management. Secondly, by assigning different access permissions to trainees, the system achieves fine-grained management of resources, allowing each trainee to access training content that matches their responsibilities, thereby improving the relevance and practicality of the training.

[0066] 2. The application provides a personalized learning path for trainees through customized learning plans and query training progress, which not only improves learning efficiency but also enhances the learning motivation of trainees. Recommending relevant training content and answer point information further ensures that trainees can focus on their weaknesses for targeted learning.

[0067] 3. The pre-download function of the application allows trainees to continue learning even when the network is unstable or unavailable, greatly improving the flexibility and continuity of training. The ability to automatically switch to offline mode ensures that training will not be interrupted due to network problems, which is particularly important for seafarers training in offshore or other remote environments.

[0068] 4. After training is completed, the answer results and offline training progress are stored on the ship end and synchronized to the shore end when the network is restored, ensuring data integrity and real-time, allowing training managers to promptly understand the learning status and progress of trainees.

[0069] 5. Based on the preset algorithm to identify knowledge weaknesses and learning preferences, the learning plan is customized again, which is an intelligent feedback and adjustment mechanism that can help trainees more effectively master knowledge points and improve the overall effectiveness of training. This ability to dynamically adjust the learning plan not only improves the level of personalization of training, but also provides data support for continuous improvement of training content and methods. BRIEF DESCRIPTION OF DRAWINGS

[0070] Figure 1 is an implementation flowchart of an embodiment of the video training method in an offline environment according to the application;

[0071] Figure 2 is an implementation flowchart of step S30 in an embodiment of the video training method in an offline environment according to the application;

[0072] Figure 3 is a first implementation flowchart of step S40 in an embodiment of the video training method in an offline environment according to the application;

[0073] Figure 4 is an implementation flowchart of step S60 in an embodiment of the video training method in an offline environment according to the application;

[0074] Figure 5 is an implementation flowchart after step S70 in an embodiment of the video training method in an offline environment of the present application;

[0075] Figure 6 is an implementation flowchart of step S100 in an embodiment of the video training method in an offline environment of the present application;

[0076] Figure 7 is a principle block diagram of a computer device of the present application. DETAILED DESCRIPTION

[0077] The following will be described in detail in combination with the accompanying drawings. Figures 1-7 The present application will be further described in detail.

[0078] In an embodiment, as shown in the accompanying drawings, the present application discloses a video training method in an offline environment, which specifically includes the following: Figure 1

[0079] S10: After receiving the login information of the student end, verify whether the login information meets the preset requirements;

[0080] In this embodiment, after receiving the login information of the student end, a series of verification steps will be performed to ensure that the information meets the preset security and format requirements.

[0081] S20: When the login information meets the preset requirements, create a session for the student end and assign a session identifier;

[0082] In this embodiment, once the login information of the student end passes the verification (as described in step S10), the following operations will be performed to establish a session for the student: a new session is created for the student, which is a server-side process to track and identify the active status and operations of the student. With the creation of the session, a unique session identifier (usually a randomly generated string) will be assigned to the session. This session identifier will be used in all subsequent interactions to identify the specific student session.

[0083] S30: Based on the login information of the student end, assign different access permissions to the student end;

[0084] In this embodiment, different access permissions will be assigned according to the login information of the student,

[0085] In an offline environment, the assignment of access permissions also determines which resources the student can access without network connection. This is crucial for seafarers working at sea or other remote areas, as network connection in these areas may be unstable or unavailable. In this way, step S30 not only ensures the security of the training content, but also ensures that the student can obtain learning resources that match their duties and training needs even in an offline environment.​

[0086] S40: Customize learning plan for trainee based on access rights and query training progress;

[0087] In this embodiment, the core of S40 is to use the trainee's access rights to tailor a learning plan for them and track their training progress, which is particularly important in offline environments. Here is a detailed explanation:

[0088] In the offline environment of seafarer training, due to the instability of network connection, the learning plan of trainees needs to be customized in advance according to their access rights to ensure that trainees can follow the established training path for learning even in offline state.

[0089] Based on the access rights assigned in S30, combined with the trainee's position, responsibilities, training history and future training needs, a personalized learning plan is developed for the trainee. At the same time, the trainee's current training progress is queried, including completed courses, ongoing courses and courses yet to start. This information is crucial to ensure that trainees do not repeat learning of mastered content or skip necessary training steps. The customized learning plan will guide the trainee on what content to learn in offline state, as well as the order and pace of learning. This helps trainees maximize learning effectiveness with limited resources. In offline environments, this customized learning plan also helps trainees effectively use their time, ensuring uninterrupted training and education during sea operations. Through S40, the seafarer training system can provide a structured and personalized learning experience for trainees in offline environments, ensuring that seafarers' professional skills and knowledge levels meet the requirements of sea operations.

[0090] S50: Recommend appropriate training content and answer point information based on training progress and learning plan;

[0091] In this embodiment, the purpose of S50 is to recommend the most appropriate training content and answer point information to the trainee based on their training progress and learning plan, to ensure that even in offline state, the trainee can receive efficient and relevant training. Here is a detailed explanation:

[0092] In an offline environment, where real-time access to server content is not possible, it becomes crucial to pre-recommend appropriate training content to the trainee. The system determines the next courses and exercises the trainee needs to learn based on the customized learning plan and the training progress obtained in step S40. The recommended training content may include video tutorials, interactive simulations, case studies, and more, carefully selected to meet the trainee's learning objectives and actual job requirements. The answer point information refers to the questions or knowledge points related to the training content, which helps the trainee consolidate learning outcomes and verify the level of knowledge mastery through testing. During the recommendation process, the system takes into account the trainee's learning speed, understanding ability, and previous answer performance to ensure that the recommended content is neither too simple nor too difficult, but just right to meet the trainee's learning needs. In this way, even in an offline state, the trainee can follow a continuous and orderly learning path for training, without interruption of the learning process or receiving inappropriate training content due to network problems. Step S50 plays a bridge role in the offline environment of seafarer training, ensuring that trainees can still receive targeted training without network connection, thereby improving the efficiency and effectiveness of training.

[0093] S60: Pre-download training content and answer point information to local storage in a network-connected state;

[0094] In this embodiment, step S60 is a key preparation step to ensure that seafarers can continue to receive training in an offline state. Here is a detailed explanation:

[0095] In a network-connected state, the system pre-downloads the training content and answer point information that the trainee needs according to his learning plan and progress to the local storage. This is done to ensure that once the network is disconnected, the trainee can still access these training resources. The pre-downloaded content may include teaching videos, documents, and other resources carefully selected to meet the trainee's learning needs, ensuring the continuity and effectiveness of training. By pre-downloading these resources when connected to the network, the system provides a "buffer" for the trainee, so that even in unstable network environments such as at sea or in remote areas, the trainee can continue to learn uninterrupted. The local storage can be a server on the ship, a personal computer, or other storage devices, as long as the trainee can access these resources offline. The importance of step S60 lies in its provision of a reliable offline learning solution for seafarers, which is crucial for ensuring the continuous updating of seafarers' professional knowledge and skills, especially during long-term sea missions. Through step S60, the seafarer training system can maintain the continuity of training in an offline environment, ensuring that seafarers can receive necessary education and training in any situation.

[0096] S70: When network disconnection is detected, automatically switch to offline mode, play pre-downloaded training content and answer point information;

[0097] In this embodiment, S70 step is designed to ensure that crew training can continue seamlessly in the case of network unavailability. The following is a detailed explanation:

[0098] During the crew training process, network connection may be interrupted for various reasons (such as maritime communication restrictions, equipment failure, etc.). S70 step automatically detects network status and switches to offline mode immediately upon detecting network disconnection. After switching to offline mode, the system begins playing pre-downloaded training content and answer point information stored locally. These contents are pre-downloaded in S60 step to ensure that trainees can access training materials even in offline state. The use of offline mode ensures that crew members will not be interrupted by network problems, which is crucial for maintaining the continuity and integrity of training, especially in professional fields that require continuous learning. In offline mode, trainees can continue to watch instructional videos and read training documents, and these activities will not be affected by network status. The design of S70 step reflects the consideration of the special environment of crew training, ensuring that training activities can proceed smoothly under various network conditions, thereby ensuring the professional skills and knowledge level of crew members. Through S70 step, the crew training system can adapt to offline environments and provide a stable and reliable learning platform for crew members, which is of great significance for improving the overall quality of crew members and their ability to respond to emergencies.

[0099] S80: When the training content and answer point information are played, store the answer results and offline training progress on the ship side;

[0100] In this embodiment, S80 step is designed to ensure that the learning achievements and progress of trainees in offline state are properly recorded and saved. The following is a detailed explanation:

[0101] In the offline environment of crew training, due to the instability or complete disconnection of the network, trainees cannot upload learning data to the central server in real time. Therefore, S80 step saves the answer results and training progress of trainees after completing the training in the local system on the ship side, ensuring that these valuable data will not be lost due to network problems.

[0102] This step is crucial for tracking the learning history of trainees, evaluating learning effectiveness, and synchronizing data when the network is reconnected in the future. It allows training managers or trainees themselves to view and analyze their performance during offline learning after the network is restored.

[0103] By storing these data on the ship end, the system also provides a continuous learning experience for the trainee, even if the user completes the training content in offline state, their efforts and achievements can be recognized.

[0104] S80 step embodies the consideration of the special needs of seafarer training, ensuring that even in offline conditions, seafarers can maintain continuous improvement of professional knowledge and skills, which is crucial for maritime safety and efficiency.

[0105] Overall, S80 step provides a reliable learning record and progress management mechanism for seafarers in offline environment, ensuring the continuity and effectiveness of training.

[0106] S90: When the network is restored, based on the session identifier, synchronize the offline training progress and answer results to the shore end;

[0107] In this embodiment, S90 step ensures that after the network is restored, the learning activities and achievements completed by the trainee in offline mode can be accurately recorded and updated to the central database or shore end server. Here is the detailed explanation:

[0108] During seafarer training, due to the particularity of maritime operations, network connection may be frequently interrupted or unavailable for a long time. S90 step allows the system to synchronize the learning progress and answer results completed by the trainee in offline state to the shore end server when the network is reconnected.

[0109] By using the session identifier, the system can accurately match the offline learning data with the corresponding trainee account, ensuring the integrity and accuracy of the data. This is crucial for maintaining the learning records of trainees and conducting subsequent learning analysis.

[0110] The synchronization process allows training managers to monitor the learning status of trainees in real time, evaluate training effectiveness, and adjust training plans as needed. At the same time, trainees can also receive the latest learning materials and guidance.

[0111] S90 step also means that even in offline environment, the learning activities of trainees will not be wasted, their efforts and achievements can be officially recorded and recognized after the network is restored.

[0112] In the offline environment of seafarer training, S90 step is the bridge connecting offline learning and online management, which guarantees the coherence and efficiency of the training system, and also provides a more flexible and reliable learning experience for trainees.

[0113] S100: Based on the preset algorithm, identify knowledge weaknesses and learning preferences, and customize the learning plan.

[0114] In this embodiment, S100 step is the key link in the whole training process, which uses data analysis to optimize the learning experience of the crew and improve the training effect. The following is a detailed explanation:

[0115] In the offline environment, the crew's learning activities and answer results are recorded and synchronized to the shore server in S90 step. S100 step analyzes these data and uses preset algorithms to identify the crew's knowledge weaknesses and learning preferences. The identification of knowledge weaknesses is achieved by analyzing the crew's error types and frequencies during the answering process, so that additional training and review materials can be provided to help the crew strengthen their learning in these areas. The identification of learning preferences takes into account the crew's learning habits, interest points, and learning efficiency, etc. The system adjusts the learning plan accordingly to better meet the crew's individual needs. In the offline environment of crew training, the importance of S100 step lies in its ability to ensure that even in a network-limited situation, the training content can be personalized according to the crew's learning situation, thereby improving the training's relevance and effectiveness. By customizing the learning plan, the system can help the crew more efficiently master the necessary knowledge and skills, which is of great significance to ensuring the safety of maritime operations and improving the professionalism of the crew. In summary, S100 step plays a bridge role in the offline environment of crew training, it converts the crew's learning data into actual training actions, ensuring the maximum utilization of training resources and meeting the crew's individual development needs.

[0116] Figure 2 , S30 step, including steps:

[0117] S301: Based on the login information of the student side, extract keywords, including username, department;

[0118] S302: Match the keywords with the preset permission rules;

[0119] S303: Based on the matching result, assign the corresponding access rights to the student side;

[0120] S304: The access rights from low to high include training rights, training management rights, system management rights, and the corresponding roles are training personnel, training management personnel, and system management personnel.

[0121] In this embodiment, these steps together constitute a permission allocation mechanism for determining the access level of the student in the training system according to the student's login information. The following is a detailed explanation:

[0122] In S301 step, the system extracts key information such as username and department from the student's login information. These information is usually related to the student's identity and position in the organization, and is the basis for determining their access rights.

[0123] In step S302, the extracted keywords are matched with the system's pre-set permission rules. These rules define the correspondence between different usernames or departments and specific access permissions. For example, all members of a certain department may be granted a specific level of permission.

[0124] In step S303, based on the matching results of keywords and permission rules, the system will assign the corresponding access permissions to the trainees. This process is automated, ensuring consistency and accuracy in permission allocation.

[0125] Step S304 details the hierarchical structure of access permissions, from low to high, which includes training permissions, training management permissions, and system management permissions. These permissions correspond to different roles, with training personnel typically only having access to training content, training managers being able to manage training materials and progress, and system managers having the highest permissions to manage system settings and user permissions.

[0126] This permission allocation mechanism ensures that trainees can only access the content and functions they are authorized to access in the training system, thereby protecting the security of the system and improving the efficiency of training management. In this way, organizations can customize the training experience for trainees based on their roles and responsibilities, ensuring the rational allocation and utilization of resources.

[0127] Figure 3 In step S40, the steps include:

[0128] S401: Generate a preliminary learning plan for the training personnel;

[0129] S402: Match the training needs of the training personnel from the pre-set offline database;

[0130] S403: Based on the training needs, the training manager adjusts the preliminary learning plan, and the system manager reviews and determines the final learning plan;

[0131] S404: The learning plan includes training courses and a learning schedule.

[0132] In this embodiment, these steps describe the entire process of creating and customizing learning plans for training personnel, particularly suitable for training management in offline environments. Here is a detailed explanation:

[0133] In step S401, the system will automatically generate a preliminary learning plan for each training personnel. This preliminary plan may be based on a general training template or the default needs of the training personnel.

[0134] In step S402, the system retrieves and matches the specific training needs of the training personnel from a pre-set offline database. The offline database contains information on training courses, skill requirements, job standards, etc., which are used to determine what specific training content the training personnel needs.

[0135] In step S403, the training manager adjusts the initial learning plan based on the training needs extracted from the offline database. This may include adding or removing certain courses, adjusting the learning sequence, etc. The adjusted learning plan is then reviewed by the system manager to ensure that the plan meets organizational standards and training objectives, and then the final learning plan is determined.

[0136] Step S404 specifies the content of the learning plan, including specific training courses and learning schedules. These courses and schedules are tailored to the actual needs and work arrangements of the training personnel, aiming to provide a structured and orderly learning path.

[0137] This learning plan development process ensures that even in offline environments, training personnel can access learning content that meets their individual and job requirements. Through the collaboration of training managers and system managers, the effectiveness and practicality of the learning plan can be ensured, thereby improving training effectiveness.

[0138] Figure 4 Step S60 includes the following steps:

[0139] S601: Pre-download training content and related interactive questions to local storage when connected to the network;

[0140] S602: The interactive questions include multiple-choice questions, fill-in-the-blank questions, and true-or-false questions;

[0141] S603: Set a mapping point for each interactive question, which corresponds to the specific time of the training content and is stored locally.

[0142] In this embodiment, these steps describe how to prepare for offline training when connected to the network, ensuring that training personnel can effectively learn without network connection. Here is a detailed explanation:

[0143] In step S601, the system takes advantage of network connectivity to pre-download training content and related interactive questions to local storage devices. This is done to ensure that training personnel can still access these resources in offline state and not be interrupted by network problems.

[0144] Step S602 specifies the types of interactive questions, including multiple-choice questions, fill-in-the-blank questions, and true-or-false questions. These questions are designed to improve the interactivity and participation of training, helping training personnel better understand and master the training content.

[0145] In step S603, the system sets a mapping point for each interactive question, which corresponds to a specific time of the training content. For example, if an interactive question is asked at 5 minutes of a training video, the mapping point corresponds to the 5-minute timestamp of the video. Such mapping relationships are stored locally so that the system can trigger interactive questions at the correct time point when playing the training content offline.

[0146] This pre-download and mapping point setting method ensures the availability and interactivity of the training content in offline environments, allowing trainees to effectively self-study and evaluate even in situations where network is unavailable. This method is particularly suitable for seafarer training in offshore or other remote areas where stable network connection may not be guaranteed.

[0147] Figure 5 , S70 step, after step:

[0148] S71: Based on the playback progress and the preset mapping points, when the mapping point is reached, pause the playback of the training content and pop up the interactive question associated with the mapping point;

[0149] S72: The preset mapping points include the time points of key knowledge points, the time points of the end of skill demonstration, and the time points of the end of theoretical explanation;

[0150] S73: When the trainee answers the interactive question correctly, the following operations are performed:

[0151] S74: Continue playing the training content to the next mapping point;

[0152] S75: When the trainee answers the interactive question incorrectly, the following operations are performed:

[0153] S76: Provide immediate feedback and explain the correct answer;

[0154] S77: Jump to a review section to re-explain the relevant knowledge points;

[0155] S78: Repeat the content before the current mapping point, and learn and answer the interactive question again;

[0156] S79: When the trainee answers the interactive question incorrectly for multiple times in a row, feedback is given to the training manager and system administrator to customize the learning plan again.

[0157] In this embodiment, these steps constitute an interactive learning feedback mechanism aimed at improving training effectiveness and student engagement. The following is a detailed explanation:

[0158] In step S71, the system pauses the playback at key time points based on the playback progress of the training content and pre-set mapping points, and pops up relevant interactive questions. This design ensures that the trainee receives timely reinforcement and testing on key knowledge points.

[0159] Step S72 explains the types of mapping points, including the end time points of key knowledge points, skill demonstrations, and theoretical explanations. These time points are set based on the importance and complexity of the training content.

[0160] Steps S73 to S78 describe different feedback mechanisms after the trainee answers the interactive questions:

[0161] When the trainee answers correctly (S73), the system continues to play the training content to the next mapping point (S74).

[0162] When the trainee answers incorrectly (S75), the system provides immediate feedback and correct answer explanations (S76), then jumps to the review section (S77), or repeats the content before the current mapping point for the trainee to learn and answer the question again (S78).

[0163] Step S79 provides an additional support mechanism. When the trainee answers incorrectly for multiple times in a row, the system will feedback this situation to the training management personnel and system management personnel, so that they can intervene and re-customize the learning plan to better meet the learning needs of the trainee.

[0164] This interactive learning feedback mechanism not only enhances the interactivity and effectiveness of learning, but also dynamically adjusts the learning plan according to the performance of the trainee, thereby providing a more personalized and effective training experience.

[0165] Figure 6 Step S100, including steps:

[0166] SA1: Based on a pre-set algorithm, extract the answer result information and the time information of watching the training content from the offline training progress and the answer result;

[0167] SA2: Analyze the answer result information and the time information of watching the training content to identify knowledge weak points and learning preferences;

[0168] SA3: The answer result information includes accuracy and answer speed;

[0169] SA4: The time information of watching the training content includes watching time and pause times;

[0170] SA5: The knowledge weak points include questions with accuracy less than a first pre-set threshold and questions with answer speed less than a second pre-set threshold;

[0171] SA6: The learning preference includes a question with a viewing duration greater than a third preset threshold value, and a question with a pause number greater than a fourth preset threshold value.

[0172] SA7: Based on the learning preference and the knowledge weak point, feedback is given to the training manager and the system manager, and the learning plan is re-customized.

[0173] In this embodiment, the steps of SA1 to SA7 describe an automated data analysis process that aims to optimize and personalize training plans by analyzing seafarers' offline training data. The following is a specific explanation of this process:

[0174] SA1: The system uses a preset algorithm to extract key data from the training progress and answer results completed by seafarers in offline state. These data include seafarers' answer results (such as correct or not, answer time) and their behavior data when watching training videos (such as viewing duration, pause number). SA2: The system then conducts in-depth analysis on these extracted data, aiming to identify seafarers' knowledge weak points and learning preferences in the learning process. Knowledge weak points refer to seafarers' lack of mastery of specific knowledge points, while learning preferences reveal seafarers' interest or learning habits for certain content. SA3: Answer result information specifically includes accuracy and answer speed. Accuracy refers to the percentage of seafarers' correct answers, and answer speed refers to the time seafarers take to answer questions. SA4: Time information for watching training content involves viewing duration and pause number. Viewing duration records the total time seafarers spend watching each training video, while pause number reflects the frequency of seafarers' pauses during watching. SA5: The identification of knowledge weak points is based on the comparison of seafarers' performance on specific questions with preset thresholds. If seafarers' accuracy on a question is lower than the first preset threshold, or the answer speed is slower than the second preset threshold, then this question is considered a knowledge weak point. SA6: The identification of learning preference is through the comparison of seafarers' viewing duration and pause number for specific questions with the third and fourth preset thresholds. When seafarers' viewing duration for a question is greater than the third preset threshold, or the pause number is greater than the fourth preset threshold, it may indicate that seafarers have a higher interest in the question or need more time to understand it. SA7: Finally, the system feeds back the learning preference and knowledge weak point information analyzed to the training manager and the system manager. These managers can use this information to re-customize the learning plan, ensuring that the training content is more in line with seafarers' individual needs, thereby improving the relevance and effectiveness of training. This data analysis process provides seafarers with a more personalized and efficient learning experience, helping to improve the overall quality of training and seafarers' professional skills.

[0175] It should be understood that the size of the serial number of each step in the above embodiments does not mean the order of execution, and the execution order of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0176] In an embodiment, a video training system in an offline environment is provided, which corresponds to the video training method in an offline environment in the above embodiments. The video training system in an offline environment comprises:

[0177] The receiving module: after receiving the login information of the student end, verifying whether the login information meets the preset requirements;

[0178] The session creation module: when the login information meets the preset requirements, creating a session for the student end and assigning a session identifier;

[0179] The assignment module: based on the login information of the student end, assigning different access permissions to the student end;

[0180] The planning module: based on the access permissions, customizing a learning plan for the student end and querying the training progress;

[0181] The recommendation module: based on the training progress and the learning plan, recommending corresponding training content and answer point information;

[0182] The pre-download module: in a networked state, pre-downloading the training content and the answer point information to the local storage;

[0183] The offline playback module: when detecting that the network is disconnected, automatically switching to the offline mode and playing the pre-downloaded training content and the answer point information;

[0184] The offline storage module: when the training content and the answer point information are played, storing the answer results and the offline training progress in the student end;

[0185] The online storage module: when the network is restored, based on the session identifier, synchronously storing the offline training progress and the answer results in the shore end;

[0186] The identification module: based on a preset algorithm, identifying knowledge weak points and learning preferences and customizing a learning plan again.

[0187] Optionally, it further comprises:

[0188] The keyword extraction module: based on the login information of the student end, extracting keywords, including the username and the department;

[0189] The first matching module: matching the keywords with preset permission rules;

[0190] The access permission assignment module: based on the matching result, assigning corresponding access permissions to the student end;

[0191] Access permission module: the access permission includes training permission, training management permission, system management permission from low to high, and the corresponding roles are training personnel, training management personnel, and system management personnel.

[0192] Optionally, the system further comprises:

[0193] Preliminary learning plan module: generating a preliminary learning plan for the training personnel;

[0194] Second matching module: matching the training needs of the training personnel from the preset offline database;

[0195] Final learning plan module: based on the training needs, the training management personnel adjusts the preliminary learning plan, and the system management personnel audits and determines the final learning plan;

[0196] Learning plan module: the learning plan includes training courses and a learning schedule.

[0197] Optionally, the system further comprises:

[0198] Pre-download content module: when connected to the network, pre-downloading training content and related interactive questions to local storage;

[0199] Interactive question module: the interactive questions include multiple-choice questions, fill-in-the-blank questions, and true-or-false questions;

[0200] Setting mapping point module: setting a mapping point for each interactive question, the mapping point corresponds to a specific time of the training content, and is stored locally.

[0201] Optionally, the system further comprises:

[0202] Pause module: based on the playing progress and the preset mapping point, when the mapping point is reached, pausing the playing of the training content, and popping up the interactive question associated with the mapping point;

[0203] Preset mapping point module: the preset mapping point includes a time point of a key knowledge point, a time point of the end of a skill demonstration, and a time point of the end of a theoretical explanation;

[0204] Correct answer module: when the training personnel answer the interactive question correctly, the following operations are performed:

[0205] Continue playing module: continuing to play the training content to the next mapping point;

[0206] Incorrect answer module: when the training personnel answer the interactive question incorrectly, the following operations are performed:

[0207] Explanation module: providing immediate feedback and explaining the correct answer;

[0208] Jumping module: jump to a review link to re-explain related knowledge points;

[0209] Repeat module: repeat the content before the current mapping point, and learn and answer interactive questions again;

[0210] Re-customization module: when the training personnel answer the interactive questions incorrectly for a plurality of times in succession, feedback to the training management personnel and the system management personnel, and re-customize the learning plan.

[0211] Optionally, it further comprises:

[0212] Extraction information module: based on a preset algorithm, extracting answer result information and viewing training content time information from offline training progress and answer results;

[0213] Analysis module: analyzing the answer result information and the viewing training content time information, identifying knowledge weak points and learning preferences;

[0214] Answer result information module: the answer result information comprises accuracy and answer speed;

[0215] Time information module: the viewing training content time information comprises viewing duration and pause times;

[0216] Knowledge weak point module: the knowledge weak points comprise questions with accuracy less than a first preset threshold and questions with answer speed less than a second preset threshold;

[0217] Learning preference module: the learning preferences comprise questions with viewing duration greater than a third preset threshold and questions with pause times greater than a fourth preset threshold;

[0218] Feedback personnel module: based on the learning preferences and the knowledge weak points, feedback to the training management personnel and the system management personnel, and re-customize the learning plan.

[0219] The specific limitations of the video training system in the offline environment can be seen in the limitations of the video training method in the offline environment described above, and will not be repeated here. Each module in the video training system in the offline environment described above can be realized by software, hardware and their combinations. The above modules can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory in the computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0220] In one embodiment, a computer device, which can be a server, is provided, and its internal structure diagram can be as shown in Figure 7The computer device includes a processor, a memory, a network interface and a database connected through a system bus. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for running the operating system and the computer program in the non-volatile storage medium. The database of the computer device is configured to store the answer results. The network interface of the computer device is configured to communicate with an external terminal through a network connection. The computer program is configured to be executed by the processor to implement the video training method in an offline environment.

[0221] In one embodiment, a computer device is provided, which includes a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor is configured to implement a video training method in an offline environment when executing the computer program.

[0222] In one embodiment, a computer readable storage medium is provided, which stores a computer program, and the computer program is configured to be executed by a processor to implement a video training method in an offline environment.

[0223] Those skilled in the art can understand that all or part of the processes of the above-mentioned embodiments can be completed by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer readable storage medium. When the computer program is executed, the processes of the above-mentioned embodiments can be included. Any reference to memory, storage, database or other medium used in the embodiments provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM) and memory bus dynamic RAM (RDRAM).

[0224] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above-mentioned division of each functional unit and module is exemplified, and in actual application, the above-mentioned functions can be completed by different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above.

[0225] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A method for video training in an offline environment, characterized by, The application relates to a method for customizing learning plans for trainees based on login information and training progress. After receiving the login information of the trainee, the application verifies whether the login information meets preset requirements. When the login information meets the preset requirements, a session is created for the trainee, and a session identifier is assigned. Based on the login information of the trainee, different access permissions are assigned to the trainee. Based on the access permissions, a learning plan is customized for the trainee, and the training progress is queried. Based on the training progress and the learning plan, corresponding training content and answer point information are recommended. In a networked state, the training content and the answer point information are pre-downloaded to local storage. When the network is disconnected, the application automatically switches to an offline mode and plays the pre-downloaded training content and answer point information. Based on the playing progress and preset mapping points, when the mapping points are reached, the playing of the training content is paused, and an interactive question associated with the mapping points is popped up. The preset mapping points include time points of key knowledge points, time points of the end of skill demonstration, and time points of the end of theoretical explanation. When the trainee answers the interactive question correctly, the following operations are performed: The training content is continued to be played until the next mapping point. When the trainee answers the interactive question incorrectly, the following operations are performed: Instant feedback is provided to explain the correct answer. A review link is jumped to, and relevant knowledge points are re-explained. The content before the current mapping point is repeated, and the interactive question is answered again. When the trainee answers the interactive question incorrectly for multiple times in succession, feedback is given to a training manager and a system manager, and a learning plan is re-customized. When the training content and the answer point information are played, the answer result and the offline training progress are stored on the trainee side. When the network is restored, based on the session identifier, the offline training progress and the answer result are synchronously stored on the shore side. Based on a preset algorithm, knowledge weak points and learning preferences are identified, and a learning plan is re-customized. Based on the preset algorithm, answer result information and time information of watching the training content are extracted from the offline training progress and the answer result. The answer result information and the time information of watching the training content are analyzed to identify the knowledge weak points and the learning preferences. The answer result information includes accuracy and answer speed. The time information of watching the training content includes watching time length and pause times. The knowledge weak points include questions with accuracy less than a first preset threshold and questions with answer speed less than a second preset threshold. The learning preferences include questions with watching time length greater than a third preset threshold and questions with pause times greater than a fourth preset threshold. Based on the learning preferences and the knowledge weak points, feedback is given to the training manager and the system manager, and the learning plan is re-customized.

2. The method of claim 1, wherein, The step of assigning different access permissions to the trainee based on the login information of the trainee includes the following steps: Based on the login information of the trainee, keywords including a username and a department are extracted. The keywords are matched with preset permission rules. Based on the matching result, corresponding access permissions are assigned to the trainee. From low to high, the access permissions include training permissions, training management permissions and system management permissions, and corresponding roles are training personnel, training managers and system managers.

3. The method of claim 1, wherein, The step of customizing a learning plan for the trainee based on the access permissions and querying the training progress includes the following steps: Generating a preliminary learning plan for the trainee; Matching the training needs of the trainee from the preset offline database; Adjusting the preliminary learning plan based on the training needs by the training manager, and determining the final learning plan by the system manager; The learning plan includes training courses and a learning schedule.

4. The method of claim 1, wherein, The step of pre-downloading the training content and the answer point information to the local storage in the networked state comprises the steps of: Pre-downloading the training content and the related interactive questions to the local storage in the networked state; The interactive questions include multiple-choice questions, fill-in-the-blank questions, and true-or-false questions; A mapping point is set for each interactive question, which corresponds to a specific time of the training content and is stored locally.

5. A video training system in an offline environment, characterized by, It comprises: A receiving module: after receiving the login information of the trainee, verify whether the login information meets the preset requirements; A session creation module: when the login information meets the preset requirements, create a session for the trainee and assign a session identifier; An allocation module: based on the login information of the trainee, allocate different access permissions to the trainee; A plan module: based on the access permissions, customize a learning plan for the trainee and query the training progress; A recommendation module: based on the training progress and the learning plan, recommend the corresponding training content and answer point information; A pre-download module: in the networked state, pre-download the training content and the answer point information to the local storage; An offline playback module: when the network is detected to be disconnected, automatically switch to offline mode and play the pre-downloaded training content and answer point information; A pause module: based on the playback progress and the preset mapping points, pause the playback of the training content when the mapping points are reached, and pop up the interactive questions associated with the mapping points; A preset mapping point module: the preset mapping points include the time points of key knowledge points, the time points of the end of skill demonstration, and the time points of the end of theoretical explanation; A correct answer module: when the trainee answers the interactive questions correctly, the following operations are performed: A continue playback module: continue playing the training content until the next mapping point; An incorrect answer module: when the trainee answers the interactive questions incorrectly, the following operations are performed: An explanation module: provide immediate feedback and explain the correct answers; A jump module: jump to a review section and re-explain the related knowledge points; A repeat module: repeat the content before the current mapping point, and learn and answer the interactive questions again; A re-customization module: when the trainee answers the interactive questions incorrectly for multiple times in succession, feedback to the training manager and the system manager, and re-customize the learning plan; An offline storage module: when the training content and the answer point information are played, store the answer results and the offline training progress on the trainee side; An online storage module: when the network is restored, based on the session identifier, synchronize the offline training progress and the answer results to the shore side; An identification module: based on the preset algorithm, identify the knowledge weak points and the learning preferences, and re-customize the learning plan; An information extraction module: based on the preset algorithm, extract the answer result information and the time information of watching the training content from the offline training progress and the answer results; An analysis module: analyze the answer result information and the time information of watching the training content, identify the knowledge weak points and the learning preferences; The answer result information includes accuracy and answer speed. The time information of watching the training content includes watching time length and pause times. The knowledge weak point includes questions with accuracy less than a first preset threshold and questions with answer speed less than a second preset threshold. The learning preference includes questions with watching time length greater than a third preset threshold and questions with pause times greater than a fourth preset threshold. The feedback personnel module feeds back to the training management personnel and the system management personnel based on the learning preference and the knowledge weak point, and customizes a learning plan again.

6. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the steps of the video training method in the offline environment according to any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, wherein the computer program comprises the following steps of: receiving a request for a resource from a client; determining whether the client is authorized to access the resource; and if the client is authorized to access the resource, providing the resource to the client. The computer program is executed by the processor to implement the steps of the video training method in the offline environment according to any one of claims 1 to 4.

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