Self-adaptive interactive teaching support system and method and storage medium

Abstract

The invention provides a self-adaptive interactive teaching support system and method and a storage medium. The system comprises a teaching content acquisition module for acquiring teaching content generated in a teaching process of a teacher; the intelligent note generation module generates student notes in real time and pushes the notes to the online and offline student terminals; the student interaction module is used for receiving labels, real-time questions and thinking records of students in student notes and personalized queries proposed to an artificial intelligence assistant; the data acquisition and analysis module acquires student behavior data generated by the student interaction module and performs big data analysis; and the teacher feedback module feeds back the analysis result to the teacher in real time. According to the embodiment of the invention, on one hand, learning notes are automatically generated for students through the system, so that learning contents can be recorded in time, and the mastering degree of learning on knowledge points is improved; and on the other hand, the system collects and analyzes feedback data of students in real time, and helps teachers adjust teaching content and progress in real time, so that the teaching effect is improved.

Description

Technical Field

[0001] This application relates to the field of online teaching technology, and in particular to an adaptive interactive teaching support system, method and storage medium. Background Technology

[0002] Remote teaching live streaming systems leverage the geographical advantages of the internet to provide students with the best educational resources. However, during remote teaching live streams, the teaching process typically relies on direct lectures from teachers, lacking student feedback. Especially when students are recording the teacher's lecture content, they may miss important information due to slow recording speed. Furthermore, teachers find it difficult to accurately understand each student's learning status and response in the classroom, relying only on superficial observation. In this traditional model, teachers' adjustments to their teaching plans are often based on limited information and experience, failing to provide real-time personalized guidance, resulting in poor student learning outcomes. Therefore, there is an urgent need for an adaptive interactive teaching support system to solve these technical problems. Summary of the Invention

[0003] This application is made in view of at least one of the aforementioned technical problems existing in the prior art. According to one aspect of this application, an adaptive interactive teaching support system is provided, the system comprising:

[0004] The teaching content acquisition module is used to acquire teaching content generated by teachers during the course of their lectures;

[0005] The intelligent note generation module is used to generate student notes in real time based on the teaching content using artificial intelligence algorithms, and push the notes to online and offline student terminals;

[0006] The student interaction module is used to receive students' annotations, real-time questions, thought records, and personalized queries to the AI ​​assistant in the student notes.

[0007] The data acquisition and analysis module is used to collect student behavior data generated by the student interaction module and perform big data analysis.

[0008] The teacher feedback module is used to provide real-time feedback of the analysis results to teachers, enabling them to dynamically adjust the teaching content and pace based on the real-time analysis results during real-time teaching, thereby achieving adaptive teaching for both online and offline student groups.

[0009] In some embodiments, the teaching content acquisition module is specifically used for:

[0010] Collect audio and video data generated during the teacher's lectures;

[0011] The audio and video data are sent to the cloud server as teaching content for students to download or watch on demand; and / or the audio and video data are pushed to the online and offline student terminals as teaching content.

[0012] In some embodiments, the smart note generation module includes a content recognition module; the content recognition module is used for:

[0013] Receive audio and video data generated during the teacher's lecture;

[0014] Identify the audio data to be processed in the audio and video data;

[0015] The audio data to be processed is subjected to speech recognition, and subtitle data corresponding to the multimedia teaching data to be processed is generated based on the speech recognition results.

[0016] Identify the video data to be processed within the audio and video data;

[0017] Identify text data in the video data to be processed;

[0018] Student notes are generated by combining the subtitle data and the text data;

[0019] The student notes are displayed in the editable area of ​​the display interface on both online and offline student terminals.

[0020] In some embodiments, the smart note generation module further includes a student record module; the student record module is used for:

[0021] Receive learning notes edited by students on the student notes; wherein the learning notes include at least one of the following: markings, annotations, and questions;

[0022] Based on the learning records and the student notes, the final learning notes are generated.

[0023] In some embodiments, the student interaction module includes a question-and-answer module, which is used for:

[0024] During the playback of the teaching content, and at any point after the playback of the teaching content, questions input by the input device are received;

[0025] The question is received through the AI ​​system entry point, and the AI ​​system's response to the question is also received.

[0026] In some embodiments, the student interaction module further includes a summary generation module, which is used to:

[0027] At any time after the teaching content has been played to a preset time or after playback has ended, a course summary of the teaching content sent by the artificial intelligence system is received; wherein the course summary is generated by the artificial intelligence system based on the teaching content.

[0028] In some embodiments, the data acquisition and analysis module is specifically used for:

[0029] Receives video footage of student learning status captured by the image acquisition devices of the online and offline student terminals;

[0030] The image frames in the learning state video are analyzed to extract the student's facial features and body posture features;

[0031] Based on the students' facial features and body posture characteristics, the students' activity level and concentration level were determined;

[0032] The learning state video includes facial emotions and / or body features; the facial emotions include at least joy, anger, confusion, sadness, disgust, fear, and neutrality, and the body posture features include at least lying down, looking down, turning away, raising hands, and standing.

[0033] The target teaching plan includes at least the teaching schedule, teaching content, and teaching speed.

[0034] In some embodiments, the teacher feedback module includes a data statistics module, which is used for:

[0035] Real-time statistics of student class attendance data;

[0036] The analysis results of the student's class attendance data are displayed.

[0037] The student's class attendance data includes at least one of the following: the number of times a student asks a question, changes in student activity levels, and whether a student takes notes.

[0038] Another aspect of this application provides an adaptive interactive teaching support method, the method comprising:

[0039] Obtain the teaching content generated during the teacher's lecture;

[0040] Based on the teaching content, artificial intelligence algorithms are used to generate student notes in real time, and the notes are pushed to online and offline student terminals.

[0041] It can receive students' annotations, real-time questions, reflection records, and personalized queries submitted to the AI ​​assistant in the student notes.

[0042] Collect student behavior data generated by the student interaction module and perform big data analysis;

[0043] The analysis results are fed back to teachers in real time, enabling them to dynamically adjust the teaching content and pace based on the real-time analysis results during teaching, thereby achieving adaptive teaching for both online and offline student groups.

[0044] In another aspect, this application provides a storage medium storing a computer program, which, when run by a processor, causes the processor to execute the adaptive interactive teaching support method described above.

[0045] The adaptive interactive teaching support system of this application embodiment, for student terminals, acquires teaching content generated during teacher instruction and generates student notes in real time based on the teaching content. Students can annotate, ask real-time questions, record their thoughts, and make personalized queries to the AI ​​assistant in these student notes. For teacher terminals, the system can collect student behavior data generated by the student interaction module, perform big data analysis, and provide real-time feedback to the teacher. This allows the teacher to dynamically adjust the teaching content and pace based on the real-time analysis results during real-time teaching, thereby achieving adaptive teaching for both online and offline student groups. This application embodiment, on the one hand, automatically generates learning notes for students, enabling them to record learning content in a timely manner and improve their mastery of knowledge points; on the other hand, the system collects and analyzes student feedback data in real time, helping teachers adjust teaching content and pace in real time to improve teaching effectiveness. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 A schematic block diagram of an adaptive interactive teaching support system according to an embodiment of this application is shown;

[0048] Figure 2 A schematic diagram showing the display interface 60 of an online and offline student terminal according to the first example of this application;

[0049] Figure 3 A schematic diagram showing the display interface 60 of an online and offline student terminal according to the second example of this application;

[0050] Figure 4 A schematic diagram showing the display interface 60 of an online and offline student terminal according to the third example of this application;

[0051] Figure 5 A schematic diagram showing the display interface 60 of an online and offline student terminal according to the fourth example of this application;

[0052] Figure 6 A schematic diagram showing the display interface 70 of a teacher terminal according to the fifth example of this application;

[0053] Figure 7 A schematic diagram showing the display interface 70 of a teacher terminal according to the sixth example of this application;

[0054] Figure 8 A schematic flowchart of an adaptive interactive teaching support method 800 according to an embodiment of this application is shown. Detailed Implementation

[0055] To enable those skilled in the art to better understand the technical solutions of the embodiments of this application, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0056] In traditional teaching models, instruction typically relies on teachers directly lecturing and students manually taking notes. When students are taking notes, they may miss information or important details due to slow writing speed. Simultaneously, teachers find it difficult to accurately understand each student's learning status and responses in the classroom, relying instead on superficial observation. Under this traditional model, teachers' adjustments are often based on limited information and experience, failing to provide real-time, personalized guidance.

[0057] Based on at least one of the aforementioned technical problems, this application provides an adaptive interactive teaching support system. The system includes: a teaching content acquisition module for acquiring teaching content generated by teachers during lectures; an intelligent note generation module for generating student notes in real-time based on the teaching content using artificial intelligence algorithms, and pushing the notes to online and offline student terminals; a student interaction module for receiving student annotations, real-time questions, reflection records, and personalized queries submitted to an AI assistant in the student notes; a data collection and analysis module for collecting student behavior data generated by the student interaction module and performing big data analysis; and a teacher feedback module for providing real-time feedback of the analysis results to teachers, enabling teachers to dynamically adjust teaching content and pace based on the real-time analysis results during real-time teaching, thereby achieving adaptive teaching for online and offline student groups. In this application, on the one hand, the system automatically generates learning notes for students, allowing them to record learning content in a timely manner to improve their mastery of knowledge points; on the other hand, the system collects and analyzes student feedback data in real-time to help teachers adjust teaching content and pace in real-time to improve teaching effectiveness.

[0058] Compared to traditional technologies, this invention combines artificial intelligence and big data analytics, bringing revolutionary changes to traditional teaching models. Through the application of AI, teachers' lectures can be automatically converted into text records, which students can easily annotate, improving learning efficiency and convenience. Simultaneously, the system can monitor students' reactions in class in real time and provide feedback to teachers, enabling them to more accurately understand students' learning status and adjust teaching content accordingly, achieving personalized instruction.

[0059] Figure 1 This diagram illustrates a schematic block diagram of an adaptive interactive teaching support system according to an embodiment of this application; as shown... Figure 1 As shown, the adaptive interactive teaching support system 100 according to an embodiment of this application may include a teaching content acquisition module 10, a smart note generation module 20, a student interaction module 30, a data acquisition and analysis module 40, and a teacher feedback module 50.

[0060] The teaching content acquisition module is used to acquire the teaching content generated by teachers during their lectures. Acquiring the teaching content generated by teachers during their lectures refers to acquiring the teacher's audio and video recordings, as well as audio and video data such as teaching materials, corresponding to the teaching content generated during the lectures.

[0061] In one embodiment of this application, the teaching content acquisition module 10 is specifically used for:

[0062] Collect audio and video data generated during the teacher's lectures;

[0063] The audio and video data are sent to the cloud server as teaching content for students to download or watch on demand; and / or the audio and video data are pushed to the online and offline student terminals as teaching content.

[0064] Specifically, the audio and video of the teacher and teaching materials can be captured using audio and video capture devices installed at the teacher's classroom. For example, at least one camera and microphone installed at the classroom can be used to capture the audio, video, and teaching materials. This audio and video data is then sent to a cloud server for students to download or access. Alternatively, a web link to the audio and video data can be sent to students so they can download or access it with authorization. The audio and video data can also be directly pushed to online and offline student terminals. Student terminals can be devices capable of playing audio and video data, such as desktop computers, laptops, and tablets.

[0065] The intelligent note-taking module is used to generate student notes in real time based on the teaching content using artificial intelligence (AI) algorithms, and then push the notes to online and offline student terminals. For example, it can identify the teacher's audio data using AI algorithms, then convert the audio data into text-based student notes, and then push the student notes to online and offline student terminals.

[0066] In one embodiment of this application, the smart note generation module 20 includes a content recognition module 201; the content recognition module 201 is used for:

[0067] Receive audio and video data generated during the teacher's lecture;

[0068] Identify the audio data to be processed in the audio and video data;

[0069] The audio data to be processed is subjected to speech recognition, and subtitle data corresponding to the multimedia teaching data to be processed is generated based on the speech recognition results.

[0070] Identify the video data to be processed within the audio and video data;

[0071] Identify text data in the video data to be processed;

[0072] Student notes are generated by combining the subtitle data and the text data;

[0073] The student notes are displayed in the editable area of ​​the display interface on both online and offline student terminals.

[0074] Specifically, when teachers are giving live lectures, they only need to turn on their microphones and the intelligent note-taking function of the adaptive interactive teaching support system. The AI ​​system will then automatically transcribe the teacher's lecture content into a written record in real time, without requiring any action from the teacher. For example, clicking the "Real-time Transcription" button on the online and offline student terminal display interface of the adaptive interactive teaching support system will activate the intelligent note-taking function, where the AI ​​system will automatically transcribe the teacher's lecture content into a written record in real time.

[0075] like Figure 2 The diagram shows a schematic of the display interface 60 of the online and offline student terminal in the first example. According to the preset layout strategy, the left display area shows the teacher's image, which can be tracked as the teacher moves; the middle display area displays the teaching content, such as teaching slides; and the right display area is the note display area, which is editable, allowing students to make marks or annotations. For example, the note display area can display only the subtitle data corresponding to the teacher's speech, or it can display the content corresponding to the teaching slides and the teacher's speech simultaneously. The layout strategy can be adjusted according to the user's needs; for example, the left area can display the teaching content, the middle area can display the teacher's image, and the right display area can display the student's notes.

[0076] In some examples, student notes can also be translated into multiple languages. For instance, one can click the "Caption" dropdown menu on the online and offline student terminal display interfaces of the adaptive interactive teaching support system and select the target language.

[0077] In other examples, student notes can also be saved in the live-streamed course replay, allowing students to access their notes at any time by watching the replay.

[0078] In other embodiments, the teacher has the authority to control whether students have permission to enable the smart note-taking and translation functions. For example, the teacher can prohibit students from enabling the smart note-taking or translation functions; when the teacher does not prohibit students from enabling the smart note-taking or translation functions, students can automatically enable or disable these functions.

[0079] This application's embodiment enables AI-generated real-time transcription. During live-streamed classes, teachers only need to enable the audio and subtitle data conversion function, and the system will use AI technology to transcribe the teacher's lecture into text records in real time, without any manual intervention from the teacher. This transcribed content will also be saved in the playback video for students to view at any time, providing convenience for learning.

[0080] In one embodiment of this application, the smart note generation module 20 further includes a student record module 202; the student record module 202 is used for:

[0081] Receive learning notes edited by students on the student notes; wherein the learning notes include at least one of the following: markings, annotations, and questions;

[0082] Based on the learning records and the student notes, the final learning notes are generated.

[0083] Specifically, students can write notes, comments, and questions in their student notebooks.

[0084] like Figure 3 The image shown is a schematic diagram of the display interface 60 of the online and offline student terminals in the second example. According to the preset layout strategy, the left display area shows the teacher's image, the middle display area shows the teaching content, and the right display area shows the notes. When a student places the mouse cursor over the editable area, the mouse action is automatically recognized, displaying an editing menu with buttons such as "Mark," "Write Thoughts," "Copy," and "AI Q&A." When a student selects "Mark," they can mark key points, difficult points, and important points in their notes. Marks can be underlines or have easily identifiable colors; different colors can correspond to different key points, difficult points, and important points. When a student needs to add annotations to key points, they can click the "Write Thoughts" button on the online and offline student terminal display interface, write their annotations in the pop-up text box, and then click the "Save" button.

[0085] The aforementioned markings, annotations, and questions are combined with the original student notes to create the final study notes. Students can also copy the study notes into a document or save them to the playback video for later review.

[0086] like Figure 4 The image shows a schematic diagram of the online and offline student terminal display interface 60 in the third example. At the end of the course, student notes, lecture slides, and student markings and annotations can be integrated to form a "Complete AI Notes," which can be saved for later review when watching replays. Alternatively, only student notes and markings / annotations can be integrated to form "Annotations and Notes." The "Complete AI Notes" and "Annotations and Notes" are different tabs on the same window and can be switched by clicking the tabs.

[0087] In this embodiment, students can mark the lecture content, easily highlighting key points, difficult concepts, or crucial information during live classes. This embodiment also supports multiple marking methods, such as different background colors and underline colors. Furthermore, students can add personal annotations to knowledge points. Simply select the "Write Thoughts" button on the display interface and click it to record and save their notes in the pop-up text box. These markings and annotations will be embedded in the replay video for students to review at any time.

[0088] The student interaction module is used to receive students' annotations, real-time questions, thought records, and personalized queries submitted to the AI ​​assistant in the student notes.

[0089] In one embodiment of this application, the student interaction module 30 includes a question-and-answer module 301, which is used for:

[0090] During the playback of the teaching content, and at any point after the playback of the teaching content, questions input by the input device are received;

[0091] The question is received through the AI ​​system entry point, and the AI ​​system's response to the question is also received.

[0092] like Figure 5 The image shown is a schematic diagram of the online and offline student terminal display interface 60 in the fourth example. Specifically, students can ask AI-powered questions about knowledge points by simply selecting the knowledge point they want to ask about and then clicking with the mouse. Figure 3 The "AI Q&A" button shown will take you to the AI ​​Q&A interface, where you can see the answers automatically generated by the AI ​​system. If students do not fully understand the answers, they can continue to ask questions until the problem is solved.

[0093] In this embodiment, students can ask and answer questions about the course content using AI. Students can use the system to ask intelligent questions; by selecting a specific knowledge point and clicking the "AI Question and Answer" button, the system will automatically generate the corresponding answer. If a student's understanding of a concept is not thorough enough, the system supports asking questions continuously until the problem is solved. This function not only promotes the depth of individual learning but also provides personalized learning support.

[0094] In one embodiment of this application, the student interaction module 30 further includes a summary generation module 302, the summary generation module 302 being used for:

[0095] At any time after the teaching content has been played to a preset time or after playback has ended, a course summary of the teaching content sent by the artificial intelligence system is received; wherein the course summary is generated by the artificial intelligence system based on the teaching content.

[0096] Continue to combine Figure 4 This is a schematic diagram of the online and offline student terminal display interface 60 in the third example. When the course ends, the AI ​​system can automatically generate a "course summary" of the teaching content; it can also generate a "course summary" of the teaching content at any time during the course. "Complete AI Notes," "Annotations and Notes," and "Course Summary" are different tab pages on the same window, which can be switched by clicking the tabs with the mouse.

[0097] The data acquisition and analysis module 40 is used to collect student behavior data generated by the student interaction module and perform big data analysis.

[0098] In one embodiment of this application, the data acquisition and analysis module 40 is specifically used for:

[0099] Receives video footage of student learning status captured by the image acquisition devices of the online and offline student terminals;

[0100] The image frames in the learning state video are analyzed to extract the student's facial features and body posture features;

[0101] Based on the students' facial features and body posture characteristics, the students' activity level and concentration level were determined;

[0102] The learning state video includes facial emotions and / or body features; the facial emotions include at least joy, anger, confusion, sadness, disgust, fear, and neutrality, and the body posture features include at least lying down, looking down, turning away, raising hands, and standing.

[0103] The target teaching plan includes at least the teaching schedule, teaching content, and teaching speed.

[0104] like Figure 6 The image shown is a schematic diagram of the display interface 70 of the teacher's terminal in the fifth example. In the teacher's terminal display interface, the teacher can see the status information of each student, such as facial expressions and actions. For example, student 1 and student 2 are raising their hands, student 3 is taking notes, and student 4 is thinking. The teacher can adjust the teaching plan based on these statuses to help students receive the teaching content more effectively and improve learning outcomes.

[0105] The teacher feedback module is used to provide real-time feedback of the analysis results to teachers, enabling them to dynamically adjust the teaching content and pace based on the real-time analysis results during real-time teaching, thereby achieving adaptive teaching for both online and offline student groups.

[0106] In one embodiment of this application, the teacher feedback module 50 includes a data statistics module 501, which is used for:

[0107] Real-time statistics of student class attendance data;

[0108] The analysis results of the student's class attendance data are displayed.

[0109] The student's class attendance data includes at least one of the following: the number of times a student asks a question, changes in student activity levels, and whether a student takes notes.

[0110] like Figure 7 The diagram shown illustrates the display interface 70 of the teacher terminal in the sixth example. In embodiments of this application, a head-up screen can be set up on the teacher terminal to dynamically display student learning data, such as course information, classroom data, student activity data, student annotation information, high-frequency questions, keywords, and student concentration data. The system summarizes and analyzes this data and transmits it to the head-up screen in front of the teacher in real time. It can also analyze students' facial expressions, posture, and attention to form additional big data; the teacher can use the AI ​​system to summarize student data to adjust their teaching content in a timely manner, knowing which knowledge points students already understand and quickly skipping those; it can also identify which points students find difficult and require a slower pace of instruction. The adaptive interactive teaching support of this application, operating in an adaptive mode, can improve students' learning efficiency.

[0111] The adaptive interactive teaching support system of this application embodiment, for student terminals, acquires teaching content generated during teacher instruction and generates student notes in real time based on the teaching content. Students can annotate, ask real-time questions, record their thoughts, and make personalized queries to the AI ​​assistant in these student notes. For teacher terminals, the system can collect student behavior data generated by the student interaction module, perform big data analysis, and provide real-time feedback to the teacher. This allows the teacher to dynamically adjust the teaching content and pace based on the real-time analysis results during real-time teaching, thereby achieving adaptive teaching for both online and offline student groups. This application embodiment, on the one hand, automatically generates learning notes for students, enabling them to record learning content in a timely manner and improve their mastery of knowledge points; on the other hand, the system collects and analyzes student feedback data in real time, helping teachers adjust teaching content and pace in real time to improve teaching effectiveness.

[0112] like Figure 8 The diagram shown is a schematic flowchart of an adaptive interactive teaching support method 800 according to an embodiment of this application. The adaptive interactive teaching support method 800 according to an embodiment of this application may include the following steps: S801, S802, S803, S804, and S805.

[0113] In step S801, the teaching content generated during the teacher's lecture is obtained;

[0114] In step S802, based on the teaching content, student notes are generated in real time using artificial intelligence algorithms, and the notes are pushed to online and offline student terminals;

[0115] In step S803, the system receives student annotations, real-time questions, thought records, and personalized queries submitted to the AI ​​assistant in the student's notes.

[0116] In step S804, student behavior data generated by the student interaction module is collected and big data analysis is performed.

[0117] In step S805, the analysis results are fed back to the teacher in real time, so that the teacher can dynamically adjust the teaching content and pace according to the real-time analysis results during real-time teaching, thereby achieving adaptive teaching for online and offline student groups.

[0118] This application relates to an adaptive interactive teaching support method that utilizes artificial intelligence (AI) technology to automatically generate learning notes and novel big data-based reports. Simultaneously, AI technology automatically converts the teacher's lecture content into text records, which students can annotate through the system. In this application embodiment, AI technology can also be used to achieve real-time classroom feedback. Students' reactions in class, including learning actions, facial expressions, posture, and attention, are displayed in real-time on a head-up display. Teachers can adjust their teaching content based on the data on the head-up display, quickly covering already mastered knowledge points, slowing down the explanation of difficult points raised by students, repeating content that needs reinforcement, and skipping familiar parts, thereby forming an adaptive teaching model.

[0119] Furthermore, according to embodiments of this application, a storage medium is also provided, on which program instructions are stored. When executed by a computer or processor, these program instructions are used to perform corresponding steps of the adaptive interactive teaching support method of this application. The storage medium may, for example, include a memory card of a smartphone, a storage component of a tablet computer, a hard disk of a personal computer, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a portable compact disc read-only memory (CD-ROM), a USB memory, or any combination of the above storage media.

[0120] The adaptive interactive teaching support method and storage medium of this application embodiment have the same advantages as the aforementioned adaptive interactive teaching support system because they can implement the aforementioned adaptive interactive teaching support system.

[0121] Although exemplary embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above exemplary embodiments are merely illustrative and are not intended to limit the scope of this application. Various changes and modifications can be made therein by those skilled in the art without departing from the scope and spirit of this application. All such changes and modifications are intended to be included within the scope of this application as claimed in the appended claims.

[0122] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0123] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed.

[0124] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of this application may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0125] Similarly, it should be understood that, in order to streamline this application and aid in understanding one or more of the various inventive aspects, features of this application may sometimes be grouped together in a single embodiment, figure, or description thereof in the description of exemplary embodiments of this application. However, this approach should not be construed as reflecting an intention that the claimed application requires more features than are expressly recited in each claim. Rather, as reflected in the corresponding claims, its inventive point lies in solving the corresponding technical problem with features fewer than all features of a single disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of this application.

[0126] Those skilled in the art will understand that, apart from the mutual exclusion of features, all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or apparatus so disclosed can be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0127] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are intended to be within the scope of this application and form different embodiments. For example, in the claims, any one of the claimed embodiments can be used in any combination.

[0128] The various component embodiments of this application can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some modules according to the embodiments of this application. This application can also be implemented as an apparatus program (e.g., a computer program and computer program product) for performing part or all of the methods described herein. Such an implementation of this application can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0129] It should be noted that the above embodiments are illustrative of this application and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. This application can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0130] The above description is merely a specific embodiment or illustration of the embodiments of this application. The scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. The scope of protection of this application shall be determined by the scope of the claims.

Claims

1. An adaptive interactive teaching support system, characterized in that, The system includes: The teaching content acquisition module is used to acquire teaching content generated by teachers during the course of their lectures; The intelligent note generation module is used to generate student notes in real time based on the teaching content using artificial intelligence algorithms, and push the notes to online and offline student terminals; The student interaction module is used to receive students' annotations, real-time questions, thought records, and personalized queries to the AI ​​assistant in the student notes. The data acquisition and analysis module is used to collect student behavior data generated by the student interaction module and perform big data analysis. The teacher feedback module is used to provide real-time feedback of the analysis results to teachers, enabling them to dynamically adjust the teaching content and pace based on the real-time analysis results during real-time teaching, thereby achieving adaptive teaching for both online and offline student groups.

2. The system according to claim 1, characterized in that, The teaching content acquisition module is specifically used for: Collect audio and video data generated during the teacher's lectures; The audio and video data are sent to the cloud server as teaching content for students to download or stream. And / or push the audio and video data as teaching content to the online and offline student terminals.

3. The system according to claim 1, characterized in that, The smart note generation module includes a content recognition module; the content recognition module is used for: Receive audio and video data generated during the teacher's lecture; Identify the audio data to be processed in the audio and video data; The audio data to be processed is subjected to speech recognition, and subtitle data corresponding to the multimedia teaching data to be processed is generated based on the speech recognition results. Identify the video data to be processed within the audio and video data; Identify text data in the video data to be processed; Student notes are generated by combining the subtitle data and the text data; The student notes are displayed in the editable area of ​​the display interface on both online and offline student terminals.

4. The system according to claim 3, characterized in that, The smart note generation module also includes a student recording module; the student recording module is used for: Receive learning notes edited by students on the student notes; wherein the learning notes include at least one of the following: markings, annotations, and questions; Based on the learning records and the student notes, the final learning notes are generated.

5. The system according to claim 3, characterized in that, The student interaction module includes a question-and-answer module, which is used for: During the playback of the teaching content, and at any point after the playback of the teaching content, questions input by the input device are received; The question is received through the AI ​​system entry point, and the AI ​​system's response to the question is also received.

6. The system according to claim 5, characterized in that, The student interaction module also includes a summary generation module, which is used for: At any time after the teaching content has been played to a preset time or after playback has ended, a course summary of the teaching content sent by the artificial intelligence system is received; wherein the course summary is generated by the artificial intelligence system based on the teaching content.

7. The system according to claim 1, characterized in that, The data acquisition and analysis module is specifically used for: Receives video footage of student learning status captured by the image acquisition devices of the online and offline student terminals; The image frames in the learning state video are analyzed to extract the student's facial features and body posture features; Based on the students' facial features and body posture characteristics, the students' activity level and concentration level were determined; The learning state video includes facial emotions and / or body features; the facial emotions include at least joy, anger, confusion, sadness, disgust, fear, and neutrality, and the body posture features include at least lying down, looking down, turning away, raising hands, and standing. The target teaching plan includes at least the teaching schedule, teaching content, and teaching speed.

8. The system according to claim 1, characterized in that, The teacher feedback module includes a data statistics module, which is used for: Real-time statistics of student class attendance data; The analysis results of the student's class attendance data are displayed. The student's class attendance data includes at least one of the following: the number of times a student asks a question, changes in student activity levels, and whether a student takes notes.

9. An adaptive interactive teaching support method, characterized in that, The method includes: Obtain the teaching content generated during the teacher's lecture; Based on the teaching content, artificial intelligence algorithms are used to generate student notes in real time, and the notes are pushed to online and offline student terminals. It can receive students' annotations, real-time questions, reflection records, and personalized queries submitted to the AI ​​assistant in the student notes. Collect student behavior data generated by the student interaction module and perform big data analysis; The analysis results are fed back to teachers in real time, enabling them to dynamically adjust the teaching content and pace based on the real-time analysis results during teaching, thereby achieving adaptive teaching for both online and offline student groups.

10. A storage medium, characterized in that, The storage medium stores a computer program, which, when run by a processor, causes the processor to execute the adaptive interactive teaching support method as described in claim 9.

Images