46 results about "Individualized learning" patented technology

The invention provides an anesthesia virtual simulation training system fusing knowledge, skills and a thinking closed loop. The anesthesia virtual simulation training system comprises a medical knowledge base module, a clinical thinking module, a skill training module, an examination question brushing module, a knowledge graph module and an intelligent platform bottom layer framework. The intelligent platform underlying architecture comprises a data middle platform, an AI engine and a 3D engine, collects student behavior data of each module, constructs a dynamic student ability portrait through a gradient boosting tree algorithm and a collaborative filtering recommendation model, analyzes knowledge blind areas and skill shortages, plans a personalized learning path and pushes targeted training content, and provides a personalized learning result. A closed-loop process of evaluation, learning, practice and re-evaluation is formed; and deep fusion of theoretical knowledge, clinical thinking and skill operation is realized through a cross-module collaboration mechanism. The problems that traditional anesthesia teaching is high in practical operation risk, scattered in resource and insufficient in individuation are solved, and the clinical comprehensive ability and teaching quality of anesthetists are effectively improved.

The invention relates to the technical field of intelligent education, in particular to a personalized learning path planning method fusing artificial intelligence and education big data, and the method comprises the steps: collecting multi-modal education data of learning behavior data, cognitive process data and emotional state data from a learning terminal; constructing a learner portrait feature vector based on the preprocessed multi-modal education data; establishing a knowledge graph, and dynamically updating a weight matrix based on group learning data; and taking the learner portrait as a state space, taking a learning path decision as an action space, taking a learning effect as a reward function, generating a personalized learning path by adopting near-end strategy optimization, optimizing a path planning model, and generating a recommendation result. Personalized learning path planning is realized by constructing a multi-modal data fusion framework, a dynamic knowledge graph and an intelligent planning method.

The invention relates to the technical field of artificial intelligence and intelligent teaching, and discloses a self-adaptive intelligent teaching path planning method and system for personalized learning, and the method comprises the following steps: synchronously collecting multi-modal data streams in intelligent glasses and an intelligent earphone worn by a learner; identifying an immediate learning disorder of the learner based on the data stream; selecting and executing a teaching intervention strategy according to the obstacle, and monitoring a feedback behavior after intervention; an effectiveness score representing the intervention effect is quantitatively generated, and a strategy preference model is dynamically optimized based on the score; and according to the obstacle frequency of long-term statistics, the macroscopic learning path is adjusted. According to the method, a sensing, decision-making, evaluation and optimization closed loop is constructed, so that microscopic adaptive optimization of a teaching intervention strategy is realized, and instant difficulties encountered by learners can be accurately solved in real time. Meanwhile, dynamic adjustment of a macroscopic learning path is realized through analysis of long-term learning data.

The invention belongs to the technical field of intelligent education, and discloses a personalized learning path intelligent planning system, which comprises a data acquisition module used for acquiring learning activity data, user behavior data and learning result data; the data processing module is used for preprocessing the collected learning activity data, user behavior data and learning achievement data to obtain a learning activity feature data set, a user behavior feature data set and a learning achievement feature data set; the learning fitness prediction module is used for fusing the learning activity feature data set, the user behavior feature data set and the learning achievement feature data set to obtain a comprehensive feature data set; a learning fitness prediction model is trained and constructed according to the comprehensive feature data set, and the learning fitness of the user is obtained through prediction of the learning fitness prediction model; each learner provides a personalized learning path and recommendation, so that learning better meets personal requirements, and the learning effect and efficiency of the learner are improved.

The application belongs to the technical field of artificial intelligence, and specifically relates to an intelligent device online language teaching translation system based on image recognition, which discards the disadvantages of isolated recognition of characters or objects in images in the prior art, fuses visual information with accurate geographical positions, queries a scene-based expression rule set associated therewith, generates scene-based translation data flow and returns to a terminal device, first realizes deep perception and semantic understanding of a real physical environment by a translation system, and introduces individualized correction operation before driving and displaying at the terminal device, so that the final translation result is most applicable and understandable to a current user while taking into account an environmental context, the interaction behavior of the user is recorded synchronously, the decision logic of a scene cultural context is dynamically adjusted, the system realizes an intelligent closed loop of self-evolution, and long-term and continuously evolving individualized learning experience is provided for the user.

We provide the system. [Solution] A means for analyzing learner information received by a data processing device and generating an individualized learning plan, A means for dynamically generating test questions based on the generated learning plan, A means of monitoring learners' learning progress and providing real-time feedback, A system that includes this.

The invention discloses a disabled elderly body position intelligent control system based on deep learning posture recognition, and the system comprises a multi-mode perception collection module which is used for generating a multi-mode input data set; the topology voltage field feature extraction module is used for carrying out topology preserving mapping and generating a topology voltage field feature sequence; the body position time sequence recognition module is used for outputting a body position category, a posture change trend and a body position risk index through an improved Mamba model; the body position safety potential energy calculation module is used for generating a potential energy distribution result; the body position micro-action control module is used for generating a micro-action instruction, executing small-angle displacement and updating risk indexes in real time; and the individualized learning optimization module is used for storing the identification result, the risk index and the control record and continuously optimizing the parameters of the Mama model. Through an improved Mama model and a potential energy control mechanism, precise recognition and safe self-adaptive regulation and control of the body position of the disabled old person are achieved.

We provide the system. [Solution] An artificial intelligence means for collecting user information and generating an individualized learning plan based on said information, A user interface means that provides the user with an interactive learning experience based on the aforementioned learning plan, A business plan development support tool that analyzes users' business ideas and provides feedback on improvement suggestions, A means of forming a network for collaborating with other users on projects, Resource management tools that provide financial support and mentoring for projects, A system that includes this.

We provide the system. [Solution] Information processing means for receiving learner information and generating an individualized learning plan, A planning means for presenting learning items based on the learning plan, taking into consideration the appropriate timing for relearning; Information analysis means for monitoring learners' learning progress and emotional state, and for providing psychological support, A display means that uses a portable information terminal to display personalized learning information to the user in real time and allows for two-way information exchange, A synchronization mechanism for periodically collecting learner progress data and sending it to a dedicated server, A system that includes this.

To provide a system for reducing the labor of a protector, and for effectively supporting the middle school examination of a child.SOLUTION: The system includes means for receiving necessary information input by the user and registering data, means for receiving a small test or a result of a class and analyzing data to create a user profile, means for specifying a weak point or a strong point of the user to create an individual learning plan, means for evaluating a progress status from an input learning progress and generating a recovery plan by the server, means for proposing a school of choice based on the characteristics, results, and progress of the user, and means for displaying the progress status and feedback of the user in a dashboard format.SELECTED DRAWING: Figure 1

The invention discloses a dynamic explanation partner training method and system for learning emotion recognition, and relates to the technical field of man-machine interaction education application, and the method comprises the steps: collecting multi-modal data, including face video data, voice audio data and interactive text data, of a learner in a learning process in real time; performing emotional state recognition based on the multi-modal data, and generating an emotional state signal carrying a credibility mark; based on the emotional state signal and the credibility, in combination with the learning task context of the learner, a teaching intervention strategy is generated through a dual-core decision-making mechanism, and the dual-core decision-making mechanism comprises a white box decision based on a preset rule and a black box decision based on a time sequence prediction model. The technical problems that an existing learning partner training tool is one-sided in emotion capture, lack of individuation in intervention and incapable of pre-judging learning contusion are solved, and the technical effects that individualized learning partner training better meets the requirements of learners, and learning assistance accuracy and effectiveness are improved are achieved.

We provide the system. [Solution] A means of storing the analyzed educational information in a database, A means for generating new test questions using a generation device, A means of identifying areas of weakness based on the answer information of individual learners, A means of providing a learning plan based on identified areas of weakness, A system that includes this.

The application discloses a big data-based intelligent education guidance evaluation system and method, belongs to the technical field of intelligent education and big data analysis, and comprises a multi-source heterogeneous education data acquisition module, a data preprocessing and feature fusion module, a multi-dimensional capacity evaluation module, a learning behavior sequence analysis module, an individualized guidance recommendation module and a multi-role visual display module. The method integrates multi-source data through a time sequence self-adaptive alignment algorithm, realizes five-dimensional comprehensive capacity evaluation by adopting a subjective and objective fusion weighting algorithm and a double-flow attention knowledge tracking algorithm, performs learning behavior time sequence modeling by using a key behavior node identification algorithm, and generates an individualized learning path by a cognitive load perception path optimization algorithm. The application solves the problems of single evaluation dimension, fragmented data acquisition and lack of data support for individualized guidance in the existing education evaluation system.

We provide the system. [Solution] An information processing device that collects and analyzes student learning data, An information processing device that generates an individualized learning plan based on the above analysis, A presentation device that outputs learning content based on the aforementioned learning plan, A communication device that provides real-time feedback on the learning content, A voice dialogue device that uses speech recognition technology to analyze students' questions and provide learning support, A system that includes this.

Provide a system. 【Solution means】 Means for collecting learning information of individual learners, Means for analyzing the collected learning information to identify the learners' strong and weak areas, Means for generating an individualized learning plan suitable for the learner based on the identified strong and weak areas, Means for presenting the generated individualized learning plan to the learner, Means for providing an immediate response to inquiries from the learner, Means for notifying the learner's learning progress, Means for providing an individually optimized learning experience in the local community where the learner resides, Means for sharing the learner's educational progress with parents or educational institutions, A system including the above.

We provide the system. [Solution] Means for collecting learner activity data, A means for analyzing the aforementioned activity data to generate an individualized learning plan suitable for the learner, A means of delivering learning content based on the generated individual learning plan, A means of collecting learner feedback and dynamically adjusting the learning plan, A means of visualizing and providing learning progress to learners, A system that includes this.

The invention is suitable for the technical field of collection training, and provides a self-adaptive collection learning path planning method and system, and the method comprises the steps: constructing a three-dimensional procurement capability model containing compliance operation, a negotiation strategy and risk management and control, decomposing the procurement capability model into capability units, and setting a quantitative index; collecting operation, decision and assessment data in the simulation scene in real time, and generating a dynamic capability assessment matrix; constructing a three-dimensional space model based on the matrix, calculating the association strength and the lifting priority of the power unit, and outputting a personalized learning path; recombining the knowledge module according to the evaluation value change of the capability unit; dynamically adjusting model parameters in combination with policies and industries and re-planning a path; a cross-dimension learning path is generated when the plurality of capability units reach the standard. According to the method, dynamic evaluation, personalized path adjustment and cross-dimension capability integration can be realized, the problems of one-sided evaluation, fixed path and insufficient adaptability in the prior art are solved, and the accuracy and efficiency of auditory collection training are improved.

The embodiment of the invention provides a dynamic learning planning teaching system and method based on multi-model agent cooperation, and relates to the technical field of intelligent education. According to the system, description information input by a user is obtained through a dynamic test question searching module, and a test question set is retrieved in a test question bank. And identifying wrong question data through a test paper dynamic analysis module, generating a structured wrong question bank through a wrong question mastering degree analysis module, and dynamically adjusting review interval parameters according to an interval repetition algorithm based on memory cards and answer data in the structured wrong question bank, so that a learning planning module generates learning task planning data. According to the system, a complete closed-loop teaching mode of question finding, wrong question, mastery degree analysis and question exercising can be constructed through a large language model, retrieval enhancement generation, YOLO image segmentation, an interval repetition algorithm and the like, dynamic test question searching, wrong question reason analysis, mastery degree tracking and personalized learning planning are achieved, and the accuracy of a recommendation result is improved.

The invention discloses a self-adaptive learning path recommendation system and a head-mounted device, and belongs to the technical field of intelligent education, the system comprises a multi-modal data acquisition module, a signal feature fusion module, a knowledge graph management module and a self-adaptive path recommendation module, electroencephalogram signals, visual behaviors and learning content data are synchronously collected through a head-mounted device, a fusion feature vector is generated by adopting a signal quality adaptive weighted fusion strategy, the knowledge mastery degree is evaluated based on a deep learning model, and a dynamic knowledge graph is updated in real time. According to the method, the recommendation priority is calculated by integrating the mastery gap, the knowledge importance, the dependence emergency degree, the forgetting risk and the fatigue state, dynamic planning and closed-loop adjustment of a personalized learning path are realized, the mastery evaluation accuracy and the learning efficiency are remarkably improved, and meanwhile, the data privacy security is guaranteed.

The present invention provides a method for providing individualized and interactive remote education and a system thereof. The method includes the steps of: storing educational materials and links to remote databases and / or library resources; providing educational materials to the educational material database and updating the educational materials stored in the educational material database; maintaining a user profile for each user; generating an individualized learning program for each user based on the user profile; and autonomously producing content to the user and forwarding user feedback via a generative artificial intelligence (AI) module.

We provide the system. [Solution] A means for generating an individualized learning plan, Means for tracking and recording learners' progress, An information processing device for presenting learning content based on a generated learning plan, A means of providing rewards according to learning progress, A means of communication for receiving and resolving questions during learning, An educational support system that includes this.

We provide the system. [Solution] A computation means for analyzing the learner's learning progress and level of understanding in real time, A distribution method that dynamically provides educational materials optimized for learners, A dialogue device that accepts inquiries in natural language and generates responses immediately, A visualization method for visualizing the setting and achievement of learners' learning goals, A display device that shows educational materials in various formats, A proposal device that suggests individualized learning content for a specific social group, A system that includes this.

The application discloses a dynamic explanation accompanying training method and system for learning emotion recognition, relates to the technical field of human-computer interaction education, and comprises the following steps: collecting multi-modal data of learners in a learning process in real time, including facial video data, voice audio data and interactive text data; performing emotion state recognition based on the multi-modal data, and generating an emotion state signal carrying a confidence mark; generating a teaching intervention strategy through a dual-core decision mechanism based on the emotion state signal and the confidence, in combination with a learning task context of the learner; and the dual-core decision mechanism comprises a white-box decision based on a preset rule and a black-box decision based on a time sequence prediction model. The application solves the technical problems of one-sided emotion capture, lack of individualized intervention and inability to predict learning setbacks of existing learning accompanying training tools, and achieves the technical effects of making individualized learning accompanying training more suitable for the needs of learners and improving the accuracy and effectiveness of learning assistance.

The invention relates to the field of medical images, and discloses a mobile DR intelligent dose control and automatic exposure system which comprises a pre-exposure anatomical modeling module, a dynamic exposure control module and a post-exposure self-optimization module. Before exposure, the system constructs a three-dimensional anatomical model by using multi-modal data, and generates an initial AEC target matrix containing a plurality of virtual regions of interest. At the moment of exposure, the system carries out one-time accurate correction on a matrix deviated from the movement of the patient. During exposure, the system monitors the dose in parallel according to the corrected matrix to terminate exposure. After exposure, the system evaluates image quality, and combines scores with patient sign parameters obtained before exposure to update an independent dose correction model instead of a standard database, so as to realize closed-loop self-optimization. According to the method, the problem of exposure misalignment caused by movement of the patient is solved, the image quality consistency is improved through a robust individualized learning mechanism, and accurate dose optimization is realized.

We provide the system. [Solution] A means of receiving educators' skill information and learning objectives, and creating individual training plans based on that information, A means of collecting and providing the latest education-related materials to users in conjunction with external educational databases, A means for analyzing lesson information and learner response information to judge the educator's performance and generate feedback, A means of providing an electronic bulletin board for exchanging information with other educators, A means for searching for and displaying career information related to education, A means of providing individualized learning plans and monitoring education using home-use information processing devices to support users' learning, A system that includes this.

The application relates to the technical field of sleep monitoring, in particular to a progressive sound therapy scene generation method and system for sleep disorder intervention. The method comprises the following steps: acquiring multi-modal sleep monitoring data in a user's sleep process and performing preprocessing, extracting sleep stability feature parameters and micro-awakening precursor feature parameters; performing weighted fusion analysis based on the same, determining a risk value of a micro-awakening event occurring in a future prediction window; determining a risk level based on the same and matching corresponding scene control parameters; judging whether to switch the risk level based on an entry threshold and an exit threshold; after confirming the entry of the risk level, generating a target sound scene by progressively adjusting a current sound scene; and updating a risk determination threshold, feature weights and a scene control parameter group according to an actual sleep state after the prediction window ends. The application continuously improves the accuracy of prediction and intervention through individualized learning, thereby effectively improving the continuity and stability of overnight sleep.

The system according to the embodiment aims to provide learners with individualized learning plans and to support them efficiently. [Solution] A system according to an embodiment includes a reception unit, a generation unit, and a support unit. The reception unit receives input of study content from a user. The generation unit analyzes the information received by the reception unit and generates a study plan. The support unit provides interactive support based on the study plan generated by the generation unit.

The invention relates to the technical field of education data mining and intelligent education, and discloses a cognitive diagnosis method based on parallel modeling of a state path and a cognitive path, and the method comprises the steps: obtaining historical interaction behavior data of a student, extracting a learning state from the historical interaction behavior data, and generating a structured state representation, the answer tendency Psta of the student in the current state is predicted; interactive data at the current moment are input into MLP to output a basic cognitive prediction result Ccog, and the basic cognitive prediction result Ccog and the state adjusting quantity Meff are fused to obtain an answer tendency Pcog based on cognitive ability to serve as a prediction result of a cognitive path; and dynamically weighting the prediction results of the state path and the cognitive path by adopting a self-adaptive gating network to obtain a final answer prediction result. According to the invention, through fusion of the learning state path and the cognitive level path, more accurate prediction of the knowledge mastering condition of the student is realized, and measurement of the knowledge mastering level of the student and personalized learning support are carried out.