Method, device and equipment for displaying learning path, medium and product

Abstract

The embodiment of the invention designs a method and device for displaying a learning path, equipment, a medium and a product. The method includes generating, by a model, a learning path based on input information, the learning path including at least one node. The method further comprises the step of displaying the learning path on a visual interface. The method further comprises the step of adjusting the display of the learning path on the visual interface in response to the interactive operation of the user. Through the method, the interactive learning path can be automatically generated, the problem that a traditional learning path planning tool lacks individuation, interactivity and dynamic adjustment capability is solved, and a user is helped to more efficiently plan and manage the learning process.

Description

Technical Field

[0001] The embodiments of this disclosure generally relate to the field of computers, and more specifically to methods, apparatuses, devices, media, and products for demonstrating learning paths. Background Technology

[0002] The model can analyze learners' knowledge structure, learning preferences, and ability levels, providing core technical support for building a dynamically adaptable learning system. Based on the model's semantic understanding and generation capabilities, it can overcome the limitations of traditional standardized learning paths in various learning systems, enabling a shift from static knowledge transmission to dynamic interactive guidance, and achieving personalized learning strategy planning.

[0003] The visualized interactive learning path revolves around the dynamic perception of learners' states, the construction of connections between knowledge nodes, and the innovative design of interaction methods, addressing learning needs across all stages from basic cognition to in-depth exploration. It shows promise for applications in practical scenarios such as personalized tutoring, skills advancement, and cross-disciplinary knowledge integration. Summary of the Invention

[0004] Embodiments of this disclosure provide a method, apparatus, device, medium, and product for demonstrating a learning path.

[0005] According to a first aspect of this disclosure, a method for displaying a learning path is provided. The method includes generating a learning path based on input information using a model, the learning path including at least one node. The method also includes displaying the learning path on a visualization interface. Furthermore, the method includes adjusting the display of the learning path on the visualization interface in response to user interaction.

[0006] According to a second aspect of this disclosure, an apparatus for displaying a learning path is provided. The apparatus includes a learning path generation module configured to generate a learning path based on input information using a model, the learning path including at least one node; a display module configured to display the learning path on a visualization interface; and an interaction module configured to adjust the display of the learning path on the visualization interface in response to user interaction.

[0007] In a third aspect of this disclosure, an electronic device is provided, including at least one processor; and a storage device for storing at least one program, which, when executed by the at least one processor, causes the at least one processor to implement the method according to the first aspect of this disclosure.

[0008] In a fourth aspect of this disclosure, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the method according to a first aspect of this disclosure.

[0009] In a fifth aspect of this disclosure, a computer program product is provided. This computer program product includes a computer program that, when executed by a processor, implements the method according to a first aspect of this disclosure.

[0010] It should be understood that the content described in this section is not intended to limit the key or essential features of the embodiments of this disclosure, nor is it intended to restrict the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0011] The above and other objects, features and advantages of this disclosure will become more apparent from the accompanying drawings, in which like reference numerals generally denote like parts.

[0012] Figure 1 The illustration shows a schematic diagram of an example environment in which some embodiments of the present disclosure may be implemented;

[0013] Figure 2 The illustration shows a schematic diagram of an example method for demonstrating a learning path according to some embodiments of the present disclosure;

[0014] Figure 3 The illustration shows a schematic diagram of an example of adjusting the node order according to some embodiments of the present disclosure;

[0015] Figure 4 The illustration shows a schematic diagram of switching learning path topics according to some embodiments of the present disclosure;

[0016] Figure 5 The illustration shows a schematic diagram of an expanded details page according to some embodiments of the present disclosure;

[0017] Figure 6 The illustration shows a schematic diagram of adding a new node according to some embodiments of the present disclosure;

[0018] Figure 7 The illustration shows a flowchart illustrating the learning progress according to some embodiments of the present disclosure;

[0019] Figure 8 The illustration shows a schematic diagram illustrating the learning progress according to some embodiments of the present disclosure;

[0020] Figure 9 The illustration shows a schematic block diagram of an apparatus for demonstrating a learning path according to some embodiments of the present disclosure;

[0021] Figure 10 A schematic block diagram of an example device suitable for implementing various embodiments of the present disclosure is illustrated. Detailed Implementation

[0022] It is understood that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and related provisions.

[0023] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0024] For example, upon receiving a user's proactive request, a prompt message is sent to the user to explicitly inform them that the requested operation will require the acquisition and use of the user's personal information. This allows the user to independently choose whether to provide personal information to the software or hardware, such as the electronic device, application, server, or storage medium performing the operations of this disclosed technical solution, based on the prompt message.

[0025] As an optional but non-limiting implementation, in response to a user's active request, sending a prompt message to the user can be done via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0026] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of this disclosure.

[0027] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0028] In the description of embodiments of this disclosure, the term "comprising" and similar terms should be understood as open-ended inclusion, i.e., "including but not limited to". The term "based on" should be understood as "at least partially based on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first", "second", etc., may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0029] Currently, online learning platforms and knowledge management tools typically use fixed course lists, static mind maps, or pre-set knowledge graphs to display learning paths. These methods lack personalization and dynamic adjustment capabilities, making it difficult for learners to intuitively understand the complete path to skill mastery.

[0030] Furthermore, learning path visualization tools are often created manually by content editing teams, resulting in long update cycles, an inability to quickly adjust to user needs, and a lack of personalized recommendations and progress tracking functions, leading to low learning efficiency and low user engagement.

[0031] To address this, embodiments of this disclosure propose a method for displaying learning paths. In this method, a learning path can be generated based on input information using a model, and the learning path includes at least one node. Furthermore, the learning path can be displayed on a visual interface. Finally, in response to user interaction, the display of the learning path on the visual interface is adjusted. This method automatically generates interactive learning paths, solving the problems of traditional learning path planning tools lacking personalization, interactivity, and dynamic adjustment capabilities, thus helping users plan and manage their learning processes more efficiently.

[0032] The embodiments of this disclosure will now be described in further detail with reference to the accompanying drawings. Figure 1 The illustration shows an example environment in which the devices and / or methods of embodiments of this disclosure may be implemented. In environment 100, model 104 can be used to generate learning paths for a user.

[0033] like Figure 1 As shown, in environment 100, input information 102 can be provided to model 104. Input information 102 can be user-inputted target skills, knowledge domains, etc. In some embodiments, input information 102 can be converted into a structured query that model 104 can process. For example, when input information 102 is "front-end learning," the input can be converted into the following structured input using a preset template:

[0034]

[0035]

[0036] Model 104 can analyze the input information 102 and generate a learning path 106. In some embodiments, model 104 can be a deep learning model such as a language model. In some embodiments, prompts can be designed to describe the task scenario, visual design specifications, and other information to guide model 104 in generating a learning path 106 that meets business needs. For example, the prompts could be designed as follows: "You are an interactive learning path visualization product design expert. Your task is to generate a dynamic learning path product interface based on the user's input of target skills or knowledge domains. Please be sure to follow the following requirements: main color XXX, background color XXX, font XXX…".

[0037] In some embodiments, model 104 can generate corresponding knowledge points based on input information 102. For example, when input information 102 is "front-end development," model 104 first generates several knowledge points to be learned, including "Hypertext Markup Language (HTML) & Cascading Style Sheets (CSS) basics," "JavaScript programming," "responsive design," "front-end frameworks," "development toolchains," and "advanced themes." Then, model 104 determines the dependencies between knowledge points and the recommended learning order. For example, "Learning JavaScript programming requires mastering HTML & CSS basics," and "Learning development toolchains requires mastering JavaScript programming and HTML & CSS basics," etc. Finally, based on the knowledge points, dependencies, and recommended learning order, a learning path 106 is generated. The learning path 106 may include multiple knowledge points or learning stages.

[0038] In some embodiments, model 104 can also generate detailed information for nodes in the learning path 106, such as a brief introduction to the knowledge point, recommended resource links, and suggested learning time. In some embodiments, users can click on the recommended resource links to jump to the corresponding course interface for learning.

[0039] The visualization interface 108 is used to present the learning path 106 generated by the model 104. In some embodiments, HTML can be used to create the basic container for the learning path 106, defining the elements of individual nodes and carrying the specific content of the learning path 106. In some embodiments, CSS can be used to control the appearance of nodes (including node size, color, border, and shadow, etc.) and design the style of the connections between nodes. In addition, responsive layouts can be implemented through fluid layouts, media queries, etc., so that the page can be adjusted according to different characteristics of the visualization interface 108. In some embodiments, JavaScript can be used to convert the learning path 106 generated by the model 104 into visual elements and implement user interaction functions.

[0040] This method automatically generates personalized learning paths for specific learning objectives, avoiding the limitations of traditional preset paths and making learning plans more aligned with users' actual needs. Furthermore, users can directly adjust the display of the learning path through interactive operations, achieving personalized customization of the learning plan.

[0041] The above combination Figure 1 The following is a schematic diagram illustrating an example environment in which some embodiments of this disclosure may be implemented, in conjunction with... Figure 2 A schematic diagram illustrating an example method for demonstrating a learning path according to some embodiments of the present disclosure.

[0042] like Figure 2 In example method 200, at box 202, a learning path is generated by a model based on input information. The learning path includes at least one node. In some embodiments, a large language model can be used to generate the learning path based on input information. The input information may be the user's target skill, knowledge domain, learner skill level, etc. In some embodiments, the user input may be further processed, such as being converted into a structured query before being provided to the large model. In some embodiments, each node of the learning path includes at least one knowledge point. In other embodiments, each node of the learning path includes at least one learning stage. In some embodiments, the model can be pre-trained to automatically construct a structured learning path that includes knowledge points, resource recommendations, and learning duration. For example, the model can be pre-trained by adding structured text such as subject outlines, knowledge point association descriptions, and knowledge graphs (course dependencies, knowledge point hierarchies) to the training data. In some embodiments, the model can recommend suitable learning resources based on the learner's skill level.

[0043] At box 204, the learning path is displayed on the visual interface. In some embodiments, the visualization of nodes can be implemented using HTML, CSS, and JavaScript. In some embodiments, preset visual design specifications (primary color, accent color, completion status color, etc.) can be applied to ensure a consistent user experience. For example, sky blue can be used as the primary color, golden yellow as the accent color, and light gray as the background color. In some embodiments, a responsive layout can be provided, allowing the display of the learning path to adapt to different visual interfaces. This enables the product to adapt to different devices and screen sizes, solving the adaptation problem for cross-device learning scenarios.

[0044] At box 206, the display of the learning path on the visualization interface is adjusted in response to user interaction. In some embodiments, the detailed information of a node can be expanded in response to a user click. In some embodiments, the node status (completed / incomplete) can be marked by user clicks. In some embodiments, nodes can be rearranged on the visualization interface by dragging.

[0045] The above methods can achieve an intuitive display of the learning path, and by enhancing interactivity, the learning path management tool can better meet users' cognitive habits and learning needs, thereby stimulating users' initiative and motivation for continuous learning.

[0046] The above combination Figure 2 The following is a schematic diagram illustrating an example method for demonstrating a learning path according to some embodiments of the present disclosure, in conjunction with... Figures 3-6 The illustration depicts a schematic diagram of adjusting the display of a learning path on a visualization interface in response to user interaction, according to some embodiments of the present disclosure.

[0047] Figure 3 The illustration shows an example of adjusting the node order according to some embodiments of the present disclosure. Figure 3 As shown, in the initial state 302 of the visual interface, the user initiates a drag-and-drop operation on a specific node (such as "JavaScript Programming"). When the user drags the node to a new position (such as above the node "HTML & CSS Basics") and releases it, the interface responds in real time. In the updated interface state 304, the display order of the nodes is dynamically adjusted (such as swapping the positions of the nodes "JavaScript Programming" and "HTML & CSS Basics"). In some embodiments, HTML can be used to define containers and draggable nodes, and JavaScript can be used to implement the response to drag-and-drop operations. In some embodiments, drag-and-drop effects (such as semi-transparency, real-time shadows, magnification feedback, etc.) can be added to the nodes using CSS.

[0048] Figure 4 A schematic diagram illustrating the switching of learning path topics according to some embodiments of this disclosure is shown. For example... Figure 4As shown, in the initial state 402 of the visualization interface, a recommended learning path (including front-end courses such as HTML & CSS basics and JavaScript programming) is displayed for the target skill "front-end development". The user can enter a search term (e.g., "Java back-end development") in the search bar and confirm the submission. The system responds to this search operation, and in the updated interface state 404, the target skill is switched to "Java back-end development", and the corresponding learning path (including Java back-end development courses such as Java basics and JavaWeb basics) is displayed. The position and format of the search bar can be arbitrarily set on the visualization interface, and this disclosure does not impose any restrictions on this. In some embodiments, the user-input search term can be converted into structured input that the model can process. In some embodiments, upon receiving the user-submitted search term, the system first checks if a learning path matching the search term exists in the cache; if so, it returns directly. In some embodiments, the model can regenerate the corresponding learning path based on the user-submitted search term.

[0049] Figure 5 This is a schematic diagram illustrating the process of expanding a details page according to some embodiments of this disclosure. For example... Figure 5 As shown, in the initial state 502 of the visualization interface, the user clicks on a specific node (e.g., the "JavaScript Programming" node). After the system responds to this action, the updated interface state 504 displays detailed information about the node. In some embodiments, the detailed information may include: links to multiple recommended resources (such as tutorial documents and video courses), suggested study time, a list of prerequisite knowledge (such as "HTML Basics"), personalized learning suggestions, etc. In some embodiments, a scrollbar may be added when the detailed information is lengthy. In some embodiments, after detecting the user's click action, it may be determined whether the node is in an expanded state to avoid repeatedly expanding the same node.

[0050] Figure 6 The illustration shows a schematic diagram of adding a new node according to some embodiments of the present disclosure. For example... Figure 6 As shown, when a user clicks "Add New Node" in the initial state 602 of the visualization interface, the system responds and generates a new node editing card, which is displayed in the updated interface state 604. The user can enter information such as the node title, description, suggested learning time, and recommended learning resources in this card. After clicking the "Confirm Add" button, the new node is added to the visualization interface of the learning path. In some embodiments, the model can determine the insertion order of the new node in the learning path based on its knowledge content and the knowledge logic of the existing path (such as progressive relationships and associative relationships). In other embodiments, the model can automatically supplement detailed information (such as typical examples, recommended learning time, etc.) for the knowledge points or learning stage of the new node.

[0051] The above methods enable direct interaction between users and the learning path, such as personalizing the learning plan by dragging and reorganizing nodes, thus improving the user experience.

[0052] Figure 7 The illustration shows a flowchart illustrating the learning progress according to some embodiments of the present disclosure. For example... Figure 7 In example method 700, at box 702, the percentage of nodes with a "completed" status among all nodes is determined. For example, this can be obtained by dividing the number of nodes with a "completed" status by the total number of nodes.

[0053] At box 704, learning progress is determined based on the percentage. In some embodiments, the percentage of completed nodes can be directly used as an indicator to evaluate the user's learning progress (e.g., completing 3 out of 6 nodes represents 50% progress). In other embodiments, a recommended learning time for each node can be preset. The calculation of the recommended learning time can be based on historical data, such as the average time for similar users to complete the node, for example, the average time for multiple users to complete "HTML Basics" is 40 hours; it can also be adjusted based on the current user's actual situation, such as calculating the average time for beginners and one-third of the average time for users in the review stage. In some embodiments, the recommended learning time for nodes can be evaluated using a model. After obtaining the recommended learning time for each node, the user's learning progress can be evaluated by calculating the sum of the recommended learning times for all nodes and the sum of the recommended learning times for completed nodes.

[0054] In some embodiments, the model can generate corresponding learning suggestions for users based on their learning progress. For example: If you have completed one basic node, it is recommended to prioritize learning "JavaScript Programming" (you have completed the prerequisite course "HTML Basics"). This node contains 90 videos (50 hours in total) and 200 practice questions (estimated to take 10 hours).

[0055] At box 706, in response to a user triggering an area to modify the node status (such as a node status marker button, checkbox, slider, etc.), the corresponding node status is changed to "Completed". Each node includes at least two states: Completed and Incomplete. In some embodiments, when a user triggers an area to modify the "Completed" node status, the corresponding node status can be remarked as Incomplete. At box 708, based on the modified node status, the proportion of completed nodes among all nodes is recalculated, and the learning progress is updated accordingly.

[0056] At box 710, the learning progress is displayed on the visualization interface. The learning progress can be displayed in any way, such as a progress bar, a pie chart, percentage data, or text description; this disclosure does not impose any restrictions on this.

[0057] Figure 8 The illustration shows a schematic diagram illustrating the learning progress according to some embodiments of the present disclosure. For example... Figure 8 As shown, in the initial state 802 of the visualization interface, the user's learning progress is displayed (e.g., 0 / 6 completed). In some embodiments, personalized suggestions (e.g., suggesting learning "HTML / CSS basics, estimated to take 40 hours to complete") and time planning information can also be displayed based on the learning progress. When the user clicks on the status marker of a specific node (e.g., the hollow circle for the incomplete state in the figure), the status of the corresponding node will change in the updated interface state 804. For example, adding a strikethrough, adding the word "completed", changing the background color of the node, or adding a symbol marker in a specific position. In some embodiments, a "marked" pop-up window can be displayed to provide feedback to the user on the result of this marking.

[0058] Accordingly, the system calculates the user's current learning progress in real time based on the updated node status and updates the content displayed on the visualization interface (e.g., the progress bar changes from 0% to 17%, and the number of completed tasks changes from 0 / 6 to 1 / 6). Furthermore, the system can regenerate targeted personalized suggestions based on the updated learning progress (e.g., after completing "HTML / CSS Basics," it suggests learning "JavaScript Programming," estimated to take 60 hours, or approximately 30 days based on an average of 2 hours per day). In some embodiments, the current learning objective, learning progress, and node information (such as node status, title, estimated duration, difficulty, dependencies, etc.) can be provided to the model, which then generates the corresponding learning progress.

[0059] The above methods enable real-time updates to node status and progress bars, providing users with a clear and intuitive visualization of their learning progress. Furthermore, personalized learning suggestions and path adjustments are generated based on the user's learning progress and behavior. This visualized progress tracking and real-time feedback enhances learning motivation, improves learning efficiency, and increases knowledge absorption.

[0060] Figure 9 The illustration shows a schematic block diagram of an apparatus for demonstrating a learning path according to some embodiments of the present disclosure. Figure 9 As shown, the device 900 includes a learning path generation module 902, configured to generate a learning path based on input information using a model, the learning path including at least one node; a display module 904, configured to display the learning path on a visualization interface; and an interaction module 906, configured to adjust the display of the learning path on the visualization interface in response to user interaction.

[0061] In some embodiments, the learning path generation module 902 includes: a knowledge point generation module configured to generate knowledge points based on input information through a model; a dependency and recommended learning order determination module configured to determine the dependency relationships and recommended learning order between knowledge points through a model; and a path generation module configured to generate a learning path based on knowledge points, dependency relationships, and recommended learning order.

[0062] In some embodiments, the interaction module 906 includes a detailed information display module, configured to expand the detailed information of a node in response to a user clicking on the node.

[0063] In some embodiments, the details include at least one of a summary of the knowledge point, recommended resource links, and suggested study time.

[0064] In some embodiments, the learning path includes a learning progress.

[0065] In some embodiments, the apparatus 900 further includes: a completed node determination module, configured to determine the proportion of nodes with a completed status in at least one node; a learning progress statistics module, configured to determine the learning progress based on the proportion; and a learning progress display module, configured to display the learning progress on a visual interface.

[0066] In some embodiments, the device 900 further includes a learning suggestion generation module, configured to generate corresponding learning suggestions based on the learning progress.

[0067] In some embodiments, the interaction module 906 includes: a node state modification module, configured to mark the node state as completed in response to a user clicking on an area that triggers the modification of the node state; and a learning progress update module, configured to update the learning progress based on the node state.

[0068] In some embodiments, the interaction module 906 includes a drag-and-drop operation response module configured to adjust the order of nodes in response to a user's drag-and-drop operation.

[0069] In some embodiments, the interaction module 906 includes a search module configured to display the learning path corresponding to the search term on a visual interface in response to a user submitting a search term through the search bar.

[0070] In some embodiments, the input information includes at least one of target skills, knowledge domains, and learner skill levels.

[0071] Figure 10 A schematic block diagram of an example device 1000 that can be used to implement embodiments of the present disclosure is shown. (For execution) Figure 2The device described in the figure can be implemented using device 1000. As shown, device 1000 includes a central processing unit (CPU) 1001, which can perform various appropriate actions and processes according to computer program instructions stored in read-only memory (ROM) 1002 or loaded from storage unit 1008 into random access memory (RAM) 1003. Various programs and data required for the operation of device 1000 can also be stored in RAM 1003. CPU 1001, ROM 1002, and RAM 1003 are interconnected via bus 1004. Input / output (I / O) interface 1005 is also connected to bus 1004.

[0072] Multiple components in device 1000 are connected to I / O interface 1005, including: input unit 1006, such as keyboard, mouse, etc.; output unit 1007, such as various types of monitors, speakers, etc.; storage unit 1008, such as disk, optical disk, etc.; and communication unit 1009, such as network card, modem, wireless transceiver, etc. Communication unit 1009 allows device 1000 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0073] The various processes and procedures described above, such as methods 200 and 700, can be executed by processing unit 1001. For example, in some embodiments, methods 200 and 700 can be implemented as computer software programs tangibly contained in a machine-readable medium, such as storage unit 1008. In some embodiments, part or all of the computer program can be loaded and / or installed on device 1000 via ROM 1002 and / or communication unit 1009. When the computer program is loaded into RAM 1003 and executed by CPU 1001, one or more actions of the example methods 200 and 700 described above can be performed.

[0074] This disclosure can be a method, apparatus, system, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for performing various aspects of this disclosure.

[0075] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0076] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0077] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0078] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0079] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processing unit of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner. Thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0080] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0081] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0082] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, and are not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical applications, or technical improvements to the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for demonstrating a learning path, comprising: The model generates a learning path based on the input information, and the learning path includes at least one node. The learning path is displayed in a visual interface; as well as In response to user interaction, the display of the learning path on the visualization interface is adjusted.

2. The method according to claim 1, wherein generating the learning path comprises: The model generates knowledge points based on the input information. The model is used to determine the dependencies between the knowledge points and to recommend a learning order. as well as The learning path is generated based on the knowledge points, the dependencies, and the recommended learning order.

3. The method according to claim 1, wherein adjusting the display of the learning path on the visualization interface in response to user interaction includes: In response to the user clicking the node, expand the node's detailed information.

4. The method according to claim 3, wherein the detailed information includes at least one of the following: a summary of the knowledge points, recommended resource links, and suggested study time.

5. The method according to claim 1, wherein the learning path includes a learning progress.

6. The method according to claim 5, further comprising: Determine the percentage of nodes whose status is "completed" among the at least one node; Based on the aforementioned percentage, the learning progress is determined; as well as The learning progress is displayed on the visualization interface.

7. The method according to claim 5, further comprising: Based on the learning progress, corresponding learning suggestions are generated.

8. The method of claim 5, wherein adjusting the display of the learning path on the visualization interface in response to a user's interactive operation comprises: In response to the user clicking on an area that triggers modification of the node's state, the node's state is marked as completed; as well as The learning progress is updated based on the state of the node.

9. The method of claim 1, wherein adjusting the display of the learning path on the visualization interface in response to a user interaction includes: In response to the user's drag-and-drop operation, the order of the nodes is adjusted.

10. The method of claim 1, wherein the learning path includes a search bar, and adjusting the display of the learning path on the visualization interface in response to user interaction includes: In response to the user submitting a search term through the search bar, the learning path corresponding to the search term is displayed on the visualization interface.

11. The method of claim 1, wherein the input information includes at least one of target skills, knowledge domains, and learner skill levels.

12. An apparatus for displaying a learning path, comprising: The learning path generation module is configured to generate a learning path based on input information using a model, the learning path including at least one node; The display module is configured to display the learning path on a visual interface; as well as The interaction module is configured to respond to user interaction operations and adjust the display of the learning path on the visualization interface.

13. An electronic device, comprising: At least one processor; as well as A storage device for storing at least one program, which, when executed by the at least one processor, causes the at least one processor to implement the method according to any one of claims 1-11.

14. A computer-readable storage medium having a computer program stored thereon, the computer program implementing the method according to any one of claims 1-11 when executed by a processor.

15. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1-11.

Images