16 results about "Professional development" patented technology

The invention relates to the technical field of intelligent education, in particular to an STEM teacher intelligent research and repair method and system fusing a knowledge graph and a graph neural network, and the method comprises an interdisciplinary knowledge graph construction and dynamic updating module which forms a concept association network with timeliness weight through the analysis of multi-source STEM educational resources and the modeling of the graph neural network; the teacher intelligent agent learning companion module is used for converting a teacher request into a teaching scheme with an evidence chain by adopting a thinking chain reasoning mechanism of graph retrieval enhancement and teaching logic constraint; the teacher portrait construction and professional development planning module is used for realizing dynamic quantification of STEM-TPACK (subject teaching knowledge of integration technology) capability characteristics of teachers through multi-modal teaching behavior analysis, and performing joint embedded representation with knowledge graph nodes; and the teacher teaching, learning and research community construction and treatment module constructs an affinity network based on the teacher feature vector, and realizes group intelligent division, self-built large-scale MOOC resource pushing and inter-disciplinary collaborative task generation.

The embodiment of the invention provides a dynamic page rendering method and system based on a front-end framework, electronic equipment and a storage medium, and belongs to the technical field of page rendering. According to the scheme, rule expansion processing is conducted on JSON structure specifications, a metadata structure model is obtained, and the metadata structure model is used for defining page rendering rules; obtaining JSON configuration data, and performing data preprocessing on the JSON configuration data based on the metadata structure model to obtain structure data; dynamic structure analysis is conducted on the structure data through an analysis engine, a virtual document object model tree structure is obtained, and the analysis engine adopts a layered architecture; and performing difference rendering according to the virtual document object model tree structure to obtain a target page. According to the method, seamless connection between a low-code platform and professional development can be realized, the development efficiency is improved, and the page rendering dynamic capability is enhanced.

The invention relates to an online multi-terminal interconnection production and teaching fusion accurate management system based on big data analysis, in particular to the field of big data analysis, effectively overcomes the problems of illumination fluctuation, noise interference and network jitter in a complex teaching environment by using a dynamic interference compensation technology, and ensures high-fidelity acquisition of classroom teaching behavior data. Through a space-time fusion mechanism, the relevance between the body movement and the voice emotion of the teacher is accurately aligned, and the recessive teaching rule in teacher-student interaction is deeply mined; the causal influence of the teaching strategy is quantitatively analyzed based on the behavior characteristic association map, and a personalized improvement direction is provided for teachers; finally, multi-modal decision-making weights are optimized in combination with reinforcement learning, a prospective teaching trend prediction and structured evaluation report is generated, closed-loop enabling from data collection to professional development is achieved, and teaching quality upgrading and teacher ability high-quality development in a production and teaching fusion scene are comprehensively promoted.

The invention provides a vocational ability cultivation scheme generation method and system for students, and the method comprises the steps: determining the learning resources of the students based on the specialty of the students, and enabling the learning resources to comprise courses and practice items; learning data in the learning process of the student is acquired, and the learning data comprises learning result data and learning behavior data; on the basis of the learning data, vocational ability portraits of the students are constructed, and the vocational ability portraits comprise post professional ability, vocational basic quality and vocational development potential; according to the learning resources and the vocational ability portrait, generating a vocational ability cultivation scheme of the student, thereby realizing visualization of student ability, enabling the student to clearly understand self learning conditions, and facilitating adjustment of a learning strategy; a teacher can optimize a training scheme according to the vocational ability portrait, and personalized learning environments and conditions are provided for students.

The invention belongs to the technical field of data analysis, and discloses a teacher evaluation method and system based on multi-modal data. The method comprises the following steps: based on a teacher professional development evaluation platform, according to collected real-time multi-modal data of a teacher, carrying out teacher evaluation to obtain a real-time teacher score and a predicted teacher score; according to the real-time teacher score and the predicted teacher score, personalized development suggestions are generated, and real-time personalized development suggestions are obtained and visually displayed. According to the method, the problems of single evaluation dimension, non-uniform evaluation standards and low efficiency in the prior art are solved.

The invention relates to the technical field of live broadcast menu recommendation, and discloses a live broadcast menu recommendation system and recommendation method based on different occupations, and the system comprises an intelligent recommendation module which is connected with a role recognition module, an interaction recognition module, a controller and a menu database; the role recognition module recognizes the occupational identity of a user and collects role information such as menu interaction habits and special menus of occupational groups, and the interaction recognition module captures and analyzes dynamic environment information including real-time user behaviors and scene features; and the intelligent recommendation module fuses occupational special menus and real-time scene features, screens target menu items from a menu database, and intelligently adjusts layout and outputs personalized recommendation menus according to user interaction habits and real-time behavior data. According to the method, the user experience of the live broadcast platform is remarkably improved, exclusive requirements of different occupational groups are met, a solid foundation is laid for diversified and professional development of the live broadcast platform, and the live broadcast technology is promoted to develop towards a more intelligent and more personalized direction.

The invention provides a teacher professional development personalized recommendation method and system based on multi-modal data, and the method comprises the steps: obtaining the multi-modal data of a teacher, carrying out the time-space alignment and dimension unification of the multi-modal data, and generating a multi-modal fusion feature; quantizing the teaching ability of the teacher based on the multi-modal fusion features to obtain ability scores of the teacher in different ability dimensions; according to the ability scores of the different ability dimensions and the demand intensity of the teacher, calculating ability gap values of the different ability dimensions; and matching the capability gap value and the demand intensity with training resources to generate recommendation information. According to the recommendation method and system provided by the invention, the defects of single data source, static evaluation, recommendation homogenization and lack of continuous optimization in the prior art are overcome, and the accuracy, personalization and sustainability of professional development support of teachers are improved.

The invention discloses an online evaluation system and method based on occupational skills, relates to the technical field of occupational skill evaluation, and aims to solve the problems of one-sidedness, low efficiency and single dimension of traditional evaluation and realize multi-dimensional, accurate and efficient evaluation. The system comprises a user information management module, an evaluation index setting module, a data acquisition module, a data analysis and evaluation module, a result display and feedback module and a certificate generation and management module. The index setting module constructs a multi-dimensional index system for different occupations and sets quantitative standards and weights; the data acquisition module is used for acquiring data in multiple modes of online examination, video analysis and the like; the analysis module generates scores and comprehensive results through machine learning; the display module displays the result and provides suggestions; the certificate module generates a verifiable certificate after the user reaches the standard. The process of the method comprises the steps of registration and entry, index determination, data acquisition, analysis and evaluation, result feedback and certificate generation, and a basis can be provided for professional development and talent selection.

This invention discloses a method for improving the success rate of POY yarn spinning. The method is characterized by the following steps: POY yarn cake is prepared through slurry preparation, esterification, polycondensation, metering, melt extrusion via spinneret, cooling, oiling, and winding. During POY spinning, the oil content of the initial 0-1000m length of the POY bottom yarn and the last 1000m length of the POY surface yarn in each POY yarn cake is increased by 8-15%, while the oil content of the middle portion of the POY yarn remains unchanged. This method solves the problem of high yarn breakage rates caused by reduced yarn cohesion and adhesion of the bottom yarn after the oil evaporates.

The invention discloses a project management system development method based on low code configuration, relates to the technical field of computer software, and remarkably improves the prediction adaptability and practicability of a project management system in a new project type through a low code configuration and meta-learning fused architecture. A low-code interface allows non-technical users to intuitively configure project parameters, such as a construction period or a risk index, so that a system customization threshold is reduced, and enterprises can quickly respond to innovative project requirements without depending on professional development teams; the meta-learning module uses general knowledge of a pre-training model to complete model adjustment only with a small amount of new data, and overcomes the defect of weak generalization ability of a traditional model in a data sparse scene; the few-sample adaptive mechanism is optimized through internal and external loops, so that the model is ensured to be fast converged while keeping stability, and the training time and resource consumption are reduced; the verification process in the deployment stage enhances the reliability of the system, and the dynamic consistency verification can detect the output deviation of the model in time.

This application provides a method for configuring a self-service mode of a system, comprising: obtaining configuration parameters for the self-service mode from the cloud; and configuring the system's self-service mode according to the configuration parameters. The configuration parameters in the cloud may be set by the manufacturer of the self-service device, for example. When the self-service device needs to enter self-service mode, it can send a request message to the cloud to request the configuration parameters for the self-service mode; subsequently, it configures the system's self-service mode according to these configuration parameters. Since the configuration parameters are set by the manufacturer of the self-service device, and manufacturers typically have more professional development capabilities than customers, the above method reduces the time required to deploy the self-service device and the risk of secondary development failures, thereby reducing developer costs.

In professional development, where learning new skills and managing complex projects are crucial, the platform introduces a tailored, innovative solution. The platform caters to a wide array of applications, from individual learning and skill acquisition to intricate task execution, and collaborative project coordination, emphasizing personalization and adaptability in engagement practices. The benefits of this software platform include its efficacy in enhancing learning outcomes, productivity, and project completion rates. By integrating customizable engagement plans and adaptive communication mechanisms, this software system aims to revolutionize the way individuals and teams navigate the challenges of professional growth and complex projects, setting a new standard for sustained engagement and success.

The invention discloses a nurse training examination system based on OKR. According to the system, a nurse can effectively master clinical theoretical knowledge and skills through the system, the nursing service quality is improved, medical errors are reduced, the work satisfaction degree and occupational development of the nurse are improved, modernization of nursing education is greatly promoted through implementation of the system, and the development of the nurse is promoted. The invention discloses an OKR-based nurse training examination system, and aims to ensure that continuous education and professional development of nurses can meet the goals of medical institutions, and improve the nursing quality and patient nursing results at the same time. By integrating the OKR into the training and assessment process, the progress can be better tracked, nurses are helped to improve professional skills, finally, the medical service quality is improved, and benefits are brought to patients. According to the system, a customized and high-efficiency nurse training system is created, and contributions are made to the development of the nursing industry.

The present invention provides a system and method for delivering interactive, chat-based training simulations tailored to mental health professionals. The system leverages large language model (LLM) technology, integrated with evidence-based psychological theories and behavioral principles, to create realistic simulations of interactions with virtual patients or colleagues. Key components include a prompting engine for generating scenario-specific prompts, an LLM for producing contextually accurate and clinically consistent responses, a transcript management module for recording and maintaining conversation logs, and an analytical feedback engine for evaluating user performance and providing actionable insights. The system enables mental health practitioners to practice therapeutic techniques, enhance clinical understanding, and refine professional skills in a controlled, immersive, and cost-effective environment. Applications extend to organizational training, candidate assessments, and broader professional development scenarios, offering an innovative, scalable solution to enhance the quality and accessibility of mental health education and training.

The invention belongs to a multi-modal analysis and evaluation method for a classroom teaching skill video, and belongs to the crossing field of education technology and artificial intelligence, and the method comprises the following steps: uploading a video and filling metadata; automatically preprocessing the video; teaching targets and characteristic innovation are analyzed; analyzing the teaching content and the teaching method; analyzing teacher behaviors; analyzing student performance; analyzing the classroom atmosphere; analyzing teaching evaluation; analyzing characteristic innovation; comprehensive evaluation is given; and generating an analysis report. According to the method, a multi-view quantitative evaluation system is constructed by fusing a multi-AI technology, full-process automation is realized, content score and improvement suggestion reports are output, evaluation objectivity and efficiency are improved, and accurate improvement of teaching quality and professional development of teachers are supported.

The application relates to a method, device and equipment for generating a professional analysis report based on social capital. The method comprises the following steps: obtaining the personnel flow relationship between professions caused by social capital in a professional data set, constructing a professional flow network model of the social capital dimension, extracting the personnel flow total amount feature, personnel retention feature and flow hub degree feature of each profession in the original professional data through the professional flow network model of the social capital dimension, recording the profession features, and generating a professional analysis report. The method can capture the personnel flow relationship between professions caused by social capital according to the professional flow network model of the social capital dimension, extract multi-dimensional personnel flow features according to the professional flow network model, and generate an analysis report, so that the comprehensiveness and accuracy of professional development analysis can be improved, and the method has important significance for guiding job seekers to employment and guiding organization human resource management.