158 results about "Online teaching" patented technology

The invention discloses an online teaching interaction method based on a multi-modal knowledge graph, a medium and equipment, and the method comprises the steps: firstly collecting original teaching information, and carrying out the cross-modal semantic alignment processing, and obtaining structured teaching information; then constructing a multi-modal knowledge graph containing text concept entities, video key frame feature vectors and voice text transcription contents, and forming a concept-visual feature association edge, a concept-voice segment association edge and a cross-modal similarity association edge; converting the user interaction behavior data into a knowledge graph query vector, extracting a three-dimensional teaching situation sub-graph from the multi-modal knowledge graph, and generating progressive or comparative teaching content according to a user operation type; and finally, dynamically adjusting a teaching strategy by constructing a cognitive state tracking matrix, and generating a personalized learning navigation map. The problems of knowledge fragmentation and insufficient interaction intellectualization in virtual simulation teaching are solved, and the teaching effect of ideological and political education is improved.

The invention relates to the technical field of online network teaching, and discloses an online network teaching practice method based on a virtual technology, and the method comprises the steps: obtaining virtual scene data, and carrying out the integration and building of a dynamic knowledge graph and a multi-modal teaching resource library; learning behavior features are extracted according to the cognitive features of the learner, knowledge difficulty levels are divided, and immersive learning is guided; constructing a cognitive evaluation model, optimizing a learning path through hierarchical reinforcement learning, and generating a self-adaptive teaching instruction; collecting interaction track data to generate an operation thermodynamic diagram, and evaluating the skill mastering degree; complexity parameters of the virtual scene are dynamically adjusted, a virtual-real linkage experiment simulation environment is constructed, and skill training closed-loop feedback is achieved. The invention further relates to specific implementation modes of resource integration, cognitive feature extraction, learning path optimization and the like. According to the method, the personalized and immersive experience and skill training effect of online teaching are improved, and the method is suitable for the field of online network teaching.

The invention relates to the technical field of online teaching management, and discloses an online teaching optimization method and system based on emotion recognition, and the method comprises the steps: collecting the real-time emotion data of a learner through a multi-modal sensor, carrying out the fusion of a graph convolutional neural network to generate a feature vector, and optimizing a teaching strategy parameter through a meta-reinforcement learning model, the dynamic course generation model combines an improved genetic algorithm and a knowledge graph to optimize a teaching content sequence, and the hierarchical teaching control model realizes knowledge path planning, interactive adjustment and learning state evaluation, and generates a teaching control instruction. According to the method, personalized online teaching optimization is realized, the state of a learner can be accurately grasped, the teaching interaction mode is optimized, the course content is dynamically adjusted, the learning effect is comprehensively and accurately evaluated, the problems that traditional online teaching lacks personalization, the state of the learner is difficult to grasp and the like are effectively solved, the online teaching quality and the learning experience are improved, and the learning experience is improved. And the online education development is promoted.

The invention provides a safety training simulation rehearsal method and system based on digital twinning, and the method comprises the steps: collecting three-dimensional posture image data when a user executes a safety training plot task, mapping the data to a safety operation virtual scene, and generating a corresponding three-dimensional virtual posture image; and recognizing three-dimensional operation posture characteristics in the three-dimensional virtual posture image through a posture recognition model, and judging whether the three-dimensional operation posture characteristics meet the posture operation requirements of the corresponding safety training plot task or not. Safety training simulation rehearsal learning can be carried out on a user, AI identification can be carried out on a three-dimensional virtual posture in safety training, and whether a safety training operation action of the user reaches the standard or not is judged in a virtual environment, so that a function of carrying out evaluation according to an actual action posture of an entity model in a virtual system is realized; therefore, an evaluation effect equivalent to practical operation is achieved, users such as trainees and the like can realize virtual preview experience and assessment of safe practical operation training, and online teaching experience and learning ability of the trainees are improved.

The invention discloses a nursing medicine education system based on the Internet, and relates to the field of computer application technology and education management, and the system comprises a theory learning module which is used for achieving the online teaching and personalized learning pushing of nursing theory knowledge, the nursing skill training module is used for training and evaluating the standardized nursing operation ability of students, the virtual simulation practical training module is used for providing an immersive virtual clinical training environment, and the structured nursing document training module is used for improving the ability of the students to write standard nursing documents. The intelligent evaluation module is used for carrying out automatic, multi-dimensional and structured comprehensive evaluation on the learning and training process of students, and the system integration interface module is used for realizing data exchange and interaction between the teaching platform and an existing information system of a hospital. The system has the advantages of complete functions, closed-loop data and accurate intelligent evaluation, and can effectively improve the standardization, practicability and intelligent level of nursing education.

The invention discloses an online programming system based on large language model assistance and a teaching recommendation method, the system comprises a base model acquisition module, a problem decomposition module, an abstract modeling module, an algorithm design module, a code analysis and assistance module and an evaluation module, and is used for helping students to finish a programming task of teaching design online. And performing problem decomposition, abstract modeling and algorithm design on actual problems by using a large language model, and solving the problems encountered by students during programming. Based on the system, the invention further designs a teaching recommendation method, multi-modal data in the information classroom teaching process is collected, a dynamic three-level teaching interaction diagram of the space-time environment, knowledge resources and cognitive behaviors is established through man-machine, life and teacher-student interaction behaviors, and accurate teaching recommendation and intervention strategies of the human-in-the-loop are provided. According to the invention, a three-dimensional comprehensive teaching field for learning environment intellectual computing is established in a programming scene, and a guarantee is provided for high-quality modern education development.

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

The present invention discloses an online education student information management system based on artificial intelligence, relates to the technical field of student information management, solves the technical problem in the prior art that students in the same channel of online teaching cannot be planned based on information analysis, and specifically comprises a progress information division unit, which is used to divide student progress information, collect information within the progress and information outside the progress, and reasonably plan the progress setting of participating online students based on information analysis; a regional information analysis unit, which is used to conduct regional impact analysis based on participating online students in different regions, collect knowledge type data and knowledge progress data, and infer whether participating online students are divided into the same channel based on data analysis; a preference ability assessment unit, which is used to conduct learning preference ability assessment on online participating students, collect preference assessment information, and obtain preference ability assessment coefficients, and further perform channel division based on coefficient threshold comparison.

The invention discloses a teaching platform data security analysis method and system based on cloud computing, and relates to the technical field of data processing. The method comprises the following steps: respectively obtaining at least one operation behavior sequence of each target user; determining a first behavior habit parameter of the target user by using each operation behavior sequence; using the first behavior habit parameter, the historical behavior habit parameter of the target user and the second behavior habit parameter of the similar user to determine a first anomaly degree; under the condition that the first anomaly degree is greater than or equal to a first preset abnormal value, determining a second anomaly degree by utilizing the operation duration of the target user on each functional unit in each functional module of the online teaching platform, the operation sequence among the functional units in each functional module and the first anomaly degree; and transmitting the normal teaching platform data to the storage space of the online teaching platform according to each second anomaly degree. And the security of data transmission and management in the fields of big data resource service and internet data service can be improved.

The invention relates to a method and device for predicting online open course learner satisfaction and electronic equipment, and the method comprises the steps: predicting the online open course satisfaction of students through an MLP and RBF neural network model by using a virtual learning environment of a large-scale online teaching and learning platform and combining learning behavior data in a learning management system (LMS); the model comprises a data acquisition and processing module, a multilayer perceptron (MLP) module, a radial basis function (RBF) neural network module, a classification tree module and a control block, the data acquisition and processing module is used for generating a training and testing data set, and the MLP and RBF neural network model predicts the satisfaction degree of a learner. The MLP model carries out feature extraction through a multi-layer perceptron structure and different activation functions, the RBF model measures the distance between input data and a center by using a radial basis function to realize feature extraction, the classification tree is used for judging a prediction model to which a data point belongs, the control block integrates features from the MLP and RBF neural network models, and the RBF model is used for determining a prediction model to which the data point belongs. Experimental results show that the prediction accuracy of low-satisfaction-degree learners and high-satisfaction-degree learners can be improved at the same time through the combination scheme of the MLP and the RBF, the method can be applied to learner satisfaction degree prediction of various online open courses, an educational institution is helped to know the satisfaction degree condition of students in time, course design and teaching strategies are optimized, and the teaching efficiency is improved. And important support is provided for teaching reform and optimization in the field of online education.

The invention relates to the technical field of teaching equipment, and discloses an online teaching auxiliary device for oral language teaching of teachers, which comprises a fixed support column used for the structure and installation of all structures, a fixed support column matched with a fixed disc I for fixing a scissor-type support mechanism I, a fixed support column matched with a fixed disc II for fixing a scissor-type support mechanism II, and a fixed support column matched with a fixed disc II for fixing a scissor-type support mechanism II, the two-way transmission mechanism and the operation motor are located at the top of the fixed supporting column and matched for automatic unfolding of the first shear type supporting mechanism, and the first shear type supporting mechanism, the shear type linkage mechanism and the second shear type supporting mechanism are synchronously unfolded through the linkage column. Students can practice and cope with various situations in a safe environment, so that the adaptive capacity and decision-making skills of the students are improved, the system covers multiple aspects of oral teaching, comprehensive education content is provided from reception, reservation to dispute handling, it is ensured that the students can comprehensively understand and master various aspects of oral teaching, and the teaching efficiency is improved. And visualization and multi-sensory learning are realized.

The invention discloses a four-stream fusion production and education connection method, device and equipment and a storage medium, and the method comprises the steps: building a knowledge fusion platform based on industrial demands, business streams, data streams, finance and taxation streams and knowledge streams; the method comprises the following steps: constructing a digital platform according to a business flow, a financial flow and a tax flow in an industrial chain, forming an online teaching module according to enterprise post requirements and course contents, and fusing the digital platform and the online teaching module to obtain an industrial resource digital fusion resource; building a comprehensive platform for connecting colleges, enterprises and scientific research institutions to obtain interconnection and intercommunication resources of education and industries; based on a knowledge fusion platform, industry resource digital fusion resources and education and industry interconnection and intercommunication resources, a production and education connection resource library is constructed; and teaching tasks are carried out by using a production and teaching connection resource library. Four-stream fusion production and teaching connection is realized, seamless joint of education and industry is realized, and the quality and effect of financial education are improved.

The invention relates to the technical field of teaching systems, and particularly discloses an education quality evaluation model construction method and system, and the method comprises the steps: S1, constructing a multi-source interface; s2, constructing a pretreatment layer; s3, constructing a feature calculation layer; s4, constructing a dynamic evaluation logic layer; s5, constructing a suggestion generation layer and a structured teaching suggestion library; s6, constructing a feedback evaluation module and an optimization module; the core of the method is that a structured teaching suggestion library is introduced and a feedback evaluation and optimization module is constructed, so that education quality evaluation, teaching intervention suggestion generation, effect tracking and suggestion library optimization form a closed-loop system; therefore, the established education quality evaluation model can realize real-time and dynamic education quality evaluation of an online teaching process, and structured and personalized teaching adjustment suggestions can be generated according to an evaluation result.

The invention discloses an online teaching video production method and device based on a virtual scene, and a medium, belongs to the technical field of teaching video production, and is used for solving the technical problem of high curriculum abandoning rate caused by low construction efficiency, low content updating rate and low knowledge transmission accuracy of an existing online curriculum. The method comprises the steps of customizing a digital teacher image of a target teacher based on modeling software; wherein the digital teacher image comprises a 3D digital teacher image and a 2D digital teacher image; constructing a virtual teaching scene, and training a virtual scene model to identify a user instruction so as to adjust features in the virtual teaching scene; based on the made teaching courseware, generating a corresponding digital human control script and a voice explanation script; placing the digital teacher image and the virtual teaching scene into a virtual environment, and fusing the digital teacher image and the virtual teaching scene with the digital human control script and the voice explanation script to form a virtual teaching model; and performing video rendering on the virtual teaching model to obtain a teaching video.

The invention relates to the technical field of data processing, and provides a teaching interaction data processing method and system based on cross-device collaboration, which are used for guaranteeing the fluency and timeliness of online teaching interaction. The method comprises the following steps: acquiring a real-time interaction data set of a plurality of heterogeneous teaching terminal devices; performing cross-device cooperative task division processing on the real-time interaction data set to obtain a plurality of sub-task sets, each sub-task set corresponding to a data processing task in one teaching interaction scene; according to the device resource demand characteristics of the plurality of subtask sets and the real-time resource capacity characteristics of the heterogeneous teaching terminal devices, executing resource scheduling processing, and generating a cross-device resource allocation strategy; and based on the cross-device resource allocation strategy, performing a co-processing operation on the plurality of sub-task sets, generating integrated teaching interaction data, and distributing the integrated teaching interaction data to corresponding terminal devices.

The invention relates to the technical field of digital twinning, and provides an online teaching interaction enhancement method and system based on digital twinning, and the method comprises the steps: obtaining a user behavior data set through a multi-modal data collection device; performing space-time alignment processing on the user behavior data set, generating a virtual avatar driving data set synchronized with the user behavior, inputting the virtual avatar driving data set into a digital twinborn model of the virtual teaching scene, and driving a virtual avatar in the digital twinborn model to execute a real-time action corresponding to the user behavior; based on the real-time action of the virtual avatar and the spatial relationship data between the teaching elements in the virtual teaching scene, an interaction instruction set is generated, and the interaction instruction set is used for indicating response operation of the teaching elements in the virtual teaching scene; and adjusting interaction feedback configuration information of the virtual teaching scene according to the interaction instruction set, and updating rendering output data of the digital twin model based on the adjusted interaction feedback configuration information.

The invention relates to the technical field of online education, and discloses an online training education informatization teaching method based on big data, which comprises the following steps: S1, collecting interaction log data of an online teaching platform, a real-time evaluation system, emotion monitoring equipment and a user, and performing cleaning, standardization, noise filtering and feature extraction on the data; s2, constructing a student state vector according to the data in the step S1 so as to implement dimension reduction processing; and S3, establishing a state action model. The personalized teaching recommendation system based on big data is adopted, learning data of students are collected in real time, a learning path is analyzed and optimized through the big data technology, the technical effect of accurately matching student requirements is achieved, compared with a technical scheme in which the states of the students cannot be responded in time in a traditional education platform, recommendation content can be adjusted in real time, and the recommendation efficiency is improved. The problem that personalized teaching resource configuration is not accurate is solved.

The invention provides an excitation system, method and device for online teaching, the system comprises a data monitoring unit, a data processing unit, a reward configuration unit, a reward calculation unit and a reward issuing unit, binlog monitoring is used as reward driving, the excitation system is isolated from an online learning system, and decoupling of excitation and learning services is realized.

The invention discloses an internet-based online teaching course recommendation method and system, and relates to the field of data analysis, and the main scheme is that a learning ability index X is calculated according to a learning progress index XA, a learning initiative index XB, a family-habit cooperation index XC and a learning efficiency index XD, and the learning ability of a user can be comprehensively evaluated; the method solves the problems that course recommendation is carried out only according to initial grade, age and other information during course recommendation, but the difference between learning ability indexes such as user learning progress conditions and learning initiative is neglected, so that the course recommendation difficulty is possibly not matched with the actual ability of the user, and the course recommendation efficiency is improved. According to the method, the problem of gradual disjunction between the recommended course and the actual demand of the user due to the learning ability index X and the learning ability grade threshold set is solved, the learning ability grade of the user is judged according to the learning ability index X and the learning ability grade threshold set, and the course recommendation method is selected, so that the course recommendation accuracy can be improved, and educational resources are utilized more effectively.

The invention relates to an online education interactive teaching method and device, equipment and a medium. The method comprises the following steps: acquiring student face image data and current teaching knowledge point data, and calculating student attention parameters according to the image data to obtain student attention parameter data; knowledge point association degree data is generated through the current teaching knowledge point data; dynamic teaching adjustment strategy data is generated based on the student attention parameter data and the knowledge point correlation degree data, teaching feedback operation is executed according to the strategy data, a teaching feedback execution result is obtained, and the teaching feedback operation comprises interface thermodynamic diagram superposition and micro-test insertion. According to the method, through the facial image data of the students and the teaching knowledge point data, not only can the attention of the students be accurately quantified and the association degree of the knowledge points be scientifically evaluated, but also a dynamic teaching strategy can be generated and feedback operation including thermodynamic diagram superposition and micro-test insertion can be executed, so that the pertinence, interactivity and effectiveness of online teaching are remarkably improved.

The invention relates to a personalized feature enhanced emotion recognition method, and belongs to the field of online education emotion calculation. According to the method, on the basis of extracting student facial expression image spatial features, emotion association of different image frames in a time dimension is captured by using a bidirectional long-short-term memory network, and effective student facial spatial-temporal features are obtained; and on the basis of a psychological'big five personality 'theory, personalized personality features hidden in student facial expressions are mined by using a deep residual network and are fused with facial features, so that student emotion classification is realized for references of teachers. According to the method, the accuracy of student learning emotion recognition is improved, the problem of unsmooth teacher-student emotion exchange in online teaching can be effectively relieved, the teacher is helped to master the student classroom state in online teaching, and the teaching implementation quality is improved.

The invention discloses an intelligent teaching effect evaluation system based on student behavior data, and relates to the technical field of teaching effect evaluation, and the system specifically comprises a behavior data extraction module, a course classification module and a teaching quality evaluation module, the course classification module is used for extracting teacher behavior characteristics according to classroom speaking duration, speed and blackboard-writing frequency of teachers, setting teaching indexes based on the teacher behavior characteristics and classifying offline behavior data through the teaching indexes, and the teaching quality evaluation module is used for evaluating teaching quality of the teachers. The system is used for integrating offline behavior data of different curriculum types, setting offline teaching evaluation indexes, setting online teaching evaluation indexes according to online behavior data and comprehensively evaluating the teaching quality of teachers, and intelligent teaching quality evaluation is achieved by integrating online and offline data.

The invention discloses an online teaching method and system suitable for laser cutting, and relates to the technical field of laser cutting. The method comprises the following steps: S1, running a generated G code cutting file, pausing and recording a line number at a deviation position between a theoretical cutting point and an actual cutting position, selecting a preset operation mode for adjustment according to displayed data, and after adjustment is completed, covering an original file with edited data and reloading; or S2, a cutting program is input in a software editing interface, cutting parameters are set, the cutting parameters comprise the cutting speed and the process type, a cutting head is moved to a designated position to execute a cutting instruction, and by inserting related instructions and macro programs in a display list, definition and editing of all cutting contours are completed, and a G code program is generated. Through real-time deviation adjustment, a simplified operation process and a flexible adjustment mode, the precision, the adaptability and the operation convenience of the laser cutting process are improved, and the working efficiency and the cutting quality are remarkably improved.

The invention discloses a teaching assistance system and method based on online learning behavior data analysis, and relates to the technical field of online teaching assistance, and the method comprises the steps: obtaining online learning platform related data and historical classroom management data, calculating a student classroom concentration risk index according to the data, and judging whether a special mark exists or not; setting a monitoring period, adjusting according to the student marking condition, counting the duration of a first abnormal behavior by using face recognition, constructing a model to recognize the abnormal behavior, recording the screen content switching condition, counting related data after class, and calculating a first adjustment index; counting the post-class job completion rate and accuracy of the history, calculating a second adjustment index, and combining the second adjustment index to obtain a comprehensive adjustment index to adjust the post-class job difficulty; and finally, counting chapter throughout data, calculating a knowledge throughout proportion, and distributing corresponding after-class exercises for the students according to the knowledge throughout proportion. According to the teaching assistance method, on the basis of online learning behavior data analysis, the difficulty of after-class homework is dynamically adjusted, and after-class exercises are accurately distributed.

The present invention discloses an automatic extraction system and method for online teaching information based on cloud computing, which relates to the technical field of online course knowledge extraction, and includes the following steps: collecting the video subtitle file of the course video and the comment data of the course video to obtain the course-related text data; and performing keyword extraction to obtain the course-related knowledge point data; obtaining the playback-related data of historical users learning the course video, and performing classification and screening processing on the historical users to obtain relevant user data; and performing level division processing on the course-related knowledge point data to obtain the course-level knowledge point data; The present invention is used to solve the problem that the existing online course video knowledge point extraction technology cannot accurately divide the difficulty and importance of professional terms according to the actual situation of users when extracting and dividing the key points and difficulties of professional terms in the course video, and cannot be adjusted in time according to the change of the user state based on the teaching content.

The application discloses a kind of teaching and learning behavior data support under causally driven dynamic organization method and system of teaching resources, and the method comprises the following steps: obtaining online teaching and learning behavior data, the online teaching and learning behavior data include teaching activity data, student learning data and online education resource information;According to the online teaching and learning behavior data, resource access dynamic time sequence causality is modeled, and the causality information of online education resource access is determined;According to the causality information, the online education resource access heat is predicted by neural network;According to the online education resource access heat obtained by prediction, the file level teaching and learning behavior data support under causally driven dynamic organization process of teaching resources is constructed, to realize the causally driven dynamic organization of teaching resources under teaching and learning behavior data support.The application can effectively improve the education user data access efficiency, and can be widely applied in the field of computer technology.

The present invention discloses a webcam and alarm system for online teaching, specifically in the field of online teaching, which is used to solve the problem of online teaching quality analysis. Through image processing and deep learning technologies, the facial expressions and upper body movements of each student can be completely captured in the teaching video, improving the image processing efficiency and the accuracy of feature recognition, ensuring data integrity, and providing a reliable basis for behavior analysis and engagement assessment. Combining Haar cascade classifier, VGG-Face and SVM classification technologies, it accurately identifies and analyzes the emotions and behaviors of students, optimizes teaching content and methods, and enhances students' engagement and satisfaction. Using clustering algorithms to analyze the student participation time series, identify teaching peaks and troughs, evaluate the teaching effect through the teaching quality index, guide teaching adjustments, enhance the pertinence and effectiveness of curriculum design, improve teaching transparency and adjustability, and better respond to students' needs.

This invention discloses a method and system for application design transformation based on technological experience, relating to the field of digital technology. The method includes: collecting open-source technology product data via the internet to construct a digital technology experience center; providing online technology experiences for students to obtain experience monitoring data; designing online courses based on a technology application creation platform to obtain online teaching courses; teaching students to obtain technology application concept design proposals; conducting simulation verification and evaluation through a mechanism simulation system to obtain simulation evaluation results for the design proposals; presenting the technology application concept design proposals in a roadshow to obtain a design demonstration dataset; conducting online expert evaluation; and transforming the technology application concept design proposals into innovative achievements based on the evaluation results. This addresses the technical problems of limited teaching resources, limited practical scenarios, and restricted technological innovation capabilities in existing science and technology education, achieving the technical effect of enriching technological experiences and enhancing technological innovation capabilities.

To provide a system for supporting an examinee to study an examination by using generative artificial intelligence.SOLUTION: The system includes a user interface means for inputting a school of choice and basic information of an examinee, an examination question generation means for automatically generating examination questions based on the school of choice information of the examinee, an analysis means for analyzing a trial result answered by the examinee and visualizing an unskillful field and a weak point, an answer explanation means for generating and displaying an explanation based on an analysis result, a teaching material recommendation means for recommending an online teaching material suitable for a learning situation of the examinee, and a similar question generation means for automatically generating similar questions based on the unskillful field of the examinee.SELECTED DRAWING: Figure 1

The invention provides an environmental art design course teaching quality monitoring method based on online data, and relates to the technical field of education, and the method comprises the steps: collecting the teaching data of an environmental art design course in real time through an online teaching platform, including the student participation degree, the homework submission condition, the online test score, the classroom interaction record and the teacher teaching feedback; and according to the teaching data, through clustering analysis and association rule analysis, constructing a teaching quality monitoring model so as to analyze the relationship between the online data and the teaching quality. According to the invention, teaching data are collected and analyzed in real time, a teaching quality monitoring model is constructed, teaching problems are accurately identified, timely feedback is provided to guide teaching improvement, a monitoring scheme is dynamically adjusted to adapt to teaching changes, and teaching quality is guaranteed and continuously improved.