21 results about "Education training" patented technology

The invention relates to the technical field of information, and discloses an intelligent adaptive education training system based on big data, and the system comprises a data collection and integration module which is used for collecting learning behavior data and physiological data of learners from a plurality of education platforms and physiological data sources; the dynamic student portrait generation module is used for automatically generating and updating a dynamic student portrait according to the learning behavior data and the physiological data collected by the data acquisition and integration module; the personalized feedback and learning path optimization module is used for generating personalized learning feedback according to the dynamic student portrait and automatically adjusting a learning path by utilizing a multi-objective optimization algorithm; the system implementation and optimization module is used for detecting operation of the data acquisition and integration module, the dynamic student portrait generation module and the personalized feedback and learning path optimization module for integration, testing and optimization; and the data acquisition and integration module comprises a multi-source data integration unit.

The invention provides a digital twinborn medical education training method and system. The method comprises the following steps: generating case information and scoring rules of AI digital patients based on clinical real cases; constructing a physical training environment which comprises a training model, an environment construction object and an operation sensing device; creating a digital training environment mapped with the physical training environment in real time, wherein the digital training environment comprises an AI digital dummy and an interactive operation process; responding to operation input of the trainee in the physical training environment or the digital training environment; through a server synchronization engine, real-time bidirectional interaction between entity operation of the physical training environment and virtual operation of the digital training environment is realized; and dynamically collecting cross-environment operation data, and generating a clinical ability evaluation report based on case information and scoring rules. The method has the beneficial effects that a medical education evaluation-diagnosis-treatment full operation chain is deeply fused, the clinical practice ability is remarkably improved, and medical risks are effectively prevented and controlled.

The invention relates to the technical field of teaching evaluation, in particular to a preschool education practical teaching evaluation device and method, and the method comprises the steps: collecting a classroom thermodynamic diagram and sound source data through the synchronous starting of an infrared camera and a microphone array, carrying out the non-uniformity correction of the thermodynamic diagram, carrying out the noise reduction of the sound source data, and eliminating the environment interference; performing threshold segmentation on the thermodynamic diagram to generate a binary focus area, calculating geometric features of the area, and filtering sound source positioning data to generate a teacher movement track; pre-storing an ideal overlap ratio growth curve of each teaching stage, and dynamically adjusting a scoring weight coefficient according to the deviation amplitude of the real-time change rate and the ideal curve; and displaying a three-dimensional superposition view of the thermodynamic diagram, the teacher track and the coincidence degree change curve in real time, and generating a teaching efficiency scoring report. A thermodynamic diagram is generated in real time through the infrared thermal imaging camera, the sight focus of an infant is quantified through temperature distribution, and high-precision positioning of a voice source of a teacher is achieved through the microphone array.

The invention relates to the technical field of vocational education training systems and methods, in particular to a post practical training cultivation system and method based on AR virtual vision, which adopts AR virtual reality, creatively adopts a dynamic environment binding technology, and scans practical training scenes such as laboratories and factory stations in real time through an RGB-D camera. A 3D environment point cloud map is constructed by adopting an SLAM algorithm, virtual equipment is automatically aligned with a real desktop coordinate system, the virtual equipment can be placed on a real desktop and is constrained by a physical shielding relation, for example, a shielded part is automatically hidden when a hand passes through the virtual equipment, and compared with a traditional AR projection technology, the method is more real, the substitution sense and the training sense are stronger, and the method is more suitable for popularization and application. The training of the trainees is further effective, and the post adaptation period is shorter; a multi-modal operation evaluation mechanism is adopted, an operation track is dynamically compared with a standard path, and a deviation thermodynamic diagram is generated in real time; the decomposition operation steps comprise three stages of preparation, execution and verification, scoring is carried out respectively, and training scoring is further realized.

1. Name of the product in this design: Training Table (Vocational Education). 2. Purpose of this design: This design is intended for vocational education training and is a teaching facility. 3. The key design features of this product are its overall shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The invention relates to the technical field of simulation training, in particular to an immersive education training system based on virtual reality and augmented reality, which comprises a scene acquisition and construction module for analyzing a track to generate a virtual-real contrast chart, and a virtual-real contact fusion module for calibrating a boundary to form a stable mapping table, the teaching action mapping module is used for generating an action synchronization set by comparing paths, the training task connection module is used for integrating actions to generate a task continuous linked list, and the immersion behavior presentation module is used for scheduling multimedia elements and dynamically adjusting feedback to generate an educational training interaction state set. According to the method, virtual-real dynamic mapping is constructed by fusing the contour and the track, so that the virtual object and the real identifier are consistent in direction and stable in form, continuous association of the action track and the virtual path is maintained, the motion trend adaptively adjusts the interaction area, the action chain association ensures the training logic traceability, and the multimedia feedback delay is corrected to maintain perception synchronization. Visual connectivity and feedback accuracy are optimized, and an immersion training environment capable of being dynamically adjusted is formed.

The application relates to the technical field of vocational education training systems and methods, in particular to a post training and cultivating system and method based on AR virtual vision, which adopts AR virtual reality, innovatively adopts dynamic environment binding technology, and through real-time scanning of a training scene such as a laboratory or a factory workstation by an RGB-D camera, a 3D environment point cloud map is constructed by adopting a SLAM algorithm, virtual equipment is automatically aligned with a real desktop coordinate system, the virtual equipment can be placed on the real desktop, and is constrained by physical shielding relationship, such as automatically hiding a shielded part when a hand passes through the virtual equipment, compared with traditional AR projection technology, the system is more real, has stronger substitution and training feeling, the training of students is further effective, and the period of adapting to a post is shorter; a multi-modal operation evaluation mechanism is adopted, operation tracks are dynamically compared with standard paths, and a deviation heat map is generated in real time; operation steps are decomposed into three stages of preparation, execution and verification, and are respectively scored, and training scoring is further realized.

The invention discloses a courseware and test question integrated intelligent generation method for vocational education training, and belongs to the technical field of vocational education training. The method comprises the following steps: collecting multi-source target vocational education training data, converting the data into a structured text, and performing redundancy removal, tagging and hierarchical organization to obtain a standard structured text; core elements are extracted from the standard structured text through a natural language processing technology, attribute information is labeled, a logic relation is recognized, and a domain knowledge graph is constructed; matching a courseware template, and calling a large model to generate adaptive courseware by taking hierarchical logic of the map as a courseware outline; and extracting knowledge points and skill points in the adaptive courseware, matching exercises by combining assessment and exercise element nodes in the atlas, generating a test question package according to a preset question type and difficulty proportion, and exporting the multi-format courseware and the test question package. According to the invention, integrated intelligent generation of courseware and test questions is realized, the resource generation efficiency and post suitability of vocational education training are improved, and the consistency of learning and examination is guaranteed.

The application relates to the technical field of education training, and discloses a training subject management method and system based on knowledge classification. The system comprises a knowledge classification unit, a knowledge evaluation unit and a matching management unit. Through unique algorithms and technologies, knowledge is accurately divided into three types, namely, basic knowledge, advanced knowledge and application knowledge. For example, basic knowledge is compared by using a keyword library, advanced knowledge is constructed to calculate a correlation degree, and application knowledge is analyzed in combination with actual cases, thereby laying a solid foundation for subsequent training. A standardized evaluation process is designed for different types of knowledge, and the knowledge level of a trainer can be comprehensively understood. Different recommendation strategies are formulated according to the level of each knowledge type of the trainer, for example, excellent basic knowledge is focused on advanced and application knowledge, and large projects are recommended for excellent application knowledge, so that the learning needs of different trainers can be met, the problem of mismatched learning content is avoided, the training effect and efficiency are improved, and the knowledge and application ability of the trainer is more efficiently improved.

The invention discloses a knowledge graph construction method and system for an educational training scene, and relates to the technical field related to knowledge graphs, and the method comprises the steps: calling educational training scene information, carrying out the multi-source collection based on the educational training scene information, and obtaining a multi-source heterogeneous data set; performing knowledge extraction based on the multi-source heterogeneous data set, and constructing an initial knowledge graph; performing teaching demand matching on the initial knowledge graph according to a teaching target to generate a domain knowledge graph; and generating a teaching resource recommendation path according to the domain knowledge graph in combination with the educational training scene information, and executing the teaching resource recommendation path to formulate a visual teaching plan. The technical problem that in the prior art, educational training information is dispersed, the matching degree of teaching resources, teaching targets and student requirements is low, and consequently an educational knowledge graph is lack of accuracy and high efficiency is solved, knowledge graph construction meeting the teaching requirements is achieved, and the educational knowledge graph construction efficiency is improved. The technical effect of improving the educational knowledge graph accuracy and the educational training efficiency and quality is achieved.

The application discloses an education training scoring and optimization method based on multi-agent process collaboration training, and relates to the technical fields of intelligent education and multi-agent collaboration. The method constructs a collaborative system composed of a training guidance agent, a special evaluation agent group, an adversarial feedback agent and a global coordination agent. Through subtask decomposition of the education training task, combined with multi-modal data such as code, voice and video, the training task is evaluated in a process and multi-dimensional manner. An adversarial feedback mechanism is introduced to correct the credibility of the special evaluation results and improve the scoring robustness. Through local continuity constraints and global consistency optimization, dynamic balance between subtask scoring and overall objectives is achieved. The method can realize real-time, traceability and iterative optimization of education training scoring, improve the objectivity, fairness and generalization ability of the evaluation results, and is suitable for various online education and vocational training scenarios.

The application discloses a data-based intelligent education training management system for guiding training subjects or trainees to make up for knowledge defects existing in a training process, comprising: a collection module for collecting multi-modal information of the trainees, a creation module in communication connection with the collection module and used for establishing multi-modal learning models from the multi-modal information, an analysis module in communication connection with the creation module and used for acquiring the multi-modal models, a detection module in communication connection with the analysis module, and a decision module in communication connection with the analysis module. The system has intelligent data information collection capability, data information analysis capability, diagnosis capability, feedback capability and improvement effect evaluation capability after being built, has the characteristics of full sample, multi-dimensional and multi-modal information, reality, accompanying, individualization, instant feedback and the like, efficiently serves the trainees to efficiently learn, reduces the burden of teachers and students, and helps the trainees to solve problems existing in a learning process.

The invention discloses an educational training assessment score drift calibration method, which relates to the technical field of education and comprises the following steps: preprocessing a multi-source evidence stream to generate a structured alignment evidence stream; multi-dimensional features are extracted based on the structured alignment evidence flow and are fused to generate evidence entropy fringes; comparing the evidence entropy fringes with standard entropy fringes of a matched steady-state anchor section in a question bank, constructing a total drift potential field, and decomposing the total drift potential field into equipment, environment and acquisition link drift components; based on each drift component, calibrating the original scoring result through a nonlinear calibration function to generate a preliminary calibration score; and evaluating the credibility of the evidence entropy fringes and the coverage degree of the steady-state anchor section, selecting to execute a normal calibration mode or a self-amplitude-limiting calibration mode according to an evaluation result, and outputting a final calibration score and a score credible interval. Through drift traceability and multi-dimensional evidence fusion, root diagnosis and self-adaptive interpretable calibration of score deviation are realized, and cross-batch comparability and decision support value of assessment scores are improved.

The invention relates to the technical field of education management, in particular to an education training management system and an education training method, and the system comprises a learning condition arrangement module, a content collection module, a material revision module, a teaching arrangement module and a task monitoring module. According to the method, a knowledge point positioning mode of time anchor points is constructed through homework annotations and time consumption data, student feedback information is mapped to section numbers to form a traceable question section, the section numbers are sequentially aggregated to form a continuous content structure, logic reconstruction of teaching content in time sequence is promoted, and a docking relation is established between classroom interaction records and teaching plan texts. The method comprises the following steps: complementing missing instances or task entries in a lecture, performing semantic matching on content tags and vacant sections of a class schedule, inserting supplementary tasks into reasonable positions according to content logic, binding class hour numbers with homework states and class messages, and generating an entries list with task pointing and feedback behaviors for supervising the execution condition of teaching tasks in the whole process. And the difference section number and the corresponding class information are positioned.

The application provides a construction method of a work personnel safety education training system, and belongs to the technical field of education training, and comprises the following steps: collecting work environment data of a training enterprise in real time through an Internet of Things terminal, obtaining quality behaviors of work personnel performing work in the work environment, obtaining enterprise information of the training enterprise, analyzing training demand according to a quality ability graph of the enterprise information, and combining a preset training framework to design a safety education training system; obtaining enterprise requirements and industry standards of the training enterprise, and developing a course based on the safety education training system; establishing a training effect evaluation system according to a preset dimension, obtaining an evaluation result, and optimizing the safety education training system based on the evaluation result. The safety education training of the enterprise can be provided more targetedly.

The application belongs to the technical field of medical education training system, and particularly relates to a personalized infection control training system and method based on generative AI. The system comprises a data acquisition module, a capability portrait construction module, a knowledge generation module, a difficulty regulation module, an evaluation module, a personalized learning module, an output module and a virtual patient interaction module. The system integrates user behavior data through a federal learning mechanism, constructs a multi-dimensional capability portrait, generates layered training content using a generative large model, and dynamically adjusts the content difficulty by combining a Q-learning algorithm. The system supports VR / AR immersive training and voice interaction control, can simulate real infection scenarios and present 3D propagation consequences. Compared with traditional static teaching programs, the system has stronger adaptability, interactivity and training closed-loop capability, significantly improving the personalization and effectiveness of infection control training.

The present application relates to the technical field of power training, in particular to an education training method and system based on augmented reality, the method comprising: constructing a virtual generator set, students learning power generation technology through augmented reality equipment, and collecting learning data of the students; presenting operation parameters in real time, and dynamically adjusting display content according to the gaze points and interactive behaviors of the students; designing interactive operation exercises to learn to operate the generator set in a virtual environment; constructing a machine learning algorithm to comprehensively analyze operation scores, gaze point distribution and interactive behavior data of the students, and establishing a personalized ability model and an operation risk prediction model; based on the personalized ability model and the predicted operation risk probability of the students, the system adaptively adjusts the exercise difficulty and the prompt strategy to realize personalized learning arrangement. The present application realizes intelligent and personalized training methods for the power generation industry, and improves the safety, pertinence and effectiveness of the generator set operation training.

The invention discloses a dynamic scheduling method for optimal allocation of advanced training resources based on a vertical large model, and relates to the technical field of educational informatization and intelligent scheduling, and the method comprises the steps: collecting course outline texts, student experiment scripts and original data of a graphic processing unit real-time load, carrying out symbolization processing, and constructing a training corpus set; inputting the training corpus set into the vertical large model for low-rank adaptation adjustment, introducing a course progress gating factor, and outputting a prediction result vector; taking the prediction result vector as input, constructing a cost matrix by using an improved Hungary algorithm, and obtaining a practical training task-resource matching matrix; and issuing the practical training task-resource matching matrix to a machine room agent program, executing preemptive scheduling on the graphic processing unit container according to the validity period of the task, and returning an actual video memory occupancy value after the task is completed so as to update parameters of the vertical large model. According to the invention, high-efficiency dynamic scheduling and accurate distribution of practical training resources of colleges and universities are realized.

The present application relates to the technical field of education and training, in particular to a kind of teaching device for remote communication online education and training, including device casing, the bottom of device casing is equipped with the electric wheel rotated by drive motor drive, and the top inner wall of device casing is equipped with power box and light supplementing lamp, the upper surface of device casing is equipped with solar cell panel, and the top of solar cell panel is equipped with transparent roof, the side of device casing is movably installed with access door;Compared with prior art, by being provided with the teaching device with electric wheel, power box, light supplementing lamp, training workbench and seat component, the uniformity of teaching device can be realized, for teachers, the teaching device can be used to complete remote online training education well, without being affected by teaching environment or teaching space facilities and other factors, effectively improve the implementation quality of online training.

1. Name of the product in this design: Integrated Training Platform (Vocational Education). 2. Purpose of this design: This design is intended for vocational education training and is a teaching facility. 3. The key design features of this product are its overall shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The invention relates to the technical field of medical education training, discloses a virtual simulation training method and system for occupational protection acupuncture injury, and aims to solve the problems that existing training lacks immersive interaction, high-risk instrument special training is insufficient, and operation evaluation subjectivity and emergency disposal are disjointed. The method comprises the following steps: constructing a multi-grabbing-point virtual model of high-risk instruments such as a suture needle and a blade; the grabbing position is monitored in real time, and wrong operation is fed back; verifying instrument transmission direction compliance based on the vector included angle; detecting the simulated acupuncture injury through the collision between the dangerous area sphere and the hand point cloud; smooth adsorption and posture calibration of the instrument are realized at the target position. The system integrates a VR interaction framework and a multi-modal feedback and emergency disposal module. According to the scheme, safe immersion training, accurate operation evaluation, closed-loop emergency response and high-simulation interaction are achieved, and the occupational protection ability of medical staff is remarkably improved.