Multi-user cooperative interaction virtual simulation experiment teaching platform and method

Abstract

The application relates to the technical field of teaching simulation interaction, and particularly discloses a virtual simulation experiment teaching platform and method for multi-user cooperative interaction, which comprises the following modules: an animation rendering and trigger instruction determination module, which generates all operation result rendering animations of each operation step and determines corresponding trigger touch screen instructions; a touch screen track matching module, which matches a touch feedback dynamic track coordinate sequence with a standard touch feedback dynamic track coordinate sequence of all trigger touch screen instructions of the current operation step; a rendering animation trigger module, which triggers corresponding operation result rendering animations on the interactive display end of the corresponding user based on the touch screen track matching result; an intelligent feedback and guidance module, which generates instant feedback and individualized guidance content based on all touch screen track matching results in the current experiment operation process; and a learning behavior analysis module, which generates experiment teaching optimization suggestions; the application comprehensively improves the interactivity, pertinence and teaching quality of experiment teaching, and helps teaching improvement and student learning.

Description

Technical Field

[0001] This invention relates to the field of teaching simulation and interactive technology, and in particular to a virtual simulation experimental teaching platform and method for multi-user collaborative interaction. Background Technology

[0002] In the field of education, with the rapid development of information technology, traditional experimental teaching faces numerous challenges. The limitations of experimental equipment, the constraints of experimental sites, and the inherent dangers of experimental operations often restrict students' practical exploration and application of knowledge. Virtual simulation experimental teaching, as an emerging teaching method, provides an effective way to solve these problems. It utilizes computer technology, virtual reality technology, and digital twin technology to construct realistic experimental and twin simulation environments. Through model simulation, it reproduces the physical characteristics, operational rules, and operational response logic of experimental objects, allowing students to conduct experiments in virtual scenarios. This not only breaks through the limitations of traditional experimental teaching but also provides a richer and more diverse learning experience. Multi-user collaborative interactive virtual simulation experimental teaching platforms and methods are of great significance in this context. From the perspective of educational development trends, with the increasing popularity of online education and blended learning, platforms combining digital twins and model fusion can better adapt to diverse teaching scenarios, have broad application prospects, and are expected to promote innovation and transformation in experimental teaching models.

[0003] However, existing virtual simulation experimental teaching platforms mostly rely on mouse clicks for operation, lacking a high degree of user participation and simulation in the experimental process. Even with touchscreen operation, it's impossible to accurately match the real-time multi-user haptic feedback dynamic trajectory coordinate sequence with the standard trajectory coordinate sequence, thus hindering timely and accurate judgment of student operation correctness and preventing the triggering of appropriate operation result rendering animations on the interactive display. Furthermore, there's a lack of immediate feedback on experimental results, personalized guidance, and teaching optimization suggestions, hindering the continuous improvement of teaching quality.

[0004] Therefore, this invention proposes a virtual simulation experiment teaching platform and method for multi-user collaborative interaction. Summary of the Invention

[0005] This invention provides a virtual simulation experimental teaching platform and method for multi-user collaborative interaction. The platform generates multiple operation result rendering animations for all operable methods in each step of the experimental operation process through an animation rendering and trigger command determination module, and determines the corresponding touch screen trigger commands, providing students with a visual presentation of different operation effects and laying the foundation for subsequent interactions. A touch screen trajectory matching module performs high-precision matching of the dynamic trajectory coordinate sequence of real-time tactile feedback from multiple users with a standard sequence to obtain results, accurately judging the correctness of student operations and providing a basis for subsequent modules. An animation rendering trigger module triggers corresponding animations on the corresponding user's interactive display end based on the touch screen trajectory matching results, enabling timely and accurate judgment of the correctness of student operations, enhancing students' understanding of the relationship between operations and results, improving learning efficiency, and achieving a high degree of user participation and simulation in the experimental operation process. An intelligent feedback and guidance module generates instant feedback and personalized guidance content based on all touch screen trajectory matching results after the experimental operation process ends, meeting the individual learning needs of students. A learning behavior analysis module generates experimental teaching optimization suggestions based on the instant feedback and personalized guidance content recorded in the interaction records of all interactive display ends within a preset teaching unit within a preset time period, contributing to the improvement of overall teaching quality and teaching methods.

[0006] This invention provides a virtual simulation experiment teaching platform for multi-user collaborative interaction, comprising:

[0007] The animation rendering and trigger command determination module is used to generate the operation result rendering animation of all operable methods for each operation step in the experimental operation process, and determine the trigger touch screen command for each operation result rendering animation.

[0008] The touch screen trajectory matching module is used to match the real-time received dynamic trajectory coordinate sequence of haptic feedback from multiple users with the standard dynamic trajectory coordinate sequence of haptic feedback of all touch screen commands triggered in the current operation step to obtain the touch screen trajectory matching result.

[0009] The rendering animation trigger module is used to trigger the corresponding operation result rendering animation on the corresponding user's interactive display end based on the touch screen trajectory matching result;

[0010] The intelligent feedback and guidance module is used to generate instant feedback and personalized guidance content based on the matching results of all touch screen trajectories in the current experimental operation process after the experimental operation process has been traversed.

[0011] The learning behavior analysis module is used to generate suggestions for optimizing experimental teaching based on all real-time feedback and personalized guidance content in the interaction records of all interactive display terminals under the preset teaching unit within a preset time period.

[0012] Optionally, the animation rendering and trigger instruction determination module includes:

[0013] The animation rendering submodule is used to generate an animation of the operation result of each correct operation method based on the operation parameter-result mapping table of all correct operation methods in each operation step in the experimental operation process. At the same time, it generates an animation of the operation result of each incorrect operation method based on the operation parameter-result mapping table of all incorrect operation methods in each operation step.

[0014] The instruction determination submodule is used to generate the touch screen trigger instruction for rendering animation for each operation result based on the corresponding operation method for rendering animation for each operation result.

[0015] Optionally, the touchscreen trajectory matching module includes:

[0016] The first coordinate sequence parsing submodule is used to fit the haptic feedback trajectory based on the real-time received haptic feedback dynamic trajectory coordinate sequence from multiple users, and to analyze the real-time velocity, real-time acceleration and trajectory curvature at each coordinate point in the touch screen feedback trajectory.

[0017] The second coordinate sequence parsing submodule is used to fit the standard haptic feedback trajectory of the corresponding touch screen command based on the coordinate sequence of the standard haptic feedback dynamic trajectory of all trigger touch screen commands in the current operation step, and analyze the real-time velocity, real-time acceleration and trajectory curvature at each coordinate point in the corresponding standard touch screen feedback trajectory.

[0018] The coordinate sequence matching submodule is used to obtain the first matching value between the haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence of each triggering touch screen command in the current operation step, based on the touch screen feedback trajectory and the real-time velocity, real-time acceleration and trajectory curvature at each coordinate point of the touch screen feedback trajectory, the standard touch screen feedback trajectory of each triggering touch screen command in the current operation step and the real-time velocity, real-time acceleration and trajectory curvature at each coordinate point of the standard touch screen feedback trajectory.

[0019] The touch screen trajectory matching submodule is used to obtain the touch screen trajectory matching result based on the first matching value between the haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence of each trigger touch screen command in the current operation step.

[0020] Optionally, the touchscreen trajectory matching submodule includes:

[0021] The first touch screen trajectory matching unit is used to take the trigger touch screen instruction corresponding to the largest first matching value among all kinds of trigger touch screen instructions in the current operation step as the touch screen trajectory matching result when there is at least one first matching value not less than the matching value threshold among the first matching values ​​between the haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence of all kinds of trigger touch screen instructions in the current operation step.

[0022] The continuous touch gesture recognition unit is used to input the haptic feedback dynamic trajectory coordinate sequence into the touch gesture recognition model to obtain the corresponding touch gesture probability distribution sequence when all the first matching values ​​between the haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence of all kinds of triggering touch commands in the current operation step are less than the matching value threshold.

[0023] The second touch screen trajectory matching unit is used to obtain touch screen trajectory matching results based on the touch screen gesture probability distribution sequence corresponding to the haptic feedback dynamic trajectory coordinate sequence.

[0024] Optionally, the second touchscreen trajectory matching unit includes:

[0025] The gesture sequence combination subunit is used to determine the probability value of all touch gesture types involved in each action interval in the touch gesture probability distribution sequence. It selects one touch gesture type from all touch gesture types involved in all action intervals in the touch gesture probability distribution sequence and combines them to obtain multiple hypothetical touch gesture type sequences and corresponding probability sequences of the touch gesture probability distribution sequence.

[0026] The coexistence rationality calculation subunit is used to calculate the coexistence rationality between any two touch gesture types in each hypothetical touch gesture type sequence;

[0027] The total probability calculation subunit is used to calculate the total probability of each hypothetical touch gesture type sequence based on the mean of the coexistence rationality between all pairs of touch gesture types in each hypothetical touch gesture type sequence and the corresponding probability sequence;

[0028] The touch screen trajectory matching subunit is used to obtain the touch screen trajectory matching result based on the total probability of each hypothetical touch screen gesture type sequence, the matching value between the corresponding hypothetical touch screen gesture type sequence and the touch screen gesture type sequence corresponding to all kinds of trigger touch screen commands in the current operation step, and the first matching value between the corresponding haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence of each trigger touch screen command in the current operation step.

[0029] Optionally, the coexistence rationality calculation subunit includes:

[0030] The interval gesture total determination end is used to determine the total number of interval gestures between each pair of touch gesture types in each hypothetical touch gesture type sequence;

[0031] The coexistence rationality determination end is used to take the number of occurrences of each pair of touch screen gesture types in each hypothetical touch screen gesture type sequence with the current interval total number of gestures in a large number of similar reference experimental records, the factorial of the difference between the total number of gestures in a large number of similar reference experimental records and 2, the factorial of 2, and the factorial of the total number of gestures as the quotient of the coexistence rationality between the corresponding pair of touch screen gesture types.

[0032] Optionally, the touch screen trajectory matching subunit includes:

[0033] The gesture type sequence matching end is used to determine the matching value between each hypothetical touch gesture type sequence and the touch gesture type sequence corresponding to the standard haptic feedback dynamic trajectory coordinate sequence of all kinds of triggering touch commands in the current operation step;

[0034] The probability statistics section is used to perform a weighted summation of the total probability of each hypothetical touch gesture type sequence and the total matching value between the corresponding hypothetical touch gesture type sequence and the touch gesture type sequence corresponding to the standard haptic feedback dynamic trajectory coordinate sequence of all kinds of triggering touch commands in the current operation step, so as to obtain the final probability of each hypothetical touch gesture type sequence.

[0035] The trajectory coordinate sequence matching end is used to perform a weighted summation of the first matching value between the hypothetical touch gesture type sequence corresponding to the highest final probability in all hypothetical touch gesture type sequences and the standard haptic feedback dynamic trajectory coordinate sequence of each triggering touch command in the current operation step, and the first matching value between the corresponding haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence of the corresponding triggering touch command in the current operation step, to obtain the second matching value between the corresponding haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence of each triggering touch command in the current operation step.

[0036] The touch screen command matching terminal is used to determine whether the second matching value between the standard haptic feedback dynamic trajectory coordinate sequence of at least one triggering touch screen command and the current haptic feedback dynamic trajectory coordinate sequence is not less than the matching value threshold. If so, the triggering touch screen command corresponding to the largest second matching value among all triggering touch screen commands in the current operation step is taken as the touch screen trajectory matching result; otherwise, the matching failure command is output as the touch screen trajectory matching result.

[0037] Optionally, the intelligent feedback and guidance module includes:

[0038] The Experiment Review and Evaluation Submodule is used to obtain the operation steps corresponding to the haptic feedback dynamic trajectory coordinate sequence where the final matching value is less than the matching degree threshold from all touch screen trajectory matching results in this experimental operation process after traversing the experimental operation process, and to count the total number of output matching failure commands and the corresponding operation steps in this experimental operation process.

[0039] The intelligent feedback and guidance submodule is used to generate instant feedback and personalized guidance content based on the operation steps corresponding to the dynamic trajectory coordinate sequences of all tactile feedback where the final matching value is less than the matching degree threshold, the total number of all output matching failure instructions and the corresponding operation steps.

[0040] Optionally, the learning behavior analysis module includes:

[0041] The Experimental Behavior Analysis Submodule is used to analyze at least one common problem in experimental teaching feedback based on all real-time feedback and personalized guidance content in the interaction records of all interactive display terminals under a preset teaching unit within a preset time period, and to determine the occurrence rate of each common problem in experimental teaching feedback.

[0042] The optimization suggestion generation submodule is used to generate optimization suggestions for experimental teaching based on common problems and their corresponding occurrence rates in all types of experimental teaching feedback.

[0043] This invention provides a virtual simulation experiment teaching method with multi-user collaborative interaction, comprising:

[0044] Generate multiple operation result rendering animations for all operable methods in each operation step of the experimental operation process, and determine the trigger touch screen command for each operation result rendering animation.

[0045] The real-time received haptic feedback dynamic trajectory coordinate sequence from multiple users is matched with the standard haptic feedback dynamic trajectory coordinate sequence of all triggered touch screen commands in the current operation step to obtain the touch screen trajectory matching result.

[0046] Based on the touch screen trajectory matching results, the corresponding operation result rendering animation is triggered on the corresponding user's interactive display terminal;

[0047] Once the entire experimental operation process has been traversed, real-time feedback and personalized guidance content will be generated based on all the touch screen trajectory matching results in this experimental operation process.

[0048] Based on all real-time feedback and personalized guidance content in the interaction records of all interactive display terminals under the preset teaching unit within the preset time period, suggestions for optimizing experimental teaching are generated.

[0049] The beneficial effects of this invention compared to existing technologies are as follows: The animation rendering and trigger command determination module, based on model simulation and other technologies, can generate multiple operation result rendering animations for all operable methods in each operation step of the experimental operation process, and determine the corresponding trigger touch screen commands, providing students with an intuitive presentation of different operation effects and laying the foundation for subsequent interactions. The touch screen trajectory matching module, relying on the model simulation environment, can perform high-precision matching of the dynamic trajectory coordinate sequence of multi-user real-time tactile feedback with a standard sequence to obtain results, accurately judging the correctness of student operations and providing a basis for subsequent modules. The rendering animation trigger module, based on the touch screen trajectory matching results, triggers corresponding animations on the corresponding user interaction display end, enabling timely and accurate judgment of the correctness of student operations, enhancing students' understanding of the relationship between operations and results, improving learning efficiency, and achieving a high degree of user participation and simulation in the experimental operation process. The intelligent feedback and guidance module, based on model fusion technology, can generate instant feedback and personalized guidance content based on all touch screen trajectory matching results after the experimental operation process is completed, meeting the individual learning needs of students. The learning behavior analysis module, based on real-time feedback and personalized guidance from interaction records across all interactive display terminals within a preset teaching unit over a pre-defined time period, combines this data with model fusion to generate optimization suggestions for experimental teaching, contributing to overall teaching quality improvement and methodological refinement. The platform allows multiple users to participate in virtual experiments simultaneously, collaboratively completing tasks. This helps cultivate students' teamwork, communication, and problem-solving abilities. Furthermore, utilizing technologies such as animation rendering and touchscreen trajectory matching, it provides real-time feedback on student performance, offering immediate feedback and personalized guidance to enhance learning outcomes.

[0050] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in this application.

[0051] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0052] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0053] Figure 1 This is a schematic diagram of a virtual simulation experiment teaching platform for multi-user collaborative interaction in an embodiment of the present invention;

[0054] Figure 2 This is a flowchart of a virtual simulation experiment teaching method for multi-user collaborative interaction in an embodiment of the present invention. Detailed Implementation

[0055] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0056] like Figure 1 As shown, this invention provides an implementation method for a multi-user collaborative interactive virtual simulation experiment teaching platform, comprising:

[0057] The animation rendering and trigger command determination module is used to generate the operation result rendering animation of all operable methods for each operation step in the experimental operation process, and determine the trigger touch screen command for each operation result rendering animation.

[0058] The touch screen trajectory matching module is used to match the real-time received dynamic trajectory coordinate sequence of haptic feedback from multiple users with the standard dynamic trajectory coordinate sequence of haptic feedback of all touch screen commands triggered in the current operation step to obtain the touch screen trajectory matching result.

[0059] The rendering animation trigger module is used to trigger the corresponding operation result rendering animation on the corresponding user's interactive display end based on the touch screen trajectory matching result;

[0060] The intelligent feedback and guidance module is used to generate instant feedback and personalized guidance content based on the matching results of all touch screen trajectories in the current experimental operation process after the experimental operation process has been traversed.

[0061] The learning behavior analysis module is used to generate suggestions for optimizing experimental teaching based on all real-time feedback and personalized guidance content in the interaction records of all interactive display terminals under the preset teaching unit within a preset time period.

[0062] In this embodiment, the experimental operation procedure refers to a series of coherent operational steps and sequences that must be followed to complete the entire experiment in a virtual simulation experimental teaching scenario. It covers the complete process from experimental preparation to experiment completion, with each step having its specific purpose and requirements, serving as the overall framework for students to conduct virtual experimental operations. For example, in a physics circuit connection experiment, the operational procedure consists of a series of steps, from selecting experimental equipment and connecting circuits to measuring data and recording results.

[0063] In this embodiment, the operation steps are the specific, phased operations of the refined experimental operation process. Each operation step is a key node in the experimental operation process, with relatively independent operational tasks and objectives. For example, in the above-mentioned physical circuit connection experiment operation process, "connecting the power supply and switch" and "connecting the resistor and ammeter" are specific operation steps.

[0064] In this embodiment, each operation step has all possible methods: For each operation step, there may be multiple different implementations. Some of these methods are correct, while others may be incorrect. For example, in the "measuring liquid" operation step of a chemistry experiment, the correct method is to read the graduated cylinder scale at eye level, while an incorrect method might be to read it from above or below. The platform considers all possible operation methods for each operation step to comprehensively evaluate the student's performance.

[0065] In this embodiment, the operation results are rendered as animations: the results produced by different operable methods for each operation step are displayed in animation form. Animations can intuitively present the changes in the experimental scene and the state of the experimental object after the operation, helping students understand the different consequences of different operations. For example, in a simulated cell division experiment, the process of cells dividing in an orderly manner according to normal stages under correct operation, as well as the phenomenon of abnormal cell division caused by incorrect operation, can both be made into operation result rendering animations to be shown to students.

[0066] In this embodiment, the touch screen command that triggers the rendering animation of the operation result is a command that triggers the animation display through touch screen operation, corresponding to each operation result rendering animation. When the student's touch screen operation on the interactive display meets the conditions set by the command, the corresponding operation result rendering animation will be triggered.

[0067] In this embodiment, the haptic feedback dynamic trajectory coordinate sequence is a sequence of dynamic coordinate information of finger touches on the screen recorded in real time by the system when multiple users operate the interactive display terminal via touch screen. It reflects the trajectory of finger movement during user operation, including information such as the operation path and speed.

[0068] In this embodiment, the standard haptic feedback dynamic trajectory coordinate sequence is a pre-defined sequence of standard touch screen dynamic coordinate information for each trigger touch command in each operation step. It represents the expected touch screen trajectory for a correct or specific operation and is used to compare and match it with the haptic feedback dynamic trajectory coordinate sequence generated by the student's actual operation. For example, in an operation step requiring drawing a straight line, the standard haptic feedback dynamic trajectory coordinate sequence is a series of coordinate points on an ideal straight line.

[0069] In this embodiment, the interactive display terminal is the device terminal where students perform virtual simulation experiments and receive feedback information. It may be a touchscreen computer, tablet computer, or other device with display and touch interaction capabilities. Students interact with the virtual experimental environment by performing touchscreen operations on the interactive display terminal, and simultaneously receive information such as rendered animations of operation results, real-time feedback, and personalized guidance content on the same device.

[0070] In this embodiment, traversing the entire experimental procedure means that the student completes all the steps in sequence according to the experimental procedure, performing a complete virtual experiment from start to finish. For example, when completing a virtual biological dissection experiment, the student completes all the operations of the entire process, from selecting dissection tools and performing the dissection steps to finally tidying up the specimen; that is, traversing the entire experimental procedure.

[0071] In this embodiment, real-time feedback and personalized guidance are provided: After a student completes the experimental procedure, the system generates feedback information based on the matching results of all touchscreen trajectories during the procedure. Real-time feedback is a timely response to the student's operation results, informing them whether the operation was correct or not; personalized guidance is tailored to the student's specific operational errors or shortcomings, offering improvement suggestions and learning guidance. For example, if a student makes multiple wiring errors during the experiment, real-time feedback will point out these errors, while personalized guidance might suggest that the student review circuit connection principles and provide relevant learning materials.

[0072] In this embodiment, the preset teaching unit is a basic unit that is pre-defined for analyzing and evaluating teaching conditions. It can be a class, a grade, or all students in a specific course.

[0073] In this embodiment, the preset time period is a pre-determined time range used to collect and analyze relevant data such as interaction records. This time period can be set according to teaching needs, such as a week, a month, or a semester.

[0074] In this embodiment, the interaction record is: within a preset time period, all interactive display terminals under the preset teaching unit record relevant information about the interaction between students and the virtual simulation experimental teaching platform, including students' operation steps, touch screen trajectory matching results, received instant feedback, and personalized guidance content.

[0075] In this embodiment, the experimental teaching optimization suggestions are as follows: Based on the real-time feedback and personalized guidance content in the interaction records of all interactive display terminals under the preset teaching unit within a preset time period, the learning behavior analysis module analyzes the common problems in experimental teaching feedback and their occurrence rates, and then proposes specific suggestions for improving experimental teaching. For example, if it is found that most students frequently make mistakes in a certain experimental operation step, it is suggested that teachers strengthen the explanation of this part in teaching, or optimize the guidance prompts of virtual experiments, etc., to improve the teaching quality.

[0076] Furthermore, to visualize the experimental results and make the interactive operations systematic, helping students clearly understand the correctness of operations and their corresponding consequences, the animation rendering and trigger command determination module includes:

[0077] The animation rendering submodule is used to generate an animation of the operation result of each correct operation method based on the operation parameter-result mapping table of all correct operation methods in each operation step in the experimental operation process. At the same time, it generates an animation of the operation result of each incorrect operation method based on the operation parameter-result mapping table of all incorrect operation methods in each operation step.

[0078] The instruction determination submodule is used to generate the touch screen trigger instruction for rendering animation for each operation result based on the corresponding operation method for rendering animation for each operation result.

[0079] In this embodiment, the operation parameter-result mapping table is a table that records the relationship between the parameters corresponding to different operation methods in the operation steps and the final result. The operation parameters describe the specific characteristics of the operation, such as force, angle, sequence, and time, while the result is the experimental phenomenon or state change caused by the operation. Taking the chemical experiment "heating a liquid" as an example, the operation parameters may include the heating temperature, time, and stirring frequency, while the result may be liquid boiling, color change, or precipitation. This mapping table provides the basis for generating operation result rendering animations, clarifying what results should be presented for different operation methods.

[0080] In this embodiment, an animation rendering of the operation result for each correct operation method is generated based on the operation parameter-result mapping table for all correct operation methods in each step of the experimental procedure. Simultaneously, an animation rendering of the operation result for each incorrect operation method is generated based on the operation parameter-result mapping table for all incorrect operation methods in each step. For example, in the operation step of "building a physical pendulum model," the operation parameter-result mapping table for the correct operation method may specify the relationship between parameters such as pendulum string length and pendulum bob mass and the result of the pendulum swinging normally. Based on this, an animation demonstrating the pendulum swinging normally according to the correct parameter settings is generated. The operation parameter-result mapping table for incorrect operation methods, such as pendulum string being too short or too long, pendulum bob being too heavy or too light, and the corresponding results of the pendulum swinging abnormally or even failing to swing normally, are used to generate corresponding animation rendering of the incorrect operation result. In this way, the impact of different operations on the experimental results is comprehensively demonstrated, helping students understand the difference between correct and incorrect operations.

[0081] In this embodiment, a trigger touchscreen command for each operation result rendering animation is generated based on the corresponding operation method for each operation result rendering animation: The command to trigger the animation display via touchscreen operation is determined according to the specific operation method corresponding to each operation result rendering animation. For example, for the rendering animation of the correct operation in the above-mentioned "building a physical pendulum model," if the corresponding operation method is to click on the pendulum string length, pendulum bob mass, and other setting options in a specific order on the interactive display, and then confirm the settings, then the generated trigger touchscreen command requires the student to perform touchscreen clicks in this specific order on the interactive display. When the operation conforms to the set command rules, the rendering animation of the pendulum swinging normally under the correct operation will be triggered. In this way, students can trigger the corresponding animation through touchscreen operation, realize interaction with the virtual experimental environment, and intuitively understand the connection between operation and result.

[0082] Furthermore, to achieve high-precision matching between the dynamic coordinate sequence of the touch screen feedback trajectory and the standard dynamic coordinate sequence of the touch screen feedback trajectory, accurately determine the correctness of user operations, and help improve the accuracy and efficiency of user experimental operation learning, the touch screen trajectory matching module includes:

[0083] The first coordinate sequence parsing submodule is used to fit the haptic feedback trajectory based on the real-time received haptic feedback dynamic trajectory coordinate sequence from multiple users, and to analyze the real-time velocity, real-time acceleration and trajectory curvature at each coordinate point in the touch screen feedback trajectory.

[0084] The second coordinate sequence parsing submodule is used to fit the standard haptic feedback trajectory of the corresponding touch screen command based on the coordinate sequence of the standard haptic feedback dynamic trajectory of all trigger touch screen commands in the current operation step, and analyze the real-time velocity, real-time acceleration and trajectory curvature at each coordinate point in the corresponding standard touch screen feedback trajectory.

[0085] The coordinate sequence matching submodule is used to obtain the first matching value between the haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence of each triggering touch screen command in the current operation step, based on the touch screen feedback trajectory and the real-time velocity, real-time acceleration and trajectory curvature at each coordinate point of the touch screen feedback trajectory, the standard touch screen feedback trajectory of each triggering touch screen command in the current operation step and the real-time velocity, real-time acceleration and trajectory curvature at each coordinate point of the standard touch screen feedback trajectory.

[0086] The touch screen trajectory matching submodule is used to obtain the touch screen trajectory matching result based on the first matching value between the haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence of each trigger touch screen command in the current operation step.

[0087] In this embodiment, a haptic feedback trajectory is fitted based on the real-time received haptic feedback dynamic trajectory coordinate sequence from multiple users, and the real-time velocity, real-time acceleration, and trajectory curvature at each coordinate point in the touch screen feedback trajectory are analyzed: When multiple users perform touch screen operations on the interactive display terminal, the system acquires their haptic feedback dynamic trajectory coordinate sequence in real time. These coordinate sequences are a series of discrete points, which are connected into a smooth haptic feedback trajectory using mathematical fitting methods (such as curve fitting algorithms).

[0088] For this fitted touchscreen feedback trajectory, further analysis is performed on the real-time velocity, real-time acceleration, and trajectory curvature at each coordinate point on the trajectory. Real-time velocity describes how fast the user's finger moves on the touchscreen at that point, and is obtained by calculating the displacement change of adjacent coordinate points per unit time; real-time acceleration reflects the rate of velocity change, calculated based on the velocity change at adjacent time points; trajectory curvature represents the degree of curvature of the trajectory, which reflects the turning points of the user's operation path.

[0089] In this embodiment, a standard haptic feedback trajectory corresponding to each touchscreen trigger command is fitted based on the standard haptic feedback dynamic trajectory coordinate sequence of all trigger touchscreen commands in the current operation step. The real-time velocity, real-time acceleration, and trajectory curvature at each coordinate point in the corresponding standard touchscreen feedback trajectory are analyzed. Similar to the processing of actual user operations, for all pre-set trigger touchscreen commands in the current operation step, there is a corresponding standard haptic feedback dynamic trajectory coordinate sequence. Using the same fitting method, these standard coordinate sequences are transformed into standard haptic feedback trajectories. Then, for each standard touchscreen feedback trajectory, the real-time velocity, real-time acceleration, and trajectory curvature at each coordinate point are calculated.

[0090] In this embodiment, based on the touch feedback trajectory and the real-time velocity, real-time acceleration, and trajectory curvature at each coordinate point of the touch feedback trajectory, the standard touch feedback trajectory for each triggering touch command in the current operation step, and the real-time velocity, real-time acceleration, and trajectory curvature at each coordinate point of the standard touch feedback trajectory, a first matching value is obtained between the haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence for each triggering touch command in the current operation step: the touch feedback trajectory generated by the user's actual operation and its velocity, acceleration, and curvature are compared with the standard touch feedback trajectory and its corresponding parameters corresponding to each triggering touch command in the current operation step. For example, the first matching value is obtained by constructing a matrix (each row includes the distance between each trajectory coordinate point and the origin, the corresponding real-time velocity, real-time acceleration, and trajectory curvature) and then calculating the similarity between the two matrices.

[0091] Furthermore, to further improve the matching accuracy and adaptability between the dynamic coordinate sequence of touch screen feedback trajectory and the standard dynamic coordinate sequence of touch screen feedback trajectory, the touch screen trajectory matching submodule includes:

[0092] The first touch screen trajectory matching unit is used to take the trigger touch screen instruction corresponding to the largest first matching value among all kinds of trigger touch screen instructions in the current operation step as the touch screen trajectory matching result when there is at least one first matching value not less than the matching value threshold among the first matching values ​​between the haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence of all kinds of trigger touch screen instructions in the current operation step.

[0093] The continuous touch gesture recognition unit is used to input the haptic feedback dynamic trajectory coordinate sequence into the touch gesture recognition model to obtain the corresponding touch gesture probability distribution sequence when all the first matching values ​​between the haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence of all kinds of triggering touch commands in the current operation step are less than the matching value threshold.

[0094] The second touch screen trajectory matching unit is used to obtain touch screen trajectory matching results based on the touch screen gesture probability distribution sequence corresponding to the haptic feedback dynamic trajectory coordinate sequence.

[0095] In this embodiment, the matching value threshold is a pre-set numerical standard used to determine whether the degree of matching between the haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence reaches an acceptable range. For example, the matching value threshold is set to 0.8.

[0096] In this embodiment, the touch gesture recognition model is a pre-trained model used to recognize user touch gestures on the interactive display. It is built through deep learning on a large amount of touch gesture data and its probability distribution data. Based on the dynamic trajectory coordinate sequence of the input tactile feedback, it can analyze possible touch gesture types and their probability distributions. For example, when a user performs operations such as swiping, clicking, and zooming on the screen, the model can identify the possible gesture types involved in each gesture and the probability of each gesture type based on the trajectory information. The model may use machine learning algorithms, such as neural networks, to extract and classify the features of various gestures. During training, the model learns the trajectory feature patterns corresponding to different gestures, thus enabling accurate recognition of user input gestures in practical applications. For example, when a user zooms on a virtual map, the touch gesture recognition model can determine that it is a zoom gesture based on the user's touch trajectory and provide relevant information such as the confidence level of the gesture, laying the foundation for more accurate matching of operations and providing feedback in the future.

[0097] In this embodiment, the touch gesture probability distribution sequence is the output of the touch gesture recognition model after the haptic feedback dynamic trajectory coordinate sequence is input. This sequence contains all possible touch gesture types for each action interval and their probabilities of occurrence. For example, it might output that the probability of a swipe gesture is 0.6, a tap gesture is 0.2, a rotation gesture is 0.1, and a zoom gesture is 0.1 for one action interval. It reflects the likelihood of various gestures occurring based on the current touch trajectory.

[0098] Furthermore, to further improve the matching accuracy and adaptability between the dynamic coordinate sequence of touch screen feedback trajectory and the standard dynamic coordinate sequence of touch screen feedback trajectory, a gesture type sequence matching process is introduced. Therefore, the second touch screen trajectory matching unit includes:

[0099] The gesture sequence combination subunit is used to determine the probability value of all touch gesture types involved in each action interval in the touch gesture probability distribution sequence. It selects one touch gesture type from all touch gesture types involved in all action intervals in the touch gesture probability distribution sequence and combines them to obtain multiple hypothetical touch gesture type sequences and corresponding probability sequences of the touch gesture probability distribution sequence. The total number of gestures in each hypothetical touch gesture type sequence is equal to the total number of action intervals in the touch gesture probability distribution sequence.

[0100] The coexistence rationality calculation subunit is used to calculate the coexistence rationality between any two touch gesture types in each hypothetical touch gesture type sequence;

[0101] The total probability calculation subunit is used to calculate the total probability of each hypothetical touch gesture type sequence based on the mean of the coexistence rationality between all pairs of touch gesture types in each hypothetical touch gesture type sequence and the corresponding probability sequence;

[0102] The touch screen trajectory matching subunit is used to obtain the touch screen trajectory matching result based on the total probability of each hypothetical touch screen gesture type sequence, the matching value between the corresponding hypothetical touch screen gesture type sequence and the touch screen gesture type sequence corresponding to all kinds of trigger touch screen commands in the current operation step, and the first matching value between the corresponding haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence of each trigger touch screen command in the current operation step.

[0103] In this embodiment, the action interval refers to the user's continuous touch actions during touchscreen operation, which can be divided into different stages, each stage being an action interval. These intervals are divided based on the characteristics, purpose, or time segment of the operation and contain only one type of gesture. For example, in a complex touchscreen operation, from starting to draw a shape to adjusting its size and then adding annotations, these three parts can be considered as different action intervals. The touchscreen gesture types within each action interval may differ. By dividing the action intervals, it is helpful to analyze the user's operational behavior and intentions in more detail, providing a basis for subsequently determining the hypothetical touchscreen gesture type sequence and related probability calculations.

[0104] In this embodiment, the probability values ​​of all touch gesture types involved in each action interval within the touch gesture probability distribution sequence are determined: the touch gesture probability distribution sequence output by the touch gesture recognition model is subdivided according to action intervals. For each action interval, the various touch gesture types involved and their respective probability values ​​are defined. For example, in an operation process, action interval 1 may involve three gesture types: swipe, click, and zoom, with probability values ​​of 0.5 for swipe, 0.3 for click, and 0.2 for zoom; action interval 2 may involve two gesture types: rotate and drag, with probability values ​​of 0.6 for rotate and 0.4 for drag. Through such subdivision, the user's gesture tendencies at different operation stages can be grasped more accurately, providing detailed probability information for subsequent combinations of hypothesized touch gesture type sequences.

[0105] In this embodiment, a probability sequence of touch gesture types is assumed: within each action interval of the touch gesture probability distribution sequence, any touch gesture type is randomly selected and combined to form multiple hypothetical touch gesture type sequences. For each hypothetical touch gesture type sequence, there is a corresponding probability sequence, where each probability value represents the probability of the gesture type occurring in the corresponding action interval. For example, assuming the touch gesture type sequence is "swipe-rotate", the corresponding probability sequence might be "0.5-0.6", where 0.5 is the probability of the swipe gesture in action interval 1, and 0.6 is the probability of the rotation gesture in action interval 2. This probability sequence reflects the likelihood of the hypothetical touch gesture type sequence occurring and is an important basis for subsequently calculating the total probability of the hypothetical touch gesture type sequence.

[0106] In this embodiment, the total probability of each hypothetical touch gesture type sequence is calculated based on the mean of the coexistence rationality between all pairs of touch gesture types in each hypothetical touch gesture type sequence and the corresponding probability sequence: For each hypothetical touch gesture type sequence, the coexistence rationality between all pairs of touch gesture types is first calculated, and then the mean of these coexistence rationality is calculated. Then, combined with the probability sequence corresponding to the hypothetical touch gesture type sequence, the total probability is obtained through a specific calculation method. For example, assuming the touch gesture type sequence is "ABC", the corresponding probability sequence is "P1-P2-P3", and the coexistence rationality between A and B, A and C, and B and C are calculated as R1, R2, and R3 respectively, with a mean of R. The total probability can then be calculated using the formula: Total Probability = R × P1 × P2 × P3. This total probability comprehensively considers the coexistence rationality between gestures and the probability of each gesture appearing in the corresponding action range, enabling a more comprehensive evaluation of the rationality and probability of each hypothetical touch gesture type sequence, thereby helping the system more accurately determine the user's operation intention and matching results in complex touch operation analysis.

[0107] Furthermore, to accurately quantify the reasonableness of coexistence between pairs of touch gesture types within the assumed touch gesture type sequence, a coexistence reasonableness calculation subunit is proposed, including:

[0108] The interval gesture total determination end is used to determine the total number of interval gestures between each pair of touch gesture types in each hypothetical touch gesture type sequence;

[0109] The coexistence rationality determination end is used to take the number of occurrences a1 of each pair of touch screen gesture types in a large number of similar reference experimental records with the current interval total number of gestures, the factorial of the difference between the total number of gestures n1 and 2 in a large number of similar reference experimental records, the factorial of 2, and the factorial of the total number of gestures, as the quotient of the factorial of the total number of gestures. The coexistence rationality is calculated as a1×(n1-2)!×2!÷n1!.

[0110] In this embodiment, the total number of interval gestures between any two touch gesture types in each hypothetical touch gesture type sequence is the sum of the number of other gesture types that separate any two touch gesture types in each hypothetical touch gesture type sequence. For example, assuming the touch gesture type sequence is "tap-swipe-zoom-rotate", for the two gesture types "tap" and "zoom", there is a "swipe" gesture between them, so the total number of interval gestures is 1; while "tap" and "rotate" are separated by two gestures, "swipe" and "zoom", so the total number of interval gestures is 2.

[0111] In this embodiment, similar reference experiment records are collected: a large number of past experiment records with similar properties, content, or operational requirements to the current virtual simulation experiment are collected. These records contain operational data from numerous students conducting similar experiments, including the usage of various touchscreen gesture types and their order of appearance. For example, for an operational analysis of a virtual chemistry experiment, similar reference experiment records may come from the operational records of students from different classes conducting the same or similar chemistry experiments. By analyzing these similar reference experiment records, we can understand the actual situation of the total number of different touchscreen gesture types appearing at various intervals in similar experimental scenarios. This provides a realistic basis for calculating the coexistence rationality between pairs of touchscreen gesture types in the current hypothetical touchscreen gesture type sequence, thereby judging the rationality and possibility of the current hypothetical gesture sequence in actual operation.

[0112] Furthermore, to improve the accuracy and reliability of the matching and effectively determine the matching status between user operations and standard quality, a touch screen trajectory matching subunit is proposed, including:

[0113] The gesture type sequence matching end is used to determine the matching value between each hypothetical touch gesture type sequence and the touch gesture type sequence corresponding to the standard haptic feedback dynamic trajectory coordinate sequence of all kinds of triggering touch commands in the current operation step;

[0114] The probability statistics module is used to perform a weighted summation (e.g., the total probability is weighted at 0.7 and the total matching value is weighted at 0.3) between the total probability of each hypothetical touch gesture type sequence and the total matching value (i.e., the sum of all matching values) between the corresponding hypothetical touch gesture type sequence and the touch gesture type sequence corresponding to the standard haptic feedback dynamic trajectory coordinate sequence that triggers touch commands in the current operation step, to obtain the final probability of each hypothetical touch gesture type sequence.

[0115] The trajectory coordinate sequence matching end is used to perform a weighted summation (e.g., both weights are 0.5) between the hypothetical touch gesture type sequence corresponding to the highest final probability among all hypothetical touch gesture type sequences and the standard haptic feedback dynamic trajectory coordinate sequence of each triggering touch command in the current operation step, and between the first matching value of the corresponding haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence of the corresponding triggering touch command in the current operation step.

[0116] The touch screen command matching end is used to determine whether the second matching value between the standard haptic feedback dynamic trajectory coordinate sequence of at least one triggering touch screen command and the current haptic feedback dynamic trajectory coordinate sequence is not less than the matching value threshold. If so, the triggering touch screen command corresponding to the largest second matching value among all triggering touch screen commands in the current operation step is taken as the touch screen trajectory matching result; otherwise, the matching failure command is output as the touch screen trajectory matching result.

[0117] In this embodiment, the matching value between each hypothetical touch gesture type sequence and the touch gesture type sequence corresponding to the standard haptic feedback dynamic trajectory coordinate sequence of all kinds of triggering touch commands in the current operation step is determined, including:

[0118] The more times the same gesture type appears in two sequences, the higher the matching score is likely to be. For example, if the standard sequence is "tap-swipe-zoom", and the sequence is "tap-rotate-zoom", the "tap" and "zoom" gesture types are the same, so a certain matching score can be recorded.

[0119] Order weighting: The order in which gestures appear is considered. If the order is exactly the same, the matching degree is high; if the order is significantly different, the matching degree is low. Gestures with the same order can be assigned higher weight scores, while those with different orders should have points deducted appropriately.

[0120] By taking these factors into account, a matching value is obtained through algorithms such as weighted summation to comprehensively measure the degree of matching between the two sequences.

[0121] Furthermore, to provide timely and individualized feedback and guidance, helping users clearly recognize their shortcomings, make targeted improvements, and enhance their experimental skills and understanding, an intelligent feedback and guidance module is proposed, including:

[0122] The Experiment Review and Evaluation Submodule is used to obtain the operation steps corresponding to the haptic feedback dynamic trajectory coordinate sequence where the final matching value is less than the matching degree threshold from all touch screen trajectory matching results in this experimental operation process after traversing the experimental operation process, and to count the total number of output matching failure commands and the corresponding operation steps in this experimental operation process.

[0123] The intelligent feedback and guidance submodule is used to generate instant feedback and personalized guidance content based on the operation steps corresponding to the dynamic trajectory coordinate sequences of all tactile feedback where the final matching value is less than the matching degree threshold, the total number of all output matching failure instructions and the corresponding operation steps.

[0124] In this embodiment, the final matching value is a value obtained after a series of calculations and judgments in the complex process of touch screen trajectory matching. It is used to measure the degree of matching between the haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence. It may be the first matching value or the second matching value.

[0125] In this embodiment, after the system has traversed the experimental operation process, it will analyze the matching status of all operation steps. If the final matching value corresponding to certain tactile feedback dynamic trajectory coordinate sequences is less than a preset matching threshold, it indicates that these operations deviate significantly from the standard operation. Simultaneously, the system will count the total number of failed matching commands and the corresponding operation steps. Based on this information, the system will generate immediate feedback and personalized guidance. For example, if in the "circuit connection" operation step, the final matching value is repeatedly less than the threshold and a failed matching command is output, the immediate feedback might indicate "there are many problems in the circuit connection operation," and the personalized guidance might suggest "reviewing the basic principles and steps of circuit connection, paying attention to the connection order and method," helping students recognize their operational deficiencies and guiding them to improve.

[0126] Furthermore, in order to provide targeted guidance for teaching improvement at a holistic level, help teachers accurately identify common problems in the teaching process, optimize teaching methods and strategies, improve the quality of experimental teaching, and make teaching more aligned with students' learning needs, the learning behavior analysis module includes:

[0127] The Experimental Behavior Analysis Submodule is used to analyze at least one common problem in experimental teaching feedback based on all real-time feedback and personalized guidance content in the interaction records of all interactive display terminals under a preset teaching unit within a preset time period, and to determine the occurrence rate of each common problem in experimental teaching feedback.

[0128] The optimization suggestion generation submodule is used to generate optimization suggestions for experimental teaching based on common problems and their corresponding occurrence rates in all types of experimental teaching feedback.

[0129] In this embodiment, based on all real-time feedback and personalized guidance content in the interaction records of all interactive display terminals under a preset teaching unit within a preset time period, at least one common problem in experimental teaching feedback is analyzed, and the occurrence rate of each common problem is determined: Based on a pre-defined teaching scope (such as a class, a grade, etc. as a preset teaching unit), interaction records generated by all interactive display terminals within that scope within a specific time period (pre-defined time period) are collected. These records include real-time feedback and personalized guidance content given by the system after student operations. By analyzing this large amount of content, common problems encountered by students in experimental operations are identified, i.e., common problems in experimental teaching feedback. For example, it may be found that many students frequently make mistakes in the solution proportioning operation steps of a certain chemistry experiment; this is a common problem. Then, the number of times each common problem appears in all interaction records is counted, divided by the total number of records, to obtain the occurrence rate of each common problem. For example, if the solution proportioning operation error occurs 20 times in 100 interaction records, then the occurrence rate of this problem is 20%. This process helps to grasp the weaknesses and common problems of students in experimental learning as a whole.

[0130] In this embodiment, optimization suggestions for experimental teaching are generated based on common problems and their respective proportions in all types of experimental teaching feedback. Targeted optimization suggestions are formulated based on the common problems identified in the preceding analysis and their respective proportions. For common problems with higher proportions, more attention and more detailed optimization measures are given. For example, if the common problem of "lack of proficiency in operating experimental instruments" has a high proportion (30%), while "errors in recording experimental data" has a proportion of 15%, then the generated optimization suggestions might suggest increasing the number of instrument demonstrations and providing more practice opportunities for "lack of proficiency in operating experimental instruments"; for "errors in recording experimental data," it would suggest emphasizing the standardization and importance of data recording in teaching. In this way, based on the actual problems encountered by students and their severity, specific directions for teaching improvement are provided to teachers to enhance the overall quality of experimental teaching.

[0131] like Figure 2 As shown, this invention provides a virtual simulation experiment teaching method for multi-user collaborative interaction, including:

[0132] Generate multiple operation result rendering animations for all operable methods in each operation step of the experimental operation process, and determine the trigger touch screen command for each operation result rendering animation.

[0133] The real-time received haptic feedback dynamic trajectory coordinate sequence from multiple users is matched with the standard haptic feedback dynamic trajectory coordinate sequence of all triggered touch screen commands in the current operation step to obtain the touch screen trajectory matching result.

[0134] Based on the touch screen trajectory matching results, the corresponding operation result rendering animation is triggered on the corresponding user's interactive display terminal;

[0135] Once the entire experimental operation process has been traversed, real-time feedback and personalized guidance content will be generated based on all touch screen trajectory matching results in this experimental operation process.

[0136] Based on all real-time feedback and personalized guidance content in the interaction records of all interactive display terminals under the preset teaching unit within the preset time period, suggestions for optimizing experimental teaching are generated.

[0137] The above method generates multiple operation result animations for all operable methods in each operation step and determines the trigger touch screen command. This allows students to intuitively see the possible results of different operations, helping them better understand the experimental content and clarify the operation interaction methods. Matching the dynamic trajectory coordinate sequence of multi-user real-time haptic feedback with a standard sequence to obtain touch screen trajectory matching results allows for real-time and accurate judgment of the accuracy of student operations, providing a basis for subsequent feedback and guidance. Based on the matching results, corresponding animations are triggered on the corresponding user interaction display, enhancing students' understanding of the correlation between operations and results, and improving the fun and intuitiveness of learning. After traversing the experimental process, instant feedback and personalized guidance content are generated based on the matching results, providing targeted suggestions for individual student operations, meeting the learning needs of different students, and helping students improve their operations in a timely manner. Based on the feedback and guidance content in the interaction records within a preset time period, optimization suggestions for experimental teaching are generated, providing direction for teaching improvement from an overall perspective, helping teachers optimize teaching methods, and improving the quality of experimental teaching.

[0138] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of this invention and its equivalents, this invention also intends to include these modifications and variations.

Claims

1. A virtual simulation experiment teaching platform for multi-user collaborative interaction, characterized in that, The application relates to a teaching system for an experiment operation process, which comprises the following modules: an animation rendering and trigger instruction determination module, which is used for generating operation result rendering animations of all operable methods of each operation step in an experiment operation process and determining trigger touch screen instructions of each operation result rendering animation; a touch screen track matching module, which is used for matching real-time received touch feedback dynamic track coordinate sequences from multiple users with standard touch feedback dynamic track coordinate sequences of all trigger touch screen instructions of a current operation step to obtain a touch screen track matching result; a rendering animation trigger module, which is used for triggering corresponding operation result rendering animations on an interactive display terminal of a corresponding user based on the touch screen track matching result; an intelligent feedback and guidance module, which is used for generating instant feedback and personalized guidance contents based on all touch screen track matching results in the experiment operation process when the experiment operation process is traversed; a learning behavior analysis module, which is used for generating experiment teaching optimization suggestions based on all instant feedback and personalized guidance contents in interactive records of all interactive display terminals in a preset teaching unit within a preset time period. The touch screen track matching module comprises the following sub-modules: a first coordinate sequence analysis sub-module, which is used for fitting a touch feedback track based on the real-time received touch feedback dynamic track coordinate sequences from multiple users and analyzing real-time speed and real-time acceleration and track curvature at each coordinate point in the touch feedback track; a second coordinate sequence analysis sub-module, which is used for fitting a standard touch feedback track corresponding to a trigger touch screen instruction based on the standard touch feedback dynamic track coordinate sequences of all trigger touch screen instructions of the current operation step and analyzing real-time speed and real-time acceleration and track curvature at each coordinate point in the corresponding standard touch feedback track; a coordinate sequence matching sub-module, which is used for obtaining a first matching value between the touch feedback dynamic track coordinate sequences and the standard touch feedback dynamic track coordinate sequences of each trigger touch screen instruction of the current operation step based on the touch feedback track, the real-time speed and real-time acceleration and track curvature at each coordinate point in the touch feedback track, the standard touch feedback track of each trigger touch screen instruction of the current operation step and the real-time speed and real-time acceleration and track curvature at each coordinate point in the standard touch feedback track; a touch screen track matching sub-module, which is used for obtaining the touch screen track matching result based on the first matching value between the touch feedback dynamic track coordinate sequences and the standard touch feedback dynamic track coordinate sequences of each trigger touch screen instruction of the current operation step; The touch screen track matching sub-module comprises the following units: a first touch screen track matching unit, which is used for taking a trigger touch screen instruction corresponding to a maximum first matching value among all trigger touch screen instructions of the current operation step as the touch screen track matching result when at least one first matching value in the first matching value between the touch feedback dynamic track coordinate sequences and the standard touch feedback dynamic track coordinate sequences of all trigger touch screen instructions of the current operation step is not less than a matching value threshold. The touch screen gesture continuous recognition unit is configured to input the haptic feedback dynamic trajectory coordinate sequence into a touch screen gesture recognition model when all the first matching values are less than a matching value threshold, and obtain a corresponding touch screen gesture probability distribution sequence. The second touch screen trajectory matching unit is configured to obtain a touch screen trajectory matching result based on the touch screen gesture probability distribution sequence corresponding to the haptic feedback dynamic trajectory coordinate sequence. The second touch screen trajectory matching unit includes: The gesture sequence combination subunit is configured to determine probability values of all touch screen gesture types involved in each action interval in the touch screen gesture probability distribution sequence, select any one of all touch screen gesture types involved in all action intervals in the touch screen gesture probability distribution sequence, and combine the selected touch screen gesture types to obtain a plurality of assumed touch screen gesture type sequences of the touch screen gesture probability distribution sequence and a corresponding probability sequence. The coexistence reasonableness calculation subunit is configured to calculate coexistence reasonableness between two touch screen gesture types in each assumed touch screen gesture type sequence. The total probability calculation subunit is configured to calculate a total probability of each assumed touch screen gesture type sequence based on a mean value of the coexistence reasonableness between all two touch screen gesture types in each assumed touch screen gesture type sequence and the corresponding probability sequence. The touch screen trajectory matching subunit is configured to obtain the touch screen trajectory matching result based on the total probability of each assumed touch screen gesture type sequence, a matching value between the corresponding assumed touch screen gesture type sequence and a touch screen gesture type sequence corresponding to the standard haptic feedback dynamic trajectory coordinate sequence of all trigger touch screen instructions of the current operation step, and a first matching value between the corresponding haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence of each trigger touch screen instruction of the current operation step.

2. The virtual simulation experiment teaching platform for multi-user cooperative interaction according to claim 1, characterized in that, The animation rendering and trigger instruction determination module includes: The animation rendering sub-module is configured to generate an operation result rendering animation of each correct operation method based on an operation parameter-result mapping table of all correct operation methods of each operation step in the experimental operation process, and simultaneously generate an operation result rendering animation of each error operation method based on an operation parameter-result mapping table of all error operation methods of each operation step. The instruction determination sub-module is configured to generate a trigger touch screen instruction of each operation result rendering animation based on a corresponding operation method of each operation result rendering animation.

3. The virtual simulation experiment teaching platform for multi-user cooperative interaction according to claim 1, characterized in that, The coexistence reasonableness calculation subunit includes: The interval gesture total number determination end is configured to determine an interval gesture total number between two touch screen gesture types in each assumed touch screen gesture type sequence. The coexistence reasonableness determination end is configured to take, as the coexistence reasonableness between the two touch screen gesture types, a quotient of a product of a factorial of a difference between a gesture total number in a large number of similar reference experiment records and 2 and a factorial of 2, and the gesture total number in the large number of similar reference experiment records.

4. The virtual simulation experiment teaching platform for multi-user cooperative interaction according to claim 1, characterized in that, The touch screen trajectory matching subunit includes: The gesture type sequence matching end is configured to determine a matching value between each assumed touch screen gesture type sequence and a touch screen gesture type sequence corresponding to a standard haptic feedback dynamic trajectory coordinate sequence of each trigger touch screen instruction of a current operation step; The probability statistics end is configured to add weights to a total probability of each assumed touch screen gesture type sequence and a total matching value between the assumed touch screen gesture type sequence corresponding to the standard haptic feedback dynamic trajectory coordinate sequence of each trigger touch screen instruction of the current operation step, to obtain a final probability of each assumed touch screen gesture type sequence; The trajectory coordinate sequence matching end is configured to add weights to a matching value between a maximum final probability corresponding assumed touch screen gesture type sequence in all assumed touch screen gesture type sequences and a standard haptic feedback dynamic trajectory coordinate sequence of each trigger touch screen instruction of the current operation step, and a first matching value between the corresponding haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence of the corresponding trigger touch screen instruction of the current operation step, to obtain a second matching value between the corresponding haptic feedback dynamic trajectory coordinate sequence and the standard haptic feedback dynamic trajectory coordinate sequence of each trigger touch screen instruction of the current operation step; The touch screen instruction matching end is configured to determine whether the second matching value between the standard haptic feedback dynamic trajectory coordinate sequence of at least one trigger touch screen instruction and the current haptic feedback dynamic trajectory coordinate sequence is not less than a matching value threshold in all trigger touch screen instructions of the current operation step, and if yes, the trigger touch screen instruction corresponding to the maximum second matching value in all trigger touch screen instructions of the current operation step is taken as a touch screen trajectory matching result, otherwise, a matching failure instruction is output as the touch screen trajectory matching result.

5. The virtual simulation experimental teaching platform for multi-user cooperative interaction according to claim 1, characterized in that, The intelligent feedback and guidance module comprises: The experimental review and evaluation submodule is configured to, when the experimental operation process is traversed, obtain an operation step corresponding to a haptic feedback dynamic trajectory coordinate sequence with a final matching value less than a matching degree threshold in all touch screen trajectory matching results in the experimental operation process, and count a total number of all output matching failure instructions and corresponding operation steps in the experimental operation process; The intelligent feedback and guidance submodule is configured to generate instant feedback and personalized guidance content based on the operation step corresponding to the haptic feedback dynamic trajectory coordinate sequence with the final matching value less than the matching degree threshold, the total number of all output matching failure instructions and the corresponding operation steps.

6. The virtual simulation experiment teaching platform for multi-user cooperative interaction according to claim 1, characterized in that, The learning behavior analysis module comprises: The experimental behavior analysis submodule is configured to analyze at least one experimental teaching feedback common problem based on all instant feedback and personalized guidance content in the interaction records of all interaction display ends in a preset teaching unit within a preset period of time, and determine an occurrence proportion of each experimental teaching feedback common problem; The optimization suggestion generation submodule is configured to generate experimental teaching optimization suggestions based on all experimental teaching feedback common problems and corresponding occurrence proportions.

7. A virtual simulation experiment teaching method of multi-user cooperative interaction, characterized in that, The virtual simulation experimental teaching platform for multi-user collaborative interaction according to any one of claims 1 to 6 comprises: A plurality of operation result rendering animations of all operable methods of each operation step in the experimental operation procedure are generated, and a trigger touch screen instruction of each operation result rendering animation is determined; The real-time received touch feedback dynamic trajectory coordinate sequence from the multiple users is matched with the standard touch feedback dynamic trajectory coordinate sequence of all trigger touch screen instructions of the current operation step, and a touch screen trajectory matching result is obtained; Based on the touch screen trajectory matching result, the corresponding operation result rendering animation is triggered on the interactive display terminal of the corresponding user; When the experimental operation procedure is traversed, instant feedback and personalized guidance content are generated based on all touch screen trajectory matching results in the experimental operation procedure; Based on all instant feedback and personalized guidance content in the interactive records of all interactive display terminals within a preset time period under a preset teaching unit, experimental teaching optimization suggestions are generated.

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