An interactive teaching system and method for art education
By combining multimodal data acquisition and AI analysis technologies with AR virtual-real fusion and a personalized teaching engine, the problems of remote tutoring and personalized teaching in art education have been solved, achieving accurate error correction and efficient collaborative creation, thus improving teaching effectiveness.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- JIANGXI INST OF FASHION TECH
- Filing Date
- 2026-03-18
- Publication Date
- 2026-06-02
AI Technical Summary
Existing art education equipment cannot provide real-time guidance to students in different locations, makes it difficult to quantify and capture brushstroke details, cannot personalize teaching content, prevents students in different locations from participating in group creation, and lacks real-time communication and effective error correction guidance during the creation process.
It employs a multimodal data acquisition module, an AI-powered intelligent pen stroke analysis module, an AR virtual-real fusion teaching module, a personalized dynamic teaching engine, a remote collaborative interaction module, and a cloud-based teaching database to achieve real-time data acquisition, accurate error correction, personalized teaching, remote collaborative creation, and intelligent evaluation.
It enables precise capture of brushstroke details, personalized teaching content adaptation, remote synchronous creation and real-time communication, improving the pertinence and efficiency of teaching, and reducing the difficulty of learning and the burden on teachers.
Smart Images
Figure CN122135624A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of interdisciplinary technology of educational technology and art teaching, and in particular to an interactive teaching system and method for art education. Background Technology
[0002] As a core discipline for cultivating aesthetic literacy, creativity, and practical skills, the effectiveness of art education relies heavily on a closed-loop interaction of "demonstration-imitation-correction-consolidation."
[0003] However, in practical applications, existing equipment requires teaching activities to be conducted in fixed locations and at fixed times. When teachers and students are in different locations, real-time tutoring is impossible, and technical problems encountered by students during after-class practice cannot be answered in a timely manner. Teachers need to pay attention to multiple students at the same time and can only judge details such as students' penmanship and brushstrokes by visual observation. It is difficult to quantify and capture key parameters such as brush pressure, speed, and trajectory, resulting in errors not being accurately identified. Correction guidance is mostly "general advice" and lacks specificity. Teachers usually use a uniform teaching pace and demonstration content, and cannot flexibly adjust the teaching difficulty and materials according to students' basic level, learning pace, and style preferences. This results in weak students falling behind and solid students not "learning enough." When creating in groups, it is necessary to rely on physical canvases for joint operation. Due to space and number of people, students in different locations cannot participate, and it is difficult to communicate technical details in real time during the creation process. The modification and review of works lack effective support, which is not conducive to practical application and operation. Summary of the Invention
[0004] One objective of this invention is to provide an interactive teaching system and method for art education.
[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: an interactive teaching system and method for art education, including a multimodal data acquisition module, an AI brushstroke intelligent analysis module, an AR virtual-real fusion teaching module, a personalized dynamic teaching engine, a remote collaborative interaction module, a cloud teaching database, and a display output module;
[0006] The multimodal data acquisition module is used to collect pressure stroke data, hand 3D posture data, voice command data, and RGB-D depth image data of the creation scene in real time during user art creation.
[0007] The AI-powered brushstroke intelligent analysis module is connected to the multimodal data acquisition module and is used to perform vectorized fitting of brushstroke data, classify brushstroke techniques, detect erroneous brushstrokes in real time, and generate technique feature labels and deviation data.
[0008] The AR virtual-real fusion teaching module uses SLAM spatial positioning to overlay and render virtual demonstration brushstrokes, structural auxiliary lines, and color matching guidelines with the real creation canvas at the millimeter level.
[0009] The personalized dynamic teaching engine dynamically matches the teaching difficulty and outputs real-time error correction instructions and tiered demonstration materials based on technique feature tags and users' historical learning data through a reinforcement learning model.
[0010] The remote collaborative interaction module supports multiple terminals accessing the same virtual canvas, enabling multi-person collaborative creation with low-latency pen stroke synchronization, hierarchical permission management, and real-time voice annotation;
[0011] The cloud-based teaching database stores art technique libraries, demonstration case libraries, user learning profile libraries, and collaborative creation datasets.
[0012] The display output module simultaneously presents the AR-integrated visuals, teaching guides, collaborative interfaces, and work evaluation results.
[0013] Preferably, the multimodal data acquisition module includes a high-precision pressure-sensing drawing board, an RGB-D depth camera, and a ring-shaped noise-reducing microphone.
[0014] Preferably, the digital brushstroke analysis module includes a trajectory fitting unit, a technique recognition unit, an error diagnosis unit, and a style matching unit.
[0015] Preferably, the AR virtual-real fusion teaching module supports virtual pen strokes following the user's hand movements in real time, realizing "hands-on" interactive guidance.
[0016] Preferably, the personalized dynamic teaching engine has three built-in teaching modes: basic completion, creative expansion, and style guidance, each corresponding to a preset technique training path.
[0017] Preferred examples include an intelligent work evaluation module that automatically scores works based on a preset evaluation index system across four dimensions: composition, color, technique, and creativity, and generates a visual report. The evaluation results are simultaneously updated to a cloud-based learning profile to iteratively optimize subsequent teaching strategies.
[0018] Preferably, the remote collaborative interaction module supports pen stroke playback, partial annotation, and work merging and export functions.
[0019] Preferably, it includes the following steps:
[0020] S1. System initialization, completing hardware calibration and loading cloud teaching data;
[0021] S2, the multimodal data acquisition module collects creative brushstrokes, postures, voice and image data in real time;
[0022] S3, the digital brushstroke analysis module performs vector analysis, technique recognition, and error detection on the data;
[0023] S4, the AR virtual-real fusion module overlays and renders virtual teaching guides with real canvases in real time;
[0024] S5, the personalized dynamic teaching engine outputs matching error correction instructions and demonstration content according to preset rules;
[0025] S6. Activate the remote collaboration module as needed to enable multi-person synchronous creation or provide single-person creation guidance.
[0026] S7. After the creation is completed, the intelligent evaluation module generates a scoring report based on preset indicators and updates the learning progress in the cloud.
[0027] S8. Save creation data and push personalized after-class practice tasks.
[0028] Preferably, the brushstroke analysis in step S3 includes digital modeling of pressure, speed, direction, and trajectory points, and the technique recognition is based on comparison and matching of a preset technique feature parameter library.
[0029] Preferably, in step S4, the AR guidance aligns with the user's drawing position in real time without delay; in step S6, collaborative creation supports layered operations, permission control, and real-time intercom; and in step S7, the evaluation report includes a score, problem analysis, improvement suggestions, and comparison with similar works.
[0030] Compared with the prior art, the beneficial effects of the present invention are as follows:
[0031] This invention utilizes multimodal data acquisition and digital brushstroke rule analysis to accurately capture users' brushstroke details and technique deviations. Unlike traditional teaching methods that rely on teachers' "visual observation and general guidance," this system enables precise "point-to-point" error correction. Furthermore, based on a pre-set rule base, personalized adaptation allows users with different skill levels and needs to receive tailored teaching content, avoiding the problem of "those with strong foundations not learning enough, and those with weak foundations falling behind," significantly improving the relevance of teaching. The AR-integrated "hands-on" guidance mode transforms abstract technique standards into visual virtual guidance. Users no longer need to repeatedly ponder through text or videos; they can quickly master techniques directly through "imitation, comparison, and adjustment." This is particularly suitable for teenagers and art beginners to understand complex creative logic, effectively reducing the learning difficulty.
[0032] The remote collaborative interaction module supports real-time access to a shared virtual canvas from multiple terminals, enabling low-latency brushstroke synchronization, hierarchical permission management, and real-time voice annotation. This solves the problems of "difficulty in remote tutoring and poor synchronization in group creation" in traditional art education. Teachers and students can conduct one-on-one precise tutoring remotely, and students can collaborate across regions to complete collective creations. It also supports brushstroke playback and partial annotation, facilitating teaching review and skill exchange, and improving the efficiency of teaching interaction. The system constructs a closed-loop process of "collection, analysis, guidance, creation, evaluation, and feedback." The intelligent evaluation after creation can not only provide quantitative scores according to preset indicators, but also provide specific improvement suggestions and comparisons with similar works to help users identify weaknesses. At the same time, the updated learning profile will drive precise push of after-class exercises, realizing continuous optimization of "learning, practicing, evaluating, and revising," avoiding the drawbacks of "only teaching without evaluation and only practicing without revision" in traditional teaching, and significantly enhancing learning effectiveness.
[0033] The system uses existing, mature hardware (pressure-sensitive drawing board, RGB-D camera, etc.), which is readily available and highly compatible. The preset technique standard library and evaluation index system can be customized to suit different teaching scenarios, adapting to the teaching needs of various painting genres such as sketching, watercolor, and oil painting, combining professional teaching with scenario flexibility. Users do not need to master complex operations; they can interact through natural creative movements and simple voice commands. Teachers do not need to repeatedly demonstrate or grade assignments one by one; the system can automatically complete data collection, error detection, and basic evaluation, freeing teachers from tedious basic tasks and allowing them to focus more on core teaching aspects such as creative guidance and style shaping, while reducing students' learning pressure. Attached Figure Description
[0034] Figure 1 This is a schematic diagram of the overall process structure of the present invention. Detailed Implementation
[0035] The present invention will now be further described in conjunction with specific embodiments. It should be noted that, without conflict, the various embodiments or technical features described below can be arbitrarily combined to form new embodiments.
[0036] In the description of this invention, it should be noted that directional terms such as "center," "lateral," "longitudinal," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise" indicate the orientation and positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. They should not be construed as limiting the specific protection scope of this invention.
[0037] It should be noted that the terms "first" and "second" in the specification and claims of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.
[0038] One preferred embodiment of the present invention, such as Figure 1 As shown, an interactive teaching system and method for art education includes a multimodal data acquisition module, an AI brushstroke intelligent analysis module, an AR virtual-real fusion teaching module, a personalized dynamic teaching engine, a remote collaborative interaction module, a cloud-based teaching database, and a display output module.
[0039] The multimodal data acquisition module is used to collect pressure stroke data, hand 3D posture data, voice command data, and RGB-D depth image data of the creation scene in real time during user art creation.
[0040] The AI-powered brushstroke intelligent analysis module, connected to the multimodal data acquisition module, is used to perform vectorized fitting of brushstroke data, classify brushstroke techniques, detect erroneous brushstrokes in real time, and generate technique feature labels and deviation data.
[0041] The AR virtual-real fusion teaching module uses SLAM spatial positioning to overlay and render virtual demonstration brushstrokes, structural auxiliary lines, and color matching guidelines with the real creation canvas at the millimeter level.
[0042] The personalized dynamic teaching engine dynamically matches the teaching difficulty and outputs real-time error correction instructions and tiered demonstration materials based on technique feature tags and users' historical learning data through a reinforcement learning model.
[0043] The remote collaborative interaction module supports multiple terminals accessing the same virtual canvas, enabling multi-person collaborative creation with low-latency pen stroke synchronization, hierarchical permission management, and real-time voice annotation;
[0044] The cloud-based teaching database stores art technique libraries, demonstration case libraries, user learning profile libraries, and collaborative creation datasets.
[0045] The display output module simultaneously presents the AR-integrated visuals, teaching guides, collaborative interfaces, and work evaluation results.
[0046] The multimodal data acquisition module includes a high-precision pressure-sensitive drawing board, an RGB-D depth camera, and a ring-shaped noise-canceling microphone.
[0047] The digital brushstroke analysis module includes a trajectory fitting unit, a technique recognition unit, an error diagnosis unit, and a style matching unit.
[0048] The AR virtual-real fusion teaching module supports virtual pen strokes that follow the user's hand movements in real time, enabling "hands-on" interactive guidance.
[0049] The personalized dynamic teaching engine has three built-in teaching modes: basic completion, creative expansion, and style guidance. Each mode corresponds to a preset technique training path.
[0050] It includes an intelligent work evaluation module that automatically scores works based on a preset evaluation index system from four dimensions: composition, color, technique, and creativity, and generates a visual report. The evaluation results are simultaneously updated to a cloud-based learning profile to iteratively optimize subsequent teaching strategies.
[0051] The remote collaborative interaction module supports pen stroke playback, partial annotation, and merging and exporting of works.
[0052] Includes the following steps:
[0053] S1. System initialization, completing hardware calibration and loading cloud teaching data;
[0054] S2, the multimodal data acquisition module collects creative brushstrokes, postures, voice and image data in real time;
[0055] S3, the digital brushstroke analysis module performs vector analysis, technique recognition, and error detection on the data;
[0056] S4, the AR virtual-real fusion module overlays and renders virtual teaching guides with real canvases in real time;
[0057] S5, the personalized dynamic teaching engine outputs matching error correction instructions and demonstration content according to preset rules;
[0058] S6. Activate the remote collaboration module as needed to enable multi-person synchronous creation or provide single-person creation guidance.
[0059] S7. After the creation is completed, the intelligent evaluation module generates a scoring report based on preset indicators and updates the learning progress in the cloud.
[0060] S8. Save creation data and push personalized after-class practice tasks.
[0061] Step S3 involves brushstroke analysis, which includes digital modeling of pressure, speed, direction, and trajectory points. Technique recognition is based on comparison and matching using a preset technique feature parameter library.
[0062] In step S4, the AR guidance aligns with the user's drawing position in real time without delay; in step S6, collaborative creation supports layered operations, permission control, and real-time intercom; in step S7, the evaluation report includes scores, problem analysis, improvement suggestions, and comparisons with similar works.
[0063] Working principle:
[0064] During use, the system initialization phase completes the calibration of hardware such as the high-precision pressure-sensitive drawing board, RGB-D depth camera, and ring noise-canceling microphone. At the same time, it loads the preset art technique standard library, demonstration case library, and user historical learning profile from the cloud teaching database to provide basic data support for subsequent teaching.
[0065] Real-time multimodal data acquisition: While the user is creating artwork, the multimodal data acquisition module works synchronously: the pressure-sensitive drawing board accurately captures the pressure of the brushstrokes, the speed of the brushstrokes, and the trajectory coordinates; the RGB-D depth camera acquires the 3D posture of the hand and the depth information of the artwork in real time; the ring noise-canceling microphone receives the user's voice commands, realizing the complete acquisition of multi-dimensional creative data and providing a comprehensive basis for subsequent analysis.
[0066] Digital pen stroke rule-based analysis: The collected multi-dimensional data is transmitted to the digital pen stroke analysis module. This module uses a preset vectorization algorithm to convert pen stroke trajectory, pressure changes, and pen stroke speed into a quantifiable digital model. Then, the parameters are compared with the technique standard library loaded in the cloud. The trajectory fitting unit matches whether the pen stroke path conforms to the standard. The technique recognition unit determines the type of technique used by the user based on the combination parameters of pressure, speed, and direction. The error diagnosis unit judges the error based on the deviation threshold and generates corresponding technique feature labels and deviation data.
[0067] AR Virtual-Real Blending Intuitive Guidance: The AR virtual-real fusion teaching module uses SLAM spatial positioning technology to achieve millimeter-level precise alignment between virtual demonstration brushstrokes, structural guidelines, and color matching instructions retrieved from the cloud and the user's real canvas. Furthermore, the virtual guidance synchronizes in real-time with the user's hand movements without delay or misalignment. This "virtual-real overlay" mode provides users with intuitive, step-by-step guidance, allowing them to directly refer to the virtual guidance to adjust their brushstrokes and quickly understand how to execute standard techniques.
[0068] Personalized teaching dynamic adaptation: The personalized dynamic teaching engine uses the technique feature tags and deviation data output by the digital brushstroke analysis module, combined with the user's historical learning profile, to match the preset teaching rule library: For users with weak technique foundation, the "Basic Completion Mode" is activated, pushing step-by-step demonstration materials and targeted error correction instructions for the corresponding techniques; for users with a certain foundation, the "Creative Expansion Mode" is activated, providing stylized demonstration materials; for users who pursue personalized expression, the "Style Guidance Mode" is activated, pushing creative ideas and technique combination suggestions of similar styles, achieving personalized teaching adaptation for "a thousand people, a thousand paths".
[0069] Remote collaborative creation support: When there is a need for multi-user collaborative teaching, the remote collaborative interaction module responds to the request and builds a shared virtual canvas: After multiple terminals are connected, pen stroke data is synchronized with low latency, and hierarchical permission management is supported. With real-time voice annotation and intercom functions, "same-screen creation and real-time communication" can be realized; during the creation process, the pen stroke trajectory of any user can be replayed at any time, which is convenient for teachers to make targeted comments or for students to learn skills from each other.
[0070] Closed-loop evaluation and feedback: After users complete their creations, the intelligent work evaluation module compares and scores them based on a preset multi-dimensional evaluation index system and standard parameters from the cloud-based demonstration case library. It generates a visual report that not only includes scores for each dimension but also clearly points out the problems, provides specific improvement suggestions, and pushes similar excellent works for comparison and reference. The evaluation results are simultaneously updated to the cloud-based learning profile. Based on the updated learning data, the system matches targeted practice tasks from the after-class practice library, forming a closed-loop teaching system of "creation, evaluation, feedback, and consolidation".
[0071] The basic principles, main features, and advantages of this invention have been described above. Those skilled in the art should understand that this invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made without departing from the spirit and scope of the invention, and all such changes and modifications fall within the scope of the invention as claimed. The scope of protection claimed by this invention is defined by the appended claims and their equivalents.
Claims
1. An interactive teaching system for art education, characterized in that, It includes a multimodal data acquisition module, an AI pen stroke intelligent analysis module, an AR virtual-real fusion teaching module, a personalized dynamic teaching engine, a remote collaborative interaction module, a cloud-based teaching database, and a display output module; The multimodal data acquisition module is used to collect pressure stroke data, hand 3D posture data, voice command data, and RGB-D depth image data of the creation scene in real time during user art creation. The AI-powered brushstroke intelligent analysis module is connected to the multimodal data acquisition module and is used to perform vectorized fitting of brushstroke data, classify brushstroke techniques, detect erroneous brushstrokes in real time, and generate technique feature labels and deviation data. The AR virtual-real fusion teaching module uses SLAM spatial positioning to overlay and render virtual demonstration brushstrokes, structural auxiliary lines, and color matching guidelines with the real creation canvas at the millimeter level. The personalized dynamic teaching engine dynamically matches the teaching difficulty and outputs real-time error correction instructions and tiered demonstration materials based on technique feature tags and users' historical learning data through a reinforcement learning model. The remote collaborative interaction module supports multiple terminals accessing the same virtual canvas, enabling multi-person collaborative creation with low-latency pen stroke synchronization, hierarchical permission management, and real-time voice annotation; The cloud-based teaching database stores art technique libraries, demonstration case libraries, user learning profile libraries, and collaborative creation datasets. The display output module simultaneously presents the AR-integrated visuals, teaching guides, collaborative interfaces, and work evaluation results.
2. The interactive teaching system for art education as described in claim 1, characterized in that: The multimodal data acquisition module includes a high-precision pressure-sensitive drawing board, an RGB-D depth camera, and a ring-shaped noise-reducing microphone.
3. The interactive teaching system for art education as described in claim 1, characterized in that: The digital brushstroke analysis module includes a trajectory fitting unit, a technique recognition unit, an error diagnosis unit, and a style matching unit.
4. The interactive teaching system for art education as described in claim 1, characterized in that: The AR virtual-real fusion teaching module supports virtual pen strokes that follow the user's hand movements in real time, enabling "hands-on" interactive guidance.
5. The interactive teaching system for art education as described in claim 1, characterized in that: The personalized dynamic teaching engine has three built-in teaching modes: basic completion, creative expansion, and style guidance. Each mode corresponds to a preset technique training path.
6. The interactive teaching system for art education as described in claim 1, characterized in that: It includes an intelligent work evaluation module that automatically scores works based on a preset evaluation index system from four dimensions: composition, color, technique, and creativity, and generates a visual report. The evaluation results are simultaneously updated to a cloud-based learning profile to iteratively optimize subsequent teaching strategies.
7. The interactive teaching system for art education as described in claim 1, characterized in that: The remote collaborative interaction module supports functions such as pen stroke playback, partial annotation, and merging and exporting of works.
8. An interactive teaching method for art education, applied to the system described in any one of claims 1-7, characterized in that: Includes the following steps: S1. System initialization, completing hardware calibration and loading cloud teaching data; S2, the multimodal data acquisition module collects creative brushstrokes, postures, voice and image data in real time; S3, the digital brushstroke analysis module performs vector analysis, technique recognition, and error detection on the data; S4, the AR virtual-real fusion module overlays and renders virtual teaching guides with real canvases in real time; S5, the personalized dynamic teaching engine outputs matching error correction instructions and demonstration content according to preset rules; S6. Activate the remote collaboration module as needed to enable multi-person synchronous creation or provide single-person creation guidance. S7. After the creation is completed, the intelligent evaluation module generates a scoring report based on preset indicators and updates the learning progress in the cloud. S8. Save creation data and push personalized after-class practice tasks.
9. The interactive teaching method for art education as described in claim 8, characterized in that: In step S3, the brushstroke analysis includes digital modeling of pressure, speed, direction, and trajectory points, and the technique recognition is based on comparison and matching of a preset technique feature parameter library.
10. The interactive teaching method for art education as described in claim 8, characterized in that: In step S4, the AR guidance aligns with the user's drawing position in real time without delay; in step S6, collaborative creation supports layered operations, permission control, and real-time intercom; in step S7, the evaluation report includes a score, problem analysis, improvement suggestions, and comparison with similar works.