Online teaching system and online teaching method

Abstract

The invention relates to the technical field of online education, and discloses an online teaching system, which comprises an intelligent handwriting recognition module used for capturing a writing track of a user, detecting a stroke sequence, force, an angle and a writing sequence and analyzing writing content, and the intelligent handwriting recognition module is used for recognizing the writing content through an advanced sensor and an algorithm. The stroke sequence error detection module captures a writing track of a user in real time, analyzes multiple items of information such as stroke sequence, force and angle, sets a writing path of the user as a vector, and calculates an included angle between strokes by using a track analysis algorithm, so that stroke sequence errors are accurately recognized, and the accuracy of error detection is improved. According to the method, the writing process can feed back the defects in the writing process in time, the user is helped to continuously improve in the learning process, and then the error detection and recording module not only can automatically recognize errors occurring in the writing process of the user, but also can record the error parts in detail.

Description

Technical Field

[0001] The present invention relates to the technical field of online education, and in particular to an online teaching system and an online teaching method. Background Art

[0002] With the rapid development of information technology, online education has gradually become an important part of modern education. Traditional calligraphy teaching methods often rely on face-to-face instruction, and teachers pay limited attention to individual differences of students, making it difficult to achieve personalized teaching. In addition, traditional calligraphy learning often lacks an effective feedback mechanism, and students find it difficult to correct mistakes in time during practice, resulting in low learning efficiency and a decrease in learning interest. In recent years, with the advancement of intelligent hardware and software technology, the research and application of online teaching systems have continued to deepen. The development of intelligent handwriting recognition technology enables electronic devices to capture and analyze users' writing trajectories in real time and provide accurate writing feedback. This technology can effectively identify elements such as stroke order, strength and angle in writing, providing new possibilities for calligraphy learning.

[0003] However, existing online teaching systems still have shortcomings in achieving personalized learning and real-time feedback. Many systems can only provide basic writing detection and cannot deeply analyze the user's learning process and provide targeted suggestions. In addition, the existing playback function is usually limited to static display and lacks vivid dynamic feedback, which makes it difficult to attract students' attention and improve learning effects.

[0004] In order to solve the above problems, an online teaching system integrating intelligent handwriting recognition, error detection, real-time feedback and personalized learning path planning was developed. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a method to solve the shortcomings of the existing online teaching system in achieving personalized learning and real-time feedback. Many systems can only provide basic writing detection and cannot deeply analyze the user's learning process and provide targeted suggestions.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an online teaching system, comprising:

[0007] Intelligent handwriting recognition module, used to capture the user's writing trajectory, detect the stroke sequence, strength, angle and writing order, and analyze the writing content;

[0008] The error detection and recording module is used to automatically identify the stroke sequence errors and handwriting deviations in the user's writing process, and record the erroneous parts;

[0009] The playback and correction module is used to playback the user's writing process after writing is completed, and display the correct writing order and strokes next to the strokes for comparison in the form of animation;

[0010] The real-time feedback module uses sensors and cameras to capture the user's hand posture and sitting posture when writing, and provides real-time correction suggestions based on the user's posture feedback information;

[0011] The personalized learning path planning module automatically recommends suitable fonts, styles and practice materials based on the user's calligraphy learning progress and error records, and provides a personalized learning plan.

[0012] Preferably, the system further includes a multi-device synchronization module, which supports users to switch seamlessly between multiple devices and synchronize users' learning progress and practice records in real time.

[0013] Preferably, the intelligent handwriting recognition module is based on pressure sensing technology and integrated with a pressure sensing device, and is capable of detecting changes in force when a user writes and providing feedback, thereby helping to simulate the pen stroke effect in calligraphy.

[0014] Preferably, the error detection and recording module can save multiple practice records, allowing the user to view the comparison of calligraphy practice in different periods and track learning progress.

[0015] Preferably, the error detection and recording module detects stroke sequence errors in user writing by the following algorithm:

[0016] First, the user's writing path is captured through the trajectory analysis algorithm, and the stroke trajectory of the user's writing is set as a vector P(t), where t is a time parameter;

[0017] The error detection and recording module calculates the angle between strokes If θ exceeds the preset correct writing angle range, it is recognized as a stroke order error and the location where the error occurs is recorded.

[0018] Preferably, the real-time feedback module can capture the user's hand movements, pen gestures and sitting posture in real time when the user is writing, and correct the posture through visual feedback prompts when it is wrong or bad.

[0019] Preferably, the intelligent handwriting recognition module includes a virtual copying function, allowing the user to select calligraphy works of famous artists for dynamic copying practice, and guiding the user in the correct writing order and structure by superimposing the original handwriting.

[0020] Preferably, the playback and correction module supports gesture and voice control, allowing the user to operate the system, switch exercise content, view feedback or playback the writing process through simple gestures or voice commands.

[0021] Preferably, the playback and correction module includes comparing the user's incorrect strokes with the correct strokes, and showing the correct writing order and stroke structure through animation demonstration.

[0022] Preferably, an online teaching method comprises the following steps:

[0023] S1: Capture the user's writing trajectory and recognize the user's stroke sequence and handwriting through the intelligent handwriting recognition module;

[0024] S2: Detect and record the errors in writing through the error detection and recording module, especially the errors in stroke order and handwriting;

[0025] S3: After writing is completed, the playback and correction module plays back the user's writing process and displays the correct stroke sequence and direction next to the incorrect strokes;

[0026] S4: Correct the user's writing posture through the real-time feedback module and give instant error prompts;

[0027] S5: Based on the user's practice performance, use the personalized learning path planning module to automatically recommend further learning content and practice materials.

[0028] Beneficial Effects

[0029] The present invention provides an online teaching system and an online teaching method. Compared with the prior art, the present invention has the following beneficial effects:

[0030] In the present invention, the intelligent handwriting recognition module uses advanced sensors and algorithms to capture the user's writing trajectory in real time, analyze multiple information such as stroke order, strength and angle, etc. The module sets the user's writing path as a vector, and uses the trajectory analysis algorithm to calculate the angle between the strokes, so as to accurately identify the stroke order errors, thereby improving the accuracy of error detection. This process can timely feedback the deficiencies in writing and help users to continuously improve in learning. Secondly, the error detection and recording module can not only automatically identify the errors made by the user in the writing process, but also record the erroneous parts in detail. This function enables users to view the comparison of multiple exercises, clarify their own learning progress and weak links, and then formulate a more effective learning plan. The introduction of the playback and correction module provides users with a review opportunity after writing is completed. Users can playback their own During the writing process, the correct writing order and structure are displayed in animated form by dynamically comparing incorrect strokes with correct strokes. This not only enhances the user's understanding of calligraphy skills, but also improves the memory effect. In addition, the real-time feedback module monitors the user's hand movements and sitting posture through sensors and cameras, and provides timely visual feedback, thereby effectively correcting the user's bad writing posture and ensuring writing quality. The personalized learning path planning module automatically recommends suitable fonts, styles and practice materials based on the user's learning progress and error records, truly realizing personalized learning. The system also supports multi-device synchronization, allowing users to seamlessly switch between different devices and synchronize learning progress and practice records in real time. The integration of this series of functions not only improves the flexibility and efficiency of calligraphy learning, but also greatly improves the user's learning experience, making calligraphy learning more intuitive and efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 A schematic diagram of a method flow of an online teaching system and an online teaching method proposed by the present invention;

[0032] Figure 2 The present invention provides a system flow chart of an online teaching system and an online teaching method. DETAILED DESCRIPTION

[0033] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] See also Figure 1 - Figure 2 The present invention provides a technical solution, which specifically includes the following embodiments:

[0035] Example:

[0036] An online teaching system and an online teaching method, comprising:

[0037] Intelligent handwriting recognition module, which is used to capture the user's writing trajectory, detect the stroke sequence, strength, angle and writing order, and analyze the writing content. It can identify the subtle differences in different writing styles and generate detailed writing data reports. These data not only help users understand their writing habits, but also evaluate specific calligraphy skills. Through continuous learning and optimization, the module can also adapt to changes in the user's writing style and provide more accurate feedback;

[0038] The error detection and recording module is used to automatically identify stroke order errors and handwriting deviations in the user's writing process, and record the erroneous parts. During the user's writing process, the module will highlight the erroneous parts and provide instant feedback to help the user correct them in time. At the same time, the module will also save the user's error records so that the user can view and analyze them at any time, helping them identify their own common mistakes and learning bottlenecks;

[0039] The playback and correction module is used to playback the user's writing process after writing is completed, and display the correct writing order and strokes next to the strokes for comparison in the form of animation. During the playback process, the system will display the correct writing order and strokes next to the user's strokes in the form of animation, helping users to intuitively compare the differences between their own writing and standard writing. Through this comparison, users can better understand the essentials of calligraphy skills and thus improve their writing level. The module can also record the user's progress and provide users with dynamic learning feedback;

[0040] The real-time feedback module uses sensors and cameras to capture the user's hand posture and sitting posture when writing, and provides real-time correction suggestions based on the user's posture feedback information, analyzing whether the user's posture meets the writing standards. If the posture is found to be bad or uncomfortable, it will be corrected in time through visual feedback, such as color changes, sound prompts or graphic instructions to guide the user to adjust. In addition, the module will also provide personalized posture suggestions based on the user's writing habits to promote the user's health and comfort during the writing process. In the real-time feedback module, sensors (such as accelerometers, gyroscopes, pressure sensors) and cameras are used to collect information such as the user's hand posture and sitting posture when writing. In order to convert these signals into feedback information, the system performs the following steps, where the sensor data collection includes accelerometers, gyroscopes, pressure sensors and cameras;

[0041] The accelerometer collects the speed and direction data of the hand movement to form a three-dimensional acceleration vector (Aπ, A y ,A z ), corresponding to the displacement speed and direction of the user's hand;

[0042] The gyroscope captures the rotational motion of the hand, outputs the angular velocity information of the hand around three axes (X, Y, and Z), and generates an angular velocity vector (w x ,w y ,w z );

[0043] The pressure sensor monitors the pressure when the user holds the pen and outputs the force value (F). This value is used to analyze whether the user's holding force is moderate and meets the requirements of calligraphy.

[0044] The camera uses computer vision algorithms to analyze the user's posture (sitting posture and hand posture), including the key point detection algorithm of the body. It uses the posture estimation model to extract the angle information of key parts such as the spine, shoulders, and elbows, and generates the sitting posture angle (such as shoulder tilt, spinal curvature, etc.) to evaluate whether it meets the healthy writing posture.

[0045] The data collected by the sensor is processed by a data fusion algorithm. For example, the acceleration sensor and gyroscope data are combined, and the complementary filter is used to fuse multi-source data to generate the comprehensive motion trajectory and angle of the user's hand. For the sitting posture data collected by the camera, the posture evaluation model is used to identify the key points of the user's body and generate the corresponding angle and position data. The preset standard sitting posture angle is compared with the actual detected sitting posture angle, the difference is calculated, and the current user data is compared with the calligraphy standard model through a formula algorithm. The posture angle comparison formula is as follows:

[0046] Δθ=θ 标准 -θ 用户

[0047] Among them, θ 标准 is the preset standard sitting angle, θ 用户 is the user's current posture angle. If the difference exceeds the set threshold, the system will remind the user to make adjustments through visualization (such as a red warning box, sound prompt);

[0048] The personalized learning path planning module automatically recommends suitable fonts, styles, and practice materials based on the user's calligraphy learning progress and error records, provides a personalized learning plan, and automatically adjusts the learning plan based on the user's practice performance to provide users with customized learning content. By continuously optimizing the learning path, it helps users effectively overcome the difficulties in calligraphy learning and improve learning efficiency. In addition, the module can also dynamically adjust the recommended content based on user feedback and progress to ensure that the learning process always remains fresh and challenging.

[0049] The system further includes a multi-device synchronization module that supports users to switch seamlessly between multiple devices and synchronize users' learning progress and practice records in real time.

[0050] The intelligent handwriting recognition module is based on pressure sensing technology and integrated with pressure sensing devices. It can detect changes in the user's writing force and provide feedback to help simulate the pen stroke effect in calligraphy.

[0051] The error detection and recording module can save multiple practice records, allowing users to view calligraphy practice comparisons at different times and track learning progress.

[0052] The error detection and recording module detects stroke sequence errors in user writing through the following algorithm:

[0053] First, the user's writing path is captured through the trajectory analysis algorithm, and the stroke trajectory of the user's writing is set as a vector P(t), where t is a time parameter;

[0054] The error detection and recording module calculates the angle between strokes If θ exceeds the preset correct writing angle range, it is recognized as a stroke order error and the location where the error occurs is recorded.

[0055] The real-time feedback module can capture the user's hand movements, pen gestures and sitting posture in real time when writing, and correct them through visual feedback prompts when the posture is wrong or bad.

[0056] The intelligent handwriting recognition module includes a virtual copying function, which allows users to select calligraphy works by famous artists for dynamic copying practice, and guides users to the correct writing order and structure by superimposing the original handwriting.

[0057] The playback and correction module supports gesture and voice control, allowing users to operate the system through simple gestures or voice commands, switch practice content, view feedback or replay the writing process.

[0058] The playback and correction module includes comparing the user's incorrect strokes with the correct strokes, and showing the correct writing order and stroke structure through animation demonstration.

[0059] The following steps are involved:

[0060] S1: Capture the user's writing trajectory and identify the user's stroke order and handwriting through the intelligent handwriting recognition module. Through the intelligent handwriting recognition module, the system captures the user's writing trajectory in real time. This module uses advanced sensor technology and image recognition algorithms to identify the user's stroke order and handwriting. Specifically, the system monitors the user's writing movements, including information such as the starting point, end point, strength, angle, and writing order of each stroke. These data not only help users understand their own writing style, but also provide basic data for subsequent error detection and learning path planning;

[0061] S2: The error detection and recording module detects and records the incorrect parts during writing, especially the incorrect stroke order and handwriting. During the user's writing process, the error detection and recording module will analyze the captured writing data in real time, automatically identify and record the errors in writing. The module pays special attention to issues such as stroke order and handwriting deviation. For example, if the user writes the character "日" with an incorrect stroke order, the system will identify this problem and mark it. All error records will be stored in the user's personal profile for the user to review and analyze later, helping them understand their common mistakes;

[0062] S3: After writing is completed, the playback and correction module replays the user's writing process and displays the correct stroke order and direction beside the incorrect strokes. After writing is completed, the playback and correction module presents the user's writing process in the form of an animation. The user can replay each step of their writing, and the system will display the correct stroke order and direction beside the incorrect strokes, helping the user intuitively understand the writing skills. This process can not only enhance the user's memory but also help them better master the basic essentials of calligraphy. In addition, the system can provide targeted improvement suggestions based on the user's playback performance;

[0063] S4: The real-time feedback module corrects the user's writing posture and gives instant error prompts. When the user's posture has an adverse effect on the writing effect, the system will provide instant visual feedback, possibly in the form of a red prompt box or a sound warning, reminding the user to make adjustments. This real-time feedback mechanism can help the user maintain the correct posture during writing, thereby improving the writing quality and avoiding muscle fatigue or injuries caused by improper posture;

[0064] S5: Based on the user's practice performance, the personalized learning path planning module automatically recommends further learning content and practice materials. The personalized learning path planning module recommends further learning content and practice materials automatically according to the user's practice performance, error records, and progress. This module uses machine learning algorithms to analyze the user's learning data, determine their weak links, and push suitable calligraphy fonts, styles, or specific practice tasks to help the user conduct in-depth learning in specific areas. Through this personalized learning plan, the user can more effectively overcome learning obstacles and improve their calligraphy level. Among them, the system generates a personalized learning data matrix based on the user's error records, stroke order, handwriting deviation, and learning progress, which is represented by the following formula:

[0065] D 用户 = { E 1 ,E 2 ,.....,E n ,P 1 ,P 2 ,.....,pm}

[0066] Among them, E n Indicates the type of error the user makes (e.g., wrong stroke order, handwriting deviation), P m m represents the user's learning progress (such as practice frequency and practice duration).

[0067] Planning output formula, based on the user's error data and progress, the system calculates the personalized learning path through weight analysis. The formula is as follows:

[0068]

[0069] Among them, wj and uj are the weights of each error type and progress respectively. The system pushes the corresponding calligraphy fonts, styles and practice materials according to the user's weak links (i.e., the error type corresponding to the maximum weight value).

[0070] Dynamic adjustment mechanism: The system continuously monitors the user's learning feedback and progress. If the user makes significant progress in a specific area, the system will dynamically adjust the weight value, reduce the recommendation frequency in that area, and increase the recommended exercises in the weak links.

[0071] When working, the intelligent handwriting recognition module uses advanced sensors and algorithms to capture the user's writing trajectory in real time, analyze multiple information such as stroke order, strength and angle, and set the user's writing path as a vector, and use the trajectory analysis algorithm to calculate the angle between strokes, so as to accurately identify stroke order errors, thereby improving the accuracy of error detection. This process can provide timely feedback on deficiencies in writing and help users continuously improve in their learning. Secondly, the error detection and recording module can not only automatically identify errors made by users during the writing process, but also record the erroneous parts in detail. This function enables users to view the comparison of multiple exercises, clarify their own learning progress and weak links, and then develop a more effective learning plan. The introduction of the playback and correction module provides users with a review opportunity after writing is completed. Users can replay their own During the writing process, the correct writing order and structure are displayed in animated form by dynamically comparing incorrect strokes with correct strokes. This not only enhances the user's understanding of calligraphy skills, but also improves the memory effect. In addition, the real-time feedback module monitors the user's hand movements and sitting posture through sensors and cameras, and provides timely visual feedback, thereby effectively correcting the user's bad writing posture and ensuring writing quality. The personalized learning path planning module automatically recommends suitable fonts, styles and practice materials based on the user's learning progress and error records, truly realizing personalized learning. The system also supports multi-device synchronization, allowing users to seamlessly switch between different devices and synchronize learning progress and practice records in real time. The integration of this series of functions not only improves the flexibility and efficiency of calligraphy learning, but also greatly improves the user's learning experience, making calligraphy learning more intuitive and efficient.

[0072] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the application should be included in the protection scope of the present application.

Claims

1. An online teaching system, characterized in that: include: Intelligent handwriting recognition module, used to capture the user's writing trajectory, detect the stroke sequence, strength, angle and writing order, and analyze the writing content; The error detection and recording module is used to automatically identify the stroke sequence errors and handwriting deviations in the user's writing process, and record the erroneous parts; The playback and correction module is used to playback the user's writing process after writing is completed, and display the correct writing order and strokes next to the strokes for comparison in the form of animation; The real-time feedback module uses sensors and cameras to capture the user's hand posture and sitting posture when writing, and provides real-time correction suggestions based on the user's posture feedback information; The personalized learning path planning module automatically recommends suitable fonts, styles and practice materials based on the user's calligraphy learning progress and error records, and provides a personalized learning plan.

2. An online teaching system according to claim 1, characterized in that: The system further includes a multi-device synchronization module, which supports users to seamlessly switch between multiple devices and synchronize users' learning progress and practice records in real time.

3. An online teaching system according to claim 1, characterized in that: The intelligent handwriting recognition module is based on pressure sensing technology and is integrated with a pressure sensing device. It can detect changes in the force of a user's writing and provide feedback to help simulate the pen stroke effect in calligraphy.

4. The online teaching system according to claim 1, characterized in that: The error detection and recording module can save multiple practice records, allowing the user to view the comparison of calligraphy practice in different periods and track learning progress.

5. The online teaching system according to claim 1, characterized in that: The error detection and recording module detects stroke sequence errors in user writing through the following algorithm: First, the user's writing path is captured through the trajectory analysis algorithm, and the stroke trajectory of the user's writing is set as a vector P(t), where t is a time parameter; The error detection and recording module calculates the angle between strokes If θ exceeds the preset correct writing angle range, it is recognized as a stroke order error and the location where the error occurs is recorded.

6. An online teaching system according to claim 1, characterized in that: The real-time feedback module can capture the hand movements, pen gestures and sitting posture of the user in real time when writing, and correct them through visual feedback prompts when the posture is wrong or bad.

7. An online teaching system according to claim 1, characterized in that: The intelligent handwriting recognition module includes a virtual copying function, which allows users to select calligraphy works of famous artists for dynamic copying practice, and guides users to the correct writing order and structure by superimposing the original handwriting.

8. An online teaching system according to claim 1, characterized in that: The playback and correction module supports gesture and voice control, allowing the user to operate the system, switch practice content, view feedback or playback the writing process through simple gestures or voice commands.

9. An online teaching system according to claim 1, characterized in that: The playback and correction module includes comparing the user's incorrect strokes with the correct strokes, and showing the correct writing order and stroke structure through animation demonstration.

10. An online teaching method, characterized in that: The following steps are involved: S1: Capture the user's writing trajectory and recognize the user's stroke sequence and handwriting through the intelligent handwriting recognition module; S2: Detect and record the errors in writing through the error detection and recording module, especially the errors in stroke order and handwriting; S3: After writing is completed, the playback and correction module plays back the user's writing process and displays the correct stroke sequence and direction next to the incorrect strokes; S4: Correct the user's writing posture through the real-time feedback module and give instant error prompts; S5: Based on the user's practice performance, use the personalized learning path planning module to automatically recommend further learning content and practice materials.

Images