Data processing method and device

Abstract

The embodiment of the invention provides a data processing method and device.The data processing method comprises the steps that interaction information corresponding to a course node is determined in response to a node ending instruction of the course node associated with a target course, and the interaction information is displayed on an interaction page corresponding to the target course; generating an initial interaction page corresponding to the interaction information, receiving an interaction operation request of a user for the initial interaction page, and analyzing the interaction operation request to obtain interaction operation data; and processing the interaction operation data by using a large language model to obtain interaction display data, and updating the initial interaction page to a target interaction page based on the interaction display data.

Description

Technical Field

[0001] The embodiments in this specification relate to the field of data processing technology, and in particular to data processing methods and apparatus. Background Technology

[0002] In online education and intelligent teaching systems, the delivery of course content is closely related to the consolidation of learning outcomes, and effective interactive elements are key to improving user engagement and knowledge internalization. Existing teaching platforms typically provide static exercises or fixed Q&As after each course segment, resulting in limited interaction, delayed feedback, and difficulty in dynamically adjusting to users' real-time understanding, thus limiting the effectiveness of personalized teaching. Therefore, a data processing method is urgently needed to address these issues. Summary of the Invention

[0003] In view of the above, embodiments of this specification provide a data processing method. One or more embodiments of this specification also relate to a data processing apparatus, a computing device, a computer-readable storage medium, and a computer program product, to address the technical deficiencies existing in the prior art.

[0004] According to a first aspect of the embodiments of this specification, a data processing method is provided, comprising: In response to the node end instruction of the course node associated with the target course, the interactive information corresponding to the course node is determined, and the interactive information is displayed on the interactive page corresponding to the target course; Generate an initial interactive page corresponding to the interactive information, receive user interaction operation requests for the initial interactive page, parse the interaction operation requests, and obtain interactive operation data; The interactive operation data is processed using a large language model to obtain interactive display data, and the initial interactive page is updated to the target interactive page based on the interactive display data.

[0005] Optionally, before determining the interactive information corresponding to the course node in response to the node end instruction of the associated target course node, the method further includes: Determine the target course, and select the course node from the set of course nodes corresponding to the target course; In response to the selection operation of the course node, the course resources corresponding to the course node are played.

[0006] Optionally, generating the initial interactive page corresponding to the interactive information includes: If the interactive information is an identification connection code, an interactive connection page is displayed in response to the identification operation of the identification connection code, and the interactive connection page is used as the initial interactive page corresponding to the interactive information.

[0007] Optionally, generating the initial interactive page corresponding to the interactive information includes: If the interactive information is a course group number, enter the course group number on the interactive access page corresponding to the course node to obtain the course interactive page, and use the course interactive page as the initial interactive page corresponding to the interactive information.

[0008] Optionally, receiving the user's interactive operation request for the initial interactive page includes: In response to the input command submitted by the user for the initial interactive page, a set of input types is displayed to the user; Receive the interactive operation request submitted by the user for the target input type selected in the set of input types.

[0009] Optionally, after parsing the interactive operation request to obtain the interactive operation data, the process further includes: The interactive operation data is stored in the data queue corresponding to the large language model, and the restriction information of the large language model is detected. If the detection is deemed successful based on the detection results, the step of processing the interactive operation data using a large language model to obtain interactive display data is executed.

[0010] Optionally, after parsing the interactive operation request to obtain the interactive operation data, the process further includes: Based on the interactive operation data, query the set of interactive pages; If, based on the query results, a matching interactive page is determined in the set of interactive pages to be displayed that matches the interactive operation data, then the matching interactive page to be displayed is taken as the target interactive page.

[0011] Optionally, after updating the initial interactive page to the target interactive page based on the interactive display data, the method further includes: The set of course nodes corresponding to the target course is detected based on the course nodes; If a target course node matching the course node is determined in the set of course nodes based on the detection results, the target course information corresponding to the target course node is displayed.

[0012] According to a second aspect of the embodiments of this specification, a data processing apparatus is provided, comprising: The determination module is configured to determine the interactive information corresponding to the course node in response to the node end instruction of the course node associated with the target course, and to display the interactive information on the interactive page corresponding to the target course. The receiving module is configured to generate an initial interactive page corresponding to the interactive information, receive user interaction operation requests for the initial interactive page, parse the interaction operation requests, and obtain interactive operation data. The update module is configured to process the interactive operation data using a large language model to obtain interactive display data, and update the initial interactive page to the target interactive page based on the interactive display data.

[0013] According to a third aspect of the embodiments of this specification, a computing device is provided, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the above-described data processing method.

[0014] According to a fourth aspect of the embodiments of this specification, a computer-readable storage medium is provided that stores computer-executable instructions, which, when executed by a processor, implement the steps of the data processing method described above.

[0015] According to a fifth aspect of the embodiments of this specification, a computer program product is provided, including a computer program or instructions that, when executed by a processor, implement the steps of the above-described data processing method.

[0016] This specification provides a data processing method in one embodiment that, in response to a node termination instruction associated with a target course node, determines the interactive information corresponding to the course node and displays the interactive information on the interactive page corresponding to the target course. This ensures that interactive information is provided to the user after the course node ends, allowing the user to consolidate the course content based on the interactive information and improve teaching quality. An initial interactive page corresponding to the interactive information is generated, and user interaction operation requests for the initial interactive page are received. The interaction operation requests are parsed to obtain interactive operation data. The interactive operation data is processed using a large language model to obtain interactive display data, and the initial interactive page is updated to the target interactive page based on the interactive display data. This improves the user's interactive experience for the target course, enriches teaching methods, and enables personalized teaching for users. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a data processing method provided in one embodiment of this specification; Figure 2 This is a schematic diagram of a large model detection method provided in one embodiment of this specification for a data processing method; Figure 3 This is a schematic diagram illustrating the generation of an HTML page for a data processing method provided in one embodiment of this specification; Figure 4 This is an interactive schematic diagram of a data processing method provided in one embodiment of this specification; Figure 5 This is a schematic diagram of the structure of a data processing apparatus provided in one embodiment of this specification; Figure 6 This is a structural block diagram of a computing device provided in one embodiment of this specification. Detailed Implementation

[0018] Many specific details are set forth in the following description to provide a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar extensions without departing from the spirit of this specification. Therefore, this specification is not limited to the specific implementations disclosed below.

[0019] The terminology used in one or more embodiments of this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of this specification. The singular forms “a,” “described,” and “the” as used in one or more embodiments of this specification and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0020] It should be understood that although the terms first, second, etc., may be used to describe various information in one or more embodiments of this specification, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first may also be referred to as second without departing from the scope of one or more embodiments of this specification, and similarly, second may also be referred to as first. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to a determination."

[0021] Furthermore, it should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties. Moreover, the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0022] First, the terms and concepts used in one or more embodiments of this specification will be explained.

[0023] Artificial Intelligence Course: A foundational course designed for students at all levels, from elementary to university, aiming to systematically introduce the core technologies and fundamental principles of artificial intelligence, including but not limited to supervised learning, unsupervised learning, large-scale models, computer vision, and speech recognition. This course combines theoretical explanations with practical examples to help students understand the basic concepts, development history, and simple applications of artificial intelligence in real life. To enhance learning effectiveness and depth of understanding, the course design incorporates interactive elements such as hands-on experiments, case studies, and group discussions, enabling students to experience the practical applications of artificial intelligence technology, stimulating their interest in learning, and promoting knowledge absorption and transfer.

[0024] Interactive AI Course: To help students gain a deeper understanding of the AI ​​course content, the course includes a wealth of interactive experiences. For example, students can personally experience the working process of a speech recognition system and see how AI converts speech into text; they can learn about the practical applications of natural language processing by conversing with large models; and they can try using generative models to generate images, intuitively experiencing the innovative capabilities of AI in areas such as image creation. These interactive experiences not only stimulate students' interest in learning but also allow them to deepen their understanding of the principles and applications of AI technology through hands-on practice, thereby better mastering the course knowledge.

[0025] Interactive input in the course refers to the information provided by the user to achieve effective interaction with the system during the operation and experience of the artificial intelligence model (such as large model dialogue, image generation, video generation, etc.). This input format is not limited to text input, voice input, photo upload, etc., and aims to provide the artificial intelligence system with the necessary data or instructions so that the artificial intelligence model can understand the user's needs and make corresponding intelligent responses.

[0026] Large Language Model (LLM): A deep learning-based Natural Language Processing (NLP) model capable of understanding, generating, and manipulating human language. It learns the statistical patterns, semantic structures, contextual relationships, and world knowledge of language by being trained on massive amounts of text data, thus possessing powerful language understanding and generation capabilities.

[0027] QR code (Quick Response Code): A two-dimensional barcode. Unlike traditional one-dimensional barcodes (which can only store data horizontally), QR codes store information in both horizontal and vertical directions, thus accommodating more data and supporting fast scanning and automatic recognition.

[0028] This specification provides a data processing method, and also relates to a data processing apparatus, a computing device, a computer-readable storage medium, and a computer program product, which will be described in detail in the following embodiments.

[0029] See Figure 1 , Figure 1 A flowchart of a data processing method according to an embodiment of this specification is shown, which specifically includes the following steps.

[0030] Step 102: In response to the node end instruction of the course node associated with the target course, determine the interactive information corresponding to the course node, and display the interactive information on the interactive page corresponding to the target course.

[0031] Specifically, the target course can be a student-oriented course within a specific teaching field. The teaching process of the target course includes teacher explanation and practical operation. The practical operation of the target course requires mobile devices such as smartphones, computers, and tablets; that is, mobile devices. The target course can be an artificial intelligence (AI) course, and course nodes can be teaching units, stages, or segments of the AI ​​course, representing one or more knowledge points within the target course. The node completion instruction of a course node indicates the completion of the corresponding lecture-based teaching content. The lecture content of the course node can be instructional videos or teacher explanations. Interactive information is used to initiate the interactive experience corresponding to the course node, i.e., interactive practice. The forms of interactive practice include, but are not limited to, mini-games, mini-experiments, and other practical content, specifically covering cutting-edge AI technologies such as speech recognition, natural language processing (NLP), large-scale model dialogue, and image generation. The interactive page corresponding to the target course can be a page displayed after the course node ends, used to display interactive information to users (teachers and students). Interactive information provides users with access interfaces for interactive practice and can take various forms such as URL links, identifiable codes (QR codes), and access commands.

[0032] Based on this, the course nodes corresponding to the target course are taught to students through teacher lectures or video playback. Once the teaching content corresponding to the course node is completed, a node end instruction is generated. In response to the node end instruction of the course node associated with the target course, the interactive information corresponding to the course node is determined and displayed on the interactive page corresponding to the target course, so that users (students and / or teachers) can carry out interactive practices corresponding to the course node based on the interactive information.

[0033] Furthermore, considering that a course node can be one of multiple candidate course nodes corresponding to the target course, and each course node corresponds to different knowledge points, in a teaching scenario, users (students or teachers) can select a course node from the set of course nodes corresponding to the target course according to their actual teaching / learning needs. The specific implementation is as follows: Determine the target course and select the course node from the set of course nodes corresponding to the target course; in response to the selection operation of the course node, play the course resources corresponding to the course node.

[0034] Specifically, the set of course nodes corresponding to the target course contains multiple candidate course nodes, which can be sorted according to the order of the target course nodes. Each course node corresponds to at least one knowledge point. Selecting a course node can be done through touch on the element corresponding to the course node on the page displaying the course node set. Alternatively, course nodes can be selected via voice input, such as playing a course node. The course resources corresponding to each course node include, but are not limited to, course explanation videos, course PPTs, course documents, and other resources that can be used for teaching students.

[0035] Based on this, the target course and the set of course nodes corresponding to the target course are determined. The system receives the user's selection instruction for the target course from the course nodes, selects a course node from the set of course nodes corresponding to the target course in response to the selection instruction, and plays the course resources corresponding to the course node in response to the selection operation.

[0036] For example, if the target course is an artificial intelligence course, the course node set contains multiple candidate course nodes stored sequentially according to the teaching plan. Users (students / teachers) can select a course node from the candidate nodes in the set based on their actual teaching or learning needs. The selected course node will then play the corresponding course resources on the user's terminal (classroom screen, student PC).

[0037] In summary, in response to the selection of a course node, the corresponding course resources are played, enabling flexible selection of course nodes from the target course to meet students' phased learning needs.

[0038] Step 104: Generate the initial interactive page corresponding to the interactive information, and receive the user's interactive operation request for the initial interactive page, parse the interactive operation request, and obtain interactive operation data.

[0039] Specifically, after the node termination instruction of the course node in response to the associated target course determines the interactive information corresponding to the course node and displays the interactive information on the interactive page corresponding to the target course, an initial interactive page corresponding to the interactive information can be generated. The system then receives user interaction operation requests for the initial interactive page, parses these requests, and obtains the interactive operation data. The initial interactive page can be a page displayed to the user, showcasing selectable data input modes. The interactive operation request is the computer instruction submitted by the user for the data to be processed entered in the data input mode, used to process the data. The interactive operation data obtained by parsing the interactive operation request includes the data to be processed.

[0040] Based on this, after determining the interactive information corresponding to the course node in response to the node end instruction of the associated target course, and displaying the interactive information on the interactive page corresponding to the target course, an initial interactive page corresponding to the interactive information is generated. The initial interactive page displays the data input mode, informing the user to select a data input model. Once the user selects the target data input mode and inputs the data to be processed, an interactive operation request is submitted. The system receives the user's interactive operation request for the initial interactive page, parses the request, and obtains the interactive operation data containing the data to be processed. The data types of the interactive operation data include, but are not limited to, text, voice, images, and video. This interactive operation data constitutes the course interactive input.

[0041] Furthermore, the interactive information can be in the form of a connection code or other forms. When the interactive information is in the form of a connection code, the initial interactive page can include the connection code, as specifically implemented below: If the interactive information is an identification connection code, an interactive connection page is displayed in response to the identification operation of the identification connection code, and the interactive connection page is used as the initial interactive page corresponding to the interactive information.

[0042] Specifically, the identification link can be a QR code, a 2D barcode, or a machine-readable identifier, and it supports fast scanning and automatic recognition. The identification link can encode various types of data, including URLs, text, phone numbers, SMS messages, email addresses, and Wi-Fi configurations. The interactive connection page can be an application page or a mini-program page. The interactive connection page displays the user's selectable data input types.

[0043] Therefore, when the interactive information is a connection code, an interactive connection page is displayed in response to the recognition operation of the connection code. The recognition operation can be performed by using a mobile device to open the scanning function and scan the connection code. The interactive connection page can then be used as the initial interactive page corresponding to the interactive information for subsequent data input.

[0044] Using the previous example, if the user selects the classroom interaction mode, a QR code can be displayed on the classroom's large screen. The user (student / teacher) can scan the QR code with their terminal device to open the mini-program APP and display the initial interactive page, which includes input type selection functionality.

[0045] In summary, in response to the identification operation of the identification link code, an interactive link page is displayed, and the interactive link page is used as the initial interactive page corresponding to the interactive information. By identifying the identification link code, the initial interactive page is obtained, and subsequent course interactions are carried out, thereby improving the efficiency of course interaction access.

[0046] Furthermore, the interactive information can be in the form of a course group number or other formats. If the interactive information is in the form of a course group number, an initial interactive page can be generated based on that course group number, as specifically implemented below: If the interactive information is a course group number, enter the course group number on the interactive access page corresponding to the course node to obtain the course interactive page, and use the course interactive page as the initial interactive page corresponding to the interactive information.

[0047] Specifically, the course group number can be the course number corresponding to the course node. By recognizing the course number, an initial interactive page can be generated. The course group number can also be the classroom number. By recognizing the classroom number, the course interactive page, i.e., the initial interactive page, can be displayed. The course group number is used to bind the course interactive page. By entering the course group number on the interactive access page corresponding to the course node, page redirection can be achieved. The course group number can be created by the teacher in the classroom and provided to the students in the classroom. Students can then enter the course group number using their mobile devices to open the course interactive page.

[0048] Based on this, when the interactive information is a course group number, the course group number is entered into the interactive access page corresponding to the course node to obtain the course interactive page. The course group number is created by the teacher in the classroom and provided to the students. Students then enter the course group number using their mobile devices to open the course interactive page. This course interactive page serves as the initial interactive page corresponding to the interactive information, allowing users to engage in interactive practices related to the knowledge points corresponding to the course nodes.

[0049] Continuing with the previous example, in the teaching scenario of an artificial intelligence course, after the teacher has completed the instruction of the knowledge points corresponding to the course nodes, they can define a course group number, create a virtual classroom based on the course group number, and display the course group number on a large screen. Students can use their own mobile devices to open an interactive webpage, enter the course group number on the interactive webpage, and enter the virtual classroom to access the initial interactive page. Subsequently, students can select the data input type on the initial interactive page and input the data that needs to be processed.

[0050] In summary, by entering the course group number on the interactive access page corresponding to the course node, the course interaction page is obtained, and the course interaction page is used as the initial interaction page corresponding to the interactive information. Course interaction is carried out in the form of course groups, which improves the diversity of course interaction methods.

[0051] Furthermore, considering that users have different data input needs for interactive experiments, in order to facilitate users' selection of input types, a set of input types containing multiple data input types can be displayed for users to choose from. The specific implementation is as follows: In response to an input instruction submitted by the user for the initial interactive page, a set of input types is displayed to the user; the user submits an interactive operation request for the target input type selected in the set of input types.

[0052] Specifically, input commands can be commands submitted by users when they have a data input need. These commands are used to obtain an input interface for inputting the data to be processed. Input commands can be generated and submitted by the user through touch on interactive elements in the initial interactive page, or they can be triggered by the user through voice input. The input type set includes various data input types, including but not limited to voice input, text input, image input, file input, and video input. Interactive operation requests are input requests triggered after the user has selected an input type as the target input type. These requests are used to obtain a data input interface for data input, which can be keyboard input, voice input, or image, file, or video uploads.

[0053] Based on this, in response to the user's input command submitted on the initial interactive page, a set of input types, including voice input, text input, image input, file input, and video input, is displayed to the user. Upon receiving an interactive operation request from the user for the target input type selected from the set, it indicates that the user's selected target input type will be the type / method of data input for this instance. A data input interface corresponding to the target input type can then be provided to the user, activating the microphone and keyboard, as well as providing a data upload control. Users can then upload data of the corresponding type using the data upload control.

[0054] Following the previous example, in response to the user's input command submitted on the initial interactive page, a set of input types, including voice input, text input, image input, file input, and video input, is displayed to the user. After the user selects "image type" as the target input type, an image input control is displayed. The user can upload an image through the input control, or after confirming that the image type is the target input type, the camera is activated for the user to take and upload an image.

[0055] In summary, the system receives interactive operation requests from users targeting a specific input type selected from the input type set, thus clarifying the user's input type. It provides users with multiple input types, improving the flexibility of user content input.

[0056] Furthermore, considering that interactive operation requests submitted to the large language model can be concurrent, and the processing of interactive operation data by the large language model depends on processing resources, the limitation information of the large language model can be checked before processing the interactive operation data to determine whether the processing of interactive operation requests exceeds the rate limit of the large language model. The specific implementation is as follows: The interactive operation data is stored in the data queue corresponding to the large language model, and the restriction information of the large language model is detected. If the detection is successful based on the detection result, the step of processing the interactive operation data using the large language model to obtain interactive display data is executed.

[0057] Specifically, the data queue refers to a cache queue used to store interactive operation data submitted to the large language model. Any interactive operation data submitted by a user must be stored in the data queue before being input into the large language model for processing. Detecting the large language model's limitation information is equivalent to detecting rate limiting. The limitation information is a pre-configured traffic limit threshold for the large language model, used to limit the amount of data input to it. The detection result is a comparison between the amount of data cached in the data queue and the limitation information. If the amount of data cached in the data queue is less than the limit threshold corresponding to the limitation information, the detection passes.

[0058] Based on this, interactive operation data is stored in a data queue corresponding to the large language model. The constraint information of the large language model is then checked, and the amount of data cached in the data queue is compared with the constraint information. If the check passes, it means that the amount of data cached in the data queue is less than the constraint threshold. The large language model can then be used to process the interactive operation data to obtain interactive display data. Alternatively, the interactive operation data can be sent to an inference service, which will process the data to obtain multimodal content and return it to the user.

[0059] Continuing with the previous example, such as Figure 2 As shown, the frontend sends an interaction request to the server, waiting for a session ID. The server receives the interaction request, creates a session ID, closes the current request, and returns the session ID to the frontend. The frontend establishes a long connection and waits for the session to end. After receiving the user-submitted information (interactive operation data), the server packages the information and caches it in the data queue. It checks for large model rate limiting. If the rate limit is exceeded, the information is cached again in the data queue, awaiting the next consumption. That is, if the current data processing is not completed, the large model rate limiting is checked again. If the large model rate limit is not exceeded, the information is extracted from the data queue and sent to the inference service. The inference service performs inference, generates multimodal content, and returns the multimodal content to the frontend. On the frontend, the multimodal content is rendered as bubbles and displayed on the large screen.

[0060] In summary, after confirming that the detection has passed based on the test results, the interactive operation data is processed using a large language model to obtain interactive display data, ensuring that interactive operation requests can be executed smoothly.

[0061] Furthermore, considering that the processing results obtained from processing interactive operation data may exist in the interactive page set, after determining the interactive operation data, we can first query the interactive page operation set and determine the interactive page to be displayed that matches the interactive operation data, thereby reducing resource consumption. The specific implementation is as follows: Based on the interactive operation data, query the set of interactive pages; if, according to the query results, an interactive page to be displayed is determined in the set of interactive pages that matches the interactive operation data, the interactive page to be displayed is taken as the target interactive page.

[0062] Specifically, the interactive page collection stores historical interactive pages, which are the HTML pages generated in the past that correspond to historical interaction data. The query result is the result of matching the interactive data with the interactive pages in the interactive page collection. The matching result may be that there is no matching interactive page in the interactive page collection, or it may be that there is a matching interactive page in the interactive page collection.

[0063] Based on this, the system queries an interactive page set containing multiple historical interactive pages. If, based on the query results, a matching interactive page is identified within the interactive page set, this indicates the existence of a matching historical interactive page. This historical interactive page is then designated as the target interactive page. If, based on the query results, no matching interactive page is found in the interactive page set, the interactive data is sent to the inference service, which then uses a large language model to generate an interactive page that matches the interactive data.

[0064] Continuing with the previous example, such as Figure 3 As shown, the frontend sends an interaction request to the server, waiting for a session ID. The server receives the interaction request, creates a session ID, closes the current request, and returns the session ID to the frontend. The frontend establishes a long connection and waits for the session to end. After receiving the information (interactive operation data) submitted by the user, the server packages the information and caches it in the data queue. It checks the cache (the set of interactive pages) for a matching interactive HTML page, that is, it checks if there is an interactive page in the set that matches the interactive operation data. If a matching interactive HTML page exists in the cache, the cached HTML page is returned, and the interactive HTML page is returned to the frontend. The frontend renders the interactive HTML page, and the user can interact with the embedded HTML page locally. If no matching interactive HTML page exists in the cache, the inference service limit is checked. If the inference service exceeds the limit, an error message or limit warning is returned. If the inference service does not exceed the limit, the large model is called to generate the HTML page code corresponding to the interactive operation data. The HTML page code is written to the cache, and the generated HTML page is returned. The generated interactive HTML page is returned to the frontend for rendering and display.

[0065] In summary, once the query results identify the interactive page to be displayed that matches the interactive operation data in the set of interactive pages, the interactive page to be displayed is used as the target interactive page to avoid resource consumption caused by regenerating the target interactive page.

[0066] Step 106: Process the interactive operation data using a large language model to obtain interactive display data, and update the initial interactive page to the target interactive page based on the interactive display data.

[0067] Specifically, on the initial interactive page corresponding to the aforementioned generated interactive information, user interaction requests for the initial interactive page are received. After parsing the interaction requests and obtaining the interaction data, a large language model is used to process the interaction data to obtain interactive display data. Based on this interactive display data, the initial interactive page is updated to the target interactive page. The interactive display data is the processing result obtained through the large language model, which can be the recognition result of the interaction data or the keyword extraction result. The processing methods of the large language model for interactive operation data include, but are not limited to, object detection, image recognition, keyword extraction, and summary generation. The target interactive page is used to display the interactive display data, which can be static text, images, or dynamic data processing processes, such as calculation processes or ticket booking processes.

[0068] Based on this, the system generates the initial interactive page corresponding to the interactive information mentioned above, receives user interaction operation requests for the initial interactive page, parses the interaction operation requests, obtains the interaction operation data, processes the interaction operation data using a large language model, obtains static or dynamic interactive display data, and updates the initial interactive page to the target interactive page based on the interactive display data, displaying the interactive display data on the target interactive page.

[0069] Furthermore, after displaying the interaction data on the target interaction page, it indicates that the interactive practice corresponding to the course node has been completed. To improve the continuity of teaching, the set of course nodes can be checked based on the course nodes to detect whether there are any target course nodes in the set that match the course node and can be continued. The specific implementation is as follows: Based on the course node, the set of course nodes corresponding to the target course is detected; if a target course node matching the course node is determined in the set of course nodes according to the detection result, the target course information corresponding to the target course node is displayed.

[0070] Specifically, target course nodes can be related to course nodes at the knowledge point level. That is, learning the knowledge points corresponding to the target course node depends on the knowledge points corresponding to the course node. The knowledge points corresponding to the course node are basic knowledge points, and the knowledge points corresponding to the target course node are advanced knowledge points corresponding to the basic knowledge points. The target course information corresponding to the target course node is the teaching content. The target course information can be text-based knowledge or audio / video explanation videos of the knowledge points.

[0071] Based on this, the set of course nodes corresponding to the target course is checked to see if there are any course nodes in the set that match the knowledge points corresponding to the course nodes. If a target course node that matches the course node is determined in the set of course nodes based on the detection results, it means that the knowledge point corresponding to the target course node is the advanced knowledge point corresponding to the basic knowledge point of the course node. The target course information corresponding to the target course node is then displayed, and further advanced learning of the target course can continue.

[0072] Using the previous example, if the knowledge point corresponding to the course node is "Overview of Artificial Intelligence", we can perform a check in the course node set to check if there is a target course node corresponding to a knowledge point that needs to be learned after the course node corresponding to the knowledge point "Overview of Artificial Intelligence". Once the target course node corresponding to the knowledge point "Problem Solving and Search Algorithms" is determined, the course information corresponding to the knowledge point "Problem Solving and Search Algorithms", that is, the target course information, can be displayed to the user.

[0073] In summary, by identifying a target course node that matches the target course node in the course node set based on the detection results, the target course information corresponding to the target course node is displayed, thereby improving the continuity of the user's learning of the target course.

[0074] This specification provides a data processing method in one embodiment that, in response to a node termination instruction associated with a target course node, determines the interactive information corresponding to the course node and displays the interactive information on the interactive page corresponding to the target course. This ensures that interactive information is provided to the user after the course node ends, allowing the user to consolidate the course content based on the interactive information and improve teaching quality. An initial interactive page corresponding to the interactive information is generated, and user interaction operation requests for the initial interactive page are received. The interaction operation requests are parsed to obtain interactive operation data. The interactive operation data is processed using a large language model to obtain interactive display data, and the initial interactive page is updated to the target interactive page based on the interactive display data. This improves the user's interactive experience for the target course, enriches teaching methods, and enables personalized teaching for users.

[0075] The following is in conjunction with the appendix Figure 4 Taking the application of the data processing method provided in this specification in artificial intelligence course teaching as an example, the data processing method will be further explained. Among other things, Figure 4 An interactive schematic diagram of a data processing method provided in one embodiment of this specification is shown, specifically including the following contents.

[0076] Artificial intelligence (AI) technology is rapidly developing, and related courses have become an important part of primary, secondary, and high school education. With the emergence of cutting-edge technologies such as large-scale models and generative AI (e.g., text generation, image generation, video generation), the content and teaching methods of AI courses are constantly being updated. However, in actual teaching, the industry generally still uses the traditional "theoretical lectures + centralized experiments" model. That is, teachers explain theoretical knowledge in class using PPTs, blackboards, etc., and students passively receive the knowledge, followed by a unified arrangement of experimental courses in a computer lab for hands-on practice. While this model ensures the systematic and standardized nature of teaching to a certain extent, it also exposes many shortcomings.

[0077] There is a significant disconnect between theoretical instruction and practical application. After learning theoretical knowledge in class, students often have to wait several days or even longer before they can begin experiments, resulting in a weak connection between knowledge points and practical applications, making it difficult for students to form a complete knowledge system. Secondly, the content and format of experimental courses are relatively fixed, and many experimental cases are outdated, failing to cover the latest technologies and applications in the field of artificial intelligence, such as large-scale model dialogue, text generation, and image generation. Students struggle to gain practical experience that keeps pace with industry developments. Furthermore, experimental courses typically use a unified computer lab setup, which, limited by computer lab resources and time constraints, restricts students' hands-on time and provides insufficient practical opportunities, failing to meet personalized and diverse learning needs. Moreover, existing experimental systems are mostly text-based, lacking support for multimodal input such as voice and images, resulting in cumbersome operation processes and low interaction efficiency, further impacting students' learning motivation and practical effectiveness.

[0078] Existing AI curriculum teaching schemes generally suffer from problems such as a disconnect between theory and practice, outdated experimental content, limited practical opportunities, and monotonous interaction methods, making it difficult to meet the current demands of AI education for efficient interaction, real-time experience, and diverse input. Therefore, there is an urgent need for an interactive teaching system for AI courses that can organically combine theoretical instruction with practical operation, support multimodal input, and enhance teaching interactivity and practical efficiency, in order to better adapt to the new trends in AI technology development and improve students' learning interest and practical abilities.

[0079] This specification provides one or more embodiments of a data processing method for teaching artificial intelligence courses. It organically combines theoretical instruction with classroom practice to form an integrated teaching system. Typically, the complete course content is divided into several lessons, and each lesson is further divided into multiple teaching segments based on different knowledge points. Each segment generally consists of two parts: a teaching video and an interactive experience. After watching the video explanation, the system automatically guides students into an interactive experience related to that knowledge point. The interactive experience is closely designed around the video content, and common forms include mini-games and experiments, covering cutting-edge AI technologies such as speech recognition, natural language processing (NLP), large-scale model dialogue, and image generation. In the interactive segments, students can directly experience the practical application effects of AI models through real input and output operations, thereby deepening their understanding and mastery of theoretical knowledge.

[0080] In terms of specific interactive design, the actual needs of different teaching scenarios, such as classrooms and computer labs, have been fully considered. To avoid the cumbersome login and identity verification processes of traditional experimental systems, the teaching system adopts a login-free, quick access method, greatly simplifying the operation process and improving the efficiency of classroom practice. In the classroom setting, teachers can scan a QR code via a mobile app or mini-program to directly input voice or upload photos on their mobile devices, enabling real-time interaction with the system. This approach not only lowers the equipment barrier but also fully utilizes the convenience of the school's own terminals, making interactive experiences possible in large-scale classroom environments. In the computer lab setting, students can quickly enter the virtual classroom by entering an interaction code, keeping pace with the teacher's lectures. Once in the experimental phase, students can choose from various methods, such as keyboard or voice input, to interact with the artificial intelligence model. The system can generate corresponding AI output results in real time based on the student's input and provide feedback to the student, helping them to promptly identify and correct problems in their learning.

[0081] Furthermore, the teaching system adopts an integrated closed-loop model of "lecture-practice-feedback" in its course flow design. Each knowledge point is immediately followed by a practical session, avoiding the separation of theory and practice and enhancing the coherence of knowledge and the immediacy of learning. The content and difficulty of the interactive experiences are also dynamically adjusted according to the course progress and students' levels, ensuring coverage of basic knowledge while introducing the latest artificial intelligence technologies and application cases to meet the learning needs of students at different levels. Some systems also support real-time monitoring and data analysis functions on the teacher's end, allowing teachers to adjust their teaching strategies in a timely manner based on students' interactive performance, achieving personalized teaching and precise tutoring.

[0082] At the technical implementation level, the teaching system mostly adopts a cloud architecture, supporting multi-terminal access and high-concurrency processing, and can meet the stable operation requirements of large-scale classrooms and computer labs. The teaching system also integrates core technologies such as multimodal input recognition, real-time data processing, and AI model invocation, ensuring the smoothness and intelligence of the interactive experience.

[0083] In practical applications, such as in the teaching scenarios of artificial intelligence courses, Figure 4 As shown, the teaching system includes a front-end (screen), user mobile devices, a back-end / large model, and a user PC (personal computer). In practice, after completing one course node of the target course, the interactive experimental phase can begin. Teachers can select the interaction mode through the front-end interface; the interaction mode can be classroom interaction or non-classroom interaction.

[0084] When the classroom interaction mode is selected, this interactive experiment can be completed by the teacher using a provided mobile device, or by students using their own mobile devices. A QR code is displayed on the screen. The teacher / student scans the QR code on the screen using their mobile device (phone, tablet, etc.) to open the mini-program app. After scanning the QR code, the connection is successful. After successful scanning, the user further selects the access type (voice, text, or image). The system determines whether the selected access type is voice. If it is voice, the microphone is activated, the user inputs voice, and the text is uploaded. If it is not voice, the system determines whether it is text. If it is text, the microphone is activated, speech recognition is performed, the voice content is converted into text, and the text is input and uploaded. If it is not text, the system determines whether the user input is an image. If it is an image, the camera is activated or a picture is selected from the album, and the image is input and uploaded. If it is not an image, other content can also be input and uploaded. After the front-end displays the user's uploaded content, it is input into the back-end large model for interaction. The large model outputs the results, which are then displayed on the front-end interface (screen). After completing the current round of dialogue, if the user needs to continue the dialogue, multiple rounds of dialogue input can be continued, displaying the user's next round of dialogue input, sending the user's input back into the large model, outputting new results, and displaying the new results on the terminal to further determine whether to continue the dialogue. If the user no longer wishes to continue the dialogue, the interaction ends.

[0085] When the classroom interaction mode is selected, it means that this interactive experiment can be completed by students via a webpage on their PCs. The teacher creates an interactive classroom through the front-end interface and displays the classroom number on the screen. After opening the interactive webpage, students enter the classroom number to begin the interaction. Students can choose the input type (voice, text, or image). The system checks if the selected input type is text. If it is, the keyboard is activated for input, and the text is submitted. If it is not text, the system checks if it is voice. If it is, the microphone is activated for voice input, and the voice input is submitted. If it is not voice, the system checks if the input is an image. If it is, a local image is selected or the camera is activated to take a picture, which is then submitted. Students can also input other content and upload it. The uploaded content is then fed into the backend big model for interaction. The big model outputs results, which are displayed on the user's PC interface and simultaneously on the front-end, ending the interaction. After completing the current round of dialogue, if the user needs to continue the dialogue, multiple rounds of dialogue input can be continued, displaying the user's next round of dialogue input, sending the user's input back into the large model, outputting new results, and displaying the new results on the terminal to further determine whether to continue the dialogue. If the user no longer wishes to continue the dialogue, the interaction ends.

[0086] The teaching system constructs a real-time interactive teaching scenario through a cyclical mechanism of "displaying user input - showing AI output - continuing dialogue." Teachers can selectively display typical questions and answers synchronously and provide collective explanations for common problems. After completing knowledge transfer or experimental guidance, teachers can end the interactive process through the front end, and the system automatically saves the dialogue record for post-class review. This design, through login-free access, multimodal interaction, and real-time feedback mechanisms, effectively solves the problems of high device dependence and significant interaction latency in traditional AI teaching. It is particularly suitable for teaching scenarios requiring immediate guidance, such as programming practice and model parameter tuning, significantly improving classroom participation and knowledge transfer efficiency.

[0087] Corresponding to the above method embodiments, this specification also provides data processing apparatus embodiments. Figure 5 A schematic diagram of the structure of a data processing apparatus according to one embodiment of this specification is shown. Figure 5 As shown, the device includes: The determination module 502 is configured to determine the interactive information corresponding to the course node in response to the node end instruction of the course node associated with the target course, and to display the interactive information on the interactive page corresponding to the target course. The receiving module 504 is configured to generate an initial interactive page corresponding to the interactive information, receive user interaction operation requests for the initial interactive page, parse the interaction operation requests, and obtain interactive operation data. The update module 506 is configured to process the interactive operation data using a large language model to obtain interactive display data, and update the initial interactive page to the target interactive page based on the interactive display data.

[0088] In an optional embodiment, the determining module 502 is further configured to: Determine the target course, and select the course node from the set of course nodes corresponding to the target course; In response to the selection operation of the course node, the course resources corresponding to the course node are played.

[0089] In an optional embodiment, the receiving module 504 is further configured to: If the interactive information is an identification connection code, an interactive connection page is displayed in response to the identification operation of the identification connection code, and the interactive connection page is used as the initial interactive page corresponding to the interactive information.

[0090] In an optional embodiment, the receiving module 504 is further configured to: If the interactive information is a course group number, enter the course group number on the interactive access page corresponding to the course node to obtain the course interactive page, and use the course interactive page as the initial interactive page corresponding to the interactive information.

[0091] In an optional embodiment, the receiving module 504 is further configured to: In response to the input command submitted by the user for the initial interactive page, a set of input types is displayed to the user; Receive the interactive operation request submitted by the user for the target input type selected in the set of input types.

[0092] In an optional embodiment, the receiving module 504 is further configured to: The interactive operation data is stored in the data queue corresponding to the large language model, and the restriction information of the large language model is detected. If the detection is deemed successful based on the detection results, the step of processing the interactive operation data using a large language model to obtain interactive display data is executed.

[0093] In an optional embodiment, the receiving module 504 is further configured to: Based on the interactive operation data, query the set of interactive pages; If, based on the query results, a matching interactive page is determined in the set of interactive pages to be displayed that matches the interactive operation data, then the matching interactive page to be displayed is taken as the target interactive page.

[0094] In an optional embodiment, the update module 506 is further configured to: The set of course nodes corresponding to the target course is detected based on the course nodes; If a target course node matching the course node is determined in the set of course nodes based on the detection results, the target course information corresponding to the target course node is displayed.

[0095] This specification provides a data processing apparatus in one embodiment that, in response to a node termination instruction associated with a target course node, determines the interactive information corresponding to the course node and displays the interactive information on the interactive page corresponding to the target course. This ensures that interactive information is provided to the user after the course node ends, allowing the user to consolidate the course content based on the interactive information and improve teaching quality. An initial interactive page corresponding to the interactive information is generated, and user interaction operation requests for the initial interactive page are received. The interaction operation requests are parsed to obtain interactive operation data. The interactive operation data is processed using a large language model to obtain interactive display data, and the initial interactive page is updated to the target interactive page based on the interactive display data. This improves the user's interactive experience for the target course, enriches teaching methods, and enables personalized teaching for users.

[0096] The above is an illustrative scheme of a data processing apparatus according to this embodiment. It should be noted that the technical solution of this data processing apparatus and the technical solution of the data processing method described above belong to the same concept. For details not described in detail in the technical solution of the data processing apparatus, please refer to the description of the technical solution of the data processing method described above.

[0097] Figure 6 A structural block diagram of a computing device 600 according to one embodiment of this specification is shown. The components of the computing device 600 include, but are not limited to, a memory 610 and a processor 620. The processor 620 is connected to the memory 610 via a bus 630, and a database 650 is used to store data.

[0098] The computing device 600 also includes an access device 640, which enables the computing device 600 to communicate via one or more networks 660. Examples of these networks include Public Switched Telephone Network (PSTN), Local Area Network (LAN), Wide Area Network (WAN), Personal Area Network (PAN), or combinations of communication networks such as the Internet. The access device 640 may include one or more of any type of wired or wireless network interface (e.g., a network interface card (NIC)), such as an IEEE 802.11 Wireless Local Area Network (WLAN) wireless interface, a Wi-MAX (Worldwide Interoperability for Microwave Access) interface, an Ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a Bluetooth interface, or a Near Field Communication (NFC) interface.

[0099] In one embodiment of this specification, the above-described components of the computing device 600 and Figure 6 Other components, not shown, can also be connected to each other, for example, via a bus. It should be understood that... Figure 6 The block diagram of the computing device shown is for illustrative purposes only and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0100] The computing device 600 can be any type of stationary or mobile computing device, including mobile computers or mobile computing devices (e.g., tablet computers, personal digital assistants, laptop computers, notebook computers, netbooks, etc.), mobile phones (e.g., smartphones), wearable computing devices (e.g., smartwatches, smart glasses, etc.) or other types of mobile devices, or stationary computing devices such as desktop computers or personal computers (PCs). The computing device 600 can also be a mobile or stationary server.

[0101] The processor 620 is configured to execute the following computer-executable instructions, which, when executed by the processor, implement the steps of the above-described data processing method.

[0102] The above is an illustrative scheme of a computing device according to this embodiment. It should be noted that the technical solution of this computing device and the technical solution of the data processing method described above belong to the same concept. For details not described in detail in the technical solution of the computing device, please refer to the description of the technical solution of the data processing method described above.

[0103] An embodiment of this specification also provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the above-described data processing method.

[0104] The above is an illustrative scheme of a computer-readable storage medium according to this embodiment. It should be noted that the technical solution of this storage medium and the technical solution of the data processing method described above belong to the same concept. For details not described in detail in the technical solution of the storage medium, please refer to the description of the technical solution of the data processing method described above.

[0105] An embodiment of this specification also provides a computer program product, including a computer program or instructions that, when executed by a processor, implement the steps of the above-described data processing method.

[0106] The above is an illustrative scheme of a computer program product according to this embodiment. It should be noted that the technical solution of this computer program product and the technical solution of the data processing method described above belong to the same concept. For details not described in detail in the technical solution of the computer program product, please refer to the description of the technical solution of the data processing method described above.

[0107] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0108] The computer instructions include computer program code, which may be in the form of source code, object code, executable file, or certain intermediate forms. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium may be appropriately added or removed according to the requirements of patent practice. For example, in some regions, according to patent practice, computer-readable media may not include electrical carrier signals and telecommunication signals.

[0109] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments in this specification are not limited to the described order of actions, because according to the embodiments in this specification, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the embodiments in this specification.

[0110] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0111] The preferred embodiments disclosed above are merely illustrative of this specification. The optional embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the embodiments described herein. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the embodiments, thereby enabling those skilled in the art to better understand and utilize this specification. This specification is limited only by the claims and their full scope and equivalents.

Claims

1. A data processing method, characterized in that, include: In response to the node end instruction of the course node associated with the target course, the interactive information corresponding to the course node is determined, and the interactive information is displayed on the interactive page corresponding to the target course; Generate an initial interactive page corresponding to the interactive information, receive user interaction operation requests for the initial interactive page, parse the interaction operation requests, and obtain interactive operation data; The interactive operation data is processed using a large language model to obtain interactive display data, and the initial interactive page is updated to the target interactive page based on the interactive display data.

2. The data processing method according to claim 1, characterized in that, Before determining the interactive information corresponding to the course node in response to the node end instruction of the associated target course node, the method further includes: Determine the target course, and select the course node from the set of course nodes corresponding to the target course; In response to the selection operation of the course node, the course resources corresponding to the course node are played.

3. The data processing method according to claim 1, characterized in that, The generation of the initial interactive page corresponding to the interactive information includes: If the interactive information is an identification connection code, an interactive connection page is displayed in response to the identification operation of the identification connection code, and the interactive connection page is used as the initial interactive page corresponding to the interactive information.

4. The data processing method according to claim 1, characterized in that, The generation of the initial interactive page corresponding to the interactive information includes: If the interactive information is a course group number, enter the course group number on the interactive access page corresponding to the course node to obtain the course interactive page, and use the course interactive page as the initial interactive page corresponding to the interactive information.

5. The data processing method according to claim 1, characterized in that, Receiving user interaction requests for the initial interactive page includes: In response to the input command submitted by the user for the initial interactive page, a set of input types is displayed to the user; Receive the interactive operation request submitted by the user for the target input type selected in the set of input types.

6. The data processing method according to claim 1, characterized in that, After parsing the interactive operation request to obtain the interactive operation data, the process further includes: The interactive operation data is stored in the data queue corresponding to the large language model, and the restriction information of the large language model is detected. If the detection is deemed successful based on the detection results, the step of processing the interactive operation data using a large language model to obtain interactive display data is executed.

7. The data processing method according to claim 1, characterized in that, After parsing the interactive operation request to obtain the interactive operation data, the process further includes: Based on the interactive operation data, query the set of interactive pages; If, based on the query results, a matching interactive page is determined in the set of interactive pages to be displayed that matches the interactive operation data, then the matching interactive page to be displayed is taken as the target interactive page.

8. The data processing method according to claim 1, characterized in that, After updating the initial interactive page to the target interactive page based on the interactive display data, the process further includes: The set of course nodes corresponding to the target course is detected based on the course nodes; If a target course node matching the course node is determined in the set of course nodes based on the detection results, the target course information corresponding to the target course node is displayed.

9. A data processing apparatus, characterized in that, include: The determination module is configured to determine the interactive information corresponding to the course node in response to the node end instruction of the course node associated with the target course, and to display the interactive information on the interactive page corresponding to the target course. The receiving module is configured to generate an initial interactive page corresponding to the interactive information, receive user interaction operation requests for the initial interactive page, parse the interaction operation requests, and obtain interactive operation data. The update module is configured to process the interactive operation data using a large language model to obtain interactive display data, and update the initial interactive page to the target interactive page based on the interactive display data.

10. A computing device, characterized in that, include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the data processing method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that, It stores computer-executable instructions that, when executed by a processor, implement the steps of the data processing method according to any one of claims 1 to 8.

12. A computer program product, characterized in that, It includes a computer program or instructions that, when executed by a processor, implement the steps of the data processing method according to any one of claims 1 to 8.

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