28 results about "Exam score" patented technology

The invention relates to a learning condition analysis method and system based on a large language model, a terminal and a medium, and relates to the field of education system technology, the method comprises the following steps: collecting learning data of students, the learning data comprising structured learning data and unstructured learning data, the structured learning data comprising examination scores and homework completion conditions, and the unstructured learning data comprising examination scores and homework completion conditions; the unstructured learning data comprises classroom behavior data, learning process data, student self-evaluation and mutual evaluation data and teacher teaching records; preprocessing the learning data to generate standardized data which can be used for analysis; input interaction information is received, analysis demand parameters are generated, and the interaction information comprises analysis demands of teachers or feedback information of students; based on a large language model, semantic understanding and deep analysis are carried out on the standardized data and the analysis demand parameters, and a learning condition analysis result is obtained; and displaying the study condition analysis result in a visual mode. The application has the effects of improving the teaching quality and meeting the actual teaching demand integrating degree.

The invention discloses a multi-modal data-driven teaching evaluation report automatic generation and intelligent analysis method. According to the method, multi-modal data is collected from various education information systems, and examination scores of students, classroom interaction, learning behaviors and feedback data of teachers are covered. The data are standardized, cleaned, preprocessed and the like, and abnormal values, missing values and unstructured data are processed. An evaluation model is constructed based on a multilayer neural network, a teaching evaluation report is generated by using an adaptive weight scoring system, and personalized teaching improvement suggestions are generated through a probability model. Meanwhile, the model is optimized by utilizing historical data and an incremental learning method, and finally, the method performance is measured through prediction accuracy, mean absolute error and comprehensive evaluation indexes, so that a comprehensive, accurate and intelligent teaching evaluation method is provided for the education field.

The invention belongs to the field of resource recommendation, and particularly relates to a learning resource recommendation method, system and device and a storage medium, the learning time of a user is divided into a fragmented time range and a long-time learning time range, the learning ability of the user is calculated, and according to the learning ability and the association degree of each chapter in a knowledge graph, the learning resource is recommended. When the current time is in the fragmented learning time range, a recommendation emergency value is obtained according to the current learning urgency degree and the knowledge gap risk degree, when the recommendation emergency value is smaller than a preset threshold value, a chapter with a maximum recommendation strategy is matched in the knowledge graph for recommendation, and if the recommendation emergency value is larger than the preset threshold value, the recommendation strategy is matched with the chapter with the maximum recommendation strategy. And if yes, optimizing and recommending chapters corresponding to the urgently needed learning resource type for learning. According to the method and the device, the corresponding learning resource recommendation is carried out in consideration of the time fragments of user learning, and the content which is urgently needed to be learned at present is also considered during recommendation to carry out preferential learning, so that the examination score is improved.

The invention discloses an intelligent management system based on data analysis, and belongs to the field of learning management systems, and the system comprises a weak subject analysis module which is used for extracting each subject score of a target student from a historical examination score database; the assistance matching module is in communication connection with the weak subject analysis module and is used for establishing a voluntary application one-to-one assistance relationship for the students with the weak subjects; the wrong question path generation module is used for analyzing the examination wrong questions of the target student in recent three months, counting knowledge point weights and constructing a dynamic learning path; the risk early warning module is used for detecting students whose scores decline in a cliff mode and starting three-level risk early warning through behavior and state analysis of campus monitoring; and the notification execution engine is used for triggering teacher appointment conversation, parent communication, seat adjustment and learning resource pushing operation according to the analysis result. According to the invention, quantitative evaluation can be carried out on dynamic change of subject strength, and then intervention necessity is automatically judged.

The invention provides an entrepreneurship practical training platform optimization method. The entrepreneurship practical training platform optimization method comprises the steps of a, collecting student data, including learning behavior data, social interaction data, practical training project data and examination score data of students, and performing data cleaning and preprocessing, noise data removal and missing data filling, and b, based on historical learning data and personal characteristics of the students, carrying out data processing on the data, so as to obtain the entrepreneurship practical training platform. And constructing a student learning model by using a machine learning algorithm, wherein the learning model can dynamically predict the learning progress, the course demand and the personalized path recommendation of the student. According to the entrepreneurship practical training platform optimization method, by introducing a multi-dimensional data acquisition and processing technology, the problem of inaccurate learning path recommendation caused by incomplete data or poor quality in a traditional platform can be effectively solved. And through data cleaning and preprocessing, a noise data detection and missing data filling method is adopted to ensure the quality of the data, so that the accuracy of a recommendation algorithm is ensured.

A method (100) for generating an ultrasound exam score, comprising: (i) receiving (104) a temporal sequence of ultra-sound image data for each of a plurality of different lungs zones; (ii) identifying (106) using a feature identification algorithm, for each zone, one or more features of the lung(s); (iii) determining (108), for each identified feature, a confidence score; (iv) determining (110), using a composite score algorithm, a composite score for each zone indicative of a disease or condition severity or a diagnosis; (v) determining (112) a lung score using a lung score algorithm, indicative of a disease or condition severity or a diagnosis for the lung(s); and (vi) providing (114), via a user interface, one or more of the lung score, the composite score for one or more of the plurality of different zones, and the confidence score for one or more of the identified one or more features.

The invention discloses an intelligent identification method and device for paper marking scores and a computer readable storage medium. The intelligent identification method for the paper marking score comprises the steps of obtaining a to-be-identified answer carrier image; wherein the to-be-identified answer carrier image comprises at least one test question score area; determining a target scoring column corresponding to at least one test question score region in the to-be-identified answer carrier image by using the template image; determining a score corresponding to each test question score region according to the target scoring column; and calculating a total score corresponding to the to-be-identified answer carrier image according to the score corresponding to each test question score region. In this way, the recognition accuracy of the score of the scoring column is improved.

The invention discloses a sports test management system based on artificial intelligence, and relates to the technical field of test management, the sports test management system comprises a data acquisition unit, a data processing unit and an application service unit, the data acquisition unit is used for acquiring data during a test, performing real-time video stream analysis by adopting a YOLOv8 algorithm after the acquisition is completed, and transmitting the data to the application service unit; and during acquisition, actions of examinees are captured through a camera, and target detection and attitude tracking are completed in combination with a machine vision technology. The dynamic state of an examination room is detected in real time through full-process intelligent invigilation and a YOLOv8 algorithm, target tracking and identity verification under the scene that multiple persons are examined at the same time are supported, the manual invigilation cost is reduced, automatic scoring and feedback are achieved, scoring is decomposed through actions, the take-off angle, the air posture and the landing distance are captured through YOLOv8, the score is calculated in combination with a physical model, and the intelligent invigilation effect is achieved. And generating examination scores in real time.

This invention discloses an AI-based physical education exam scoring method, belonging to the field of exam scoring methods, including the following steps: (1) activating the cameras deployed in the exam room to collect motion images and facial expression images of the examinee during pull-ups; (2) analyzing the collected facial expression images using AI image recognition technology to divide the exam process into three stages; (3) for each stage, analyzing the examinee's motion images using AI technology to determine whether each pull-up motion is a qualified motion; (4) counting the number of qualified motions in each stage and scoring them separately, adding the scores of the three stages to obtain the examinee's final exam score. This invention can divide the exam into three stages based on facial expression recognition, perform differentiated analysis on the motion characteristics of each stage, better fit the examinee's physical fitness change patterns, and make the evaluation results more targeted.

To enable provision of support to students and instructors in implementing effective learning methods.SOLUTION: A test support device is provided, comprising a target grade acquisition unit for acquiring target grades for target schools of test takers, and a task determination unit for determining learning tasks to be presented to the test takers based on utilization grates of the test takers based on test results of the test takers and the target grades.SELECTED DRAWING: Figure 1

This invention discloses a blockchain-based distributed examination method and system, comprising multiple modules including a management server, a teacher management unit, a student management unit, an examination business management unit, and a smart terminal. The teacher management unit allocates personal accounts and initial keys to teachers. These accounts contain teachers' personal information such as email addresses and mobile phone numbers. When a teacher accesses the grades section, the blockchain network receives a request and sends a dynamic key to the teacher's email address or mobile phone. The dynamic key is valid for 5 minutes. The teacher enters the dynamic key to log in to the grades section, and then the examination business management unit publishes the examination results. Students can check their results via their smart terminals. By adding a dynamic key to the grades section of the teacher management unit, and associating the dynamic key with the teacher's personal terminal, the security of the examination system is enhanced, preventing students from logging into the teacher management unit and tampering with the results.

1. Name of the product in this design: Unmanned Aerial Vehicle Training and Examination Scoring System Equipment. 2. Purpose of this design: For use in a training and scoring system for unmanned aerial vehicles (UAVs). 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

1. Name of the product in this design: Graphical User Interface for Robot Disassembly and Assembly Training Platform for Electronic Equipment. 2. Purpose of this design: An electronic device. 3. The key design features of this product are the graphical interface on the screen of the electronic device. 4. The image or photograph that best illustrates the design's key points: the front view. 5. Human-computer interaction method of graphical user interface: This graphical user interface is applied to computers. Using the main view as the main interface, clicking the "Exam" button on the left side of the main interface will take you to interface state 1, where you can select the exam subject; clicking the "Assembly Exam" button in interface state 1 will take you to interface state 2, where you can perform an assembly exam on the robot; clicking the "End Exam" button in the upper right corner of interface state 2, or when the "Exam Remaining Time" in the upper left corner of interface state 2 is "00:00:00", will take you to interface state 3, which displays the exam score and exam completion status. In each view, the specific text content can be replaced, and the number of texts does not limit the number of characters that can be replaced.

The invention provides a psychological assessment method and system for senior high school students based on artificial intelligence, and the method comprises the steps: enabling a testee to wear an intelligent bracelet in daily learning life, obtaining the daily physiological data of the testee through the bracelet, and obtaining the ranking of all examination scores of the testee from a school; performing data statistics, feature extraction and analysis on the acquired physiological data and score ranking data to obtain physiological and score feature data of the testee; the physiological and score feature data are imported into a high school student psychological assessment model to speculate a psychological assessment result of the subject, a psychological health score is generated, and the high school student psychological assessment model is obtained by training an artificial intelligence model through machine learning and deep learning and is updated through reinforcement learning. According to the method, the internal relation and rule among the physiological indexes, the academic performance and the psychological health state can be revealed, and the algorithm and accurate speculation of the psychological health state of the senior high school students are realized.

The present invention relates to the technical field of performance data analysis, and specifically to a student test performance intelligent analysis system. The present invention obtains the independent learning performance trend of each student and the overall learning performance trend of all students in each test; analyzes the difference characteristics between the learning performance trends, and obtains the change correlation between the independent learning performance trend and the overall learning performance trend of each student in the current test; then obtains the performance influencing factor of each student in the current test; then adjusts the current original performance data of each student to obtain the current adjusted performance data of each student; clusters all students according to the changes in the current adjusted performance data and the adjacent previous original performance data to obtain student clustering clusters; and analyzes the test performance. The present invention improves the accuracy of the clustering effect and the effectiveness of the performance analysis by adaptively adjusting the test performance of students.

The invention provides a teaching data management system and method based on cloud computing, and belongs to the field of data management. The problem of complex data management is solved; the data collection module is used for acquiring the number of students and examination scores to form student information; obtaining teaching data; the data processing module is used for averaging examination scores and teaching data in combination with the number of students; obtaining a correlation coefficient according to the obtained mean value in combination with the examination score; according to the correlation coefficient, calculating a total influence value of the teaching data on the student examination scores; the data prediction module is used for performing regression analysis on the examination scores and the total influence value, constructing a score prediction model, predicting student scores, comparing predicted scores with the examination scores, and providing teaching plans for the students with the scores lower than the predicted scores; according to the method, the data is acquired and predicted, and the predicted data is analyzed and judged, so that the data management difficulty is reduced.

The invention relates to the technical field of teaching quality evaluation, and discloses an English teaching quality evaluation method based on a knowledge graph, and the method comprises the steps: collecting the voice, text, examination score and interactive behavior data of a student; extracting phoneme accuracy, intonation curves and fluency indexes from the voice data, performing subject-predicate-object structure recognition and logical relationship labeling on the text data, and processing score and interaction data to form a preprocessed data set; establishing a knowledge graph containing vocabularies, grammar, semantics and communication strategy elements according to the preprocessed data set, and generating an element evolution trajectory; mapping the data to knowledge graph identification semantic isolated points and logic interruption points to form a teaching quality factor group; and correcting the factor group, generating a change process, generating an early warning level according to the trend and the element redundancy, and finally outputting an evaluation result. According to the invention, comprehensive, dynamic and traceable evaluation of English teaching quality is realized through the knowledge graph.

The invention belongs to the field of intelligent query, and particularly relates to an examination score and admission destination query and analysis method and system.The method comprises the steps that firstly, a query demand instruction is analyzed through a clustering algorithm, and a query cluster representing a query intention is generated; based on the initialized query concurrence tree, intelligently mapping query clusters to corresponding regional concurrence nodes according to examination number mapping or regional information, and establishing rapid indexes of examination numbers and nodes; analyzing a query intention condition field in the instruction, generating an effective query condition chain and evaluating query concurrency difficulty; and dynamically generating a query demand feedback information cluster by combining the real-time load state of each data storage node according to a comparison result of the concurrence difficulty and a preset threshold value. According to the method, intelligent routing of the query request and accurate scheduling of load awareness are realized, the processing pressure of a core node is effectively relieved, system overload and crash in a high-concurrency scene are avoided, and the throughput and service reliability of a score query system are remarkably improved.

The application discloses a kind of based on blockchain examination management method, system, storage medium and equipment, belong to blockchain technical field.Method includes: blockchain triggers smart contract according to the examination subject issued by examination system to issue digital assets, each examination subject corresponds to a kind of digital assets;According to the examination subject of each reading side will be read by the paper, enough digital assets of corresponding kind are transferred to the on-chain address of each reading side;Examination system sends the transfer request carrying the reading score of each examinee side to blockchain according to the digital identity of reading side;Blockchain transfers corresponding kind and corresponding amount of digital assets from the on-chain address of reading side to the on-chain address of examinee side;Examination system statistics the amount of digital assets of each kind in the on-chain address of examinee side, obtains the examination result of corresponding examination subject;Ensure that the result statistics is carried out on chain, so that examination result is authentic and credible, and check score review is open and transparent.

This invention relates to the field of teaching management technology, specifically to an anti-cheating system based on big data monitoring. The system includes a video monitoring module and a wristband. The video monitoring module is evenly distributed around the sports field and is equipped with a Bluetooth communication module. The wristband includes a housing and a strap movably connected to the housing. The housing contains a data processing module that transmits signals to the Bluetooth communication module. The housing also contains a one-way tightening unit for the strap, which prevents cheating by proxy. A reset unit is also included to release the one-way tightening of the tightening unit. This reset unit transmits a stop-exam signal to the data processing module when the one-way tightening is released. By improving the timing method in middle- and long-distance running physical education exams, only a small number of invigilators are needed. The system uses video monitoring combined with automatic single-shot continuous timing to record exam scores, preventing cheating such as proxy testing.

The invention discloses a middle school examination admission prediction visual analysis method for optimizing a random forest based on a genetic algorithm, and belongs to the technical field of visual analysis. The method comprises the steps of firstly obtaining related simulation filling data in a Chinese school examination data set; performing automatic hyper-parameter tuning on the random forest model by using a genetic algorithm; predicting a student admission result by using the trained model; a model interpretation view is constructed, a student prediction result view is constructed, and multi-dimensional data such as examination scores, volunteer filling and admission prediction are presented in an interactive table form; and finally, constructing a student list. The method can effectively solve the problems that a traditional prediction model is low in parameter tuning efficiency, insufficient in interpretation and one-sided in visual analysis, and provides data-driven scientific decision support for student personalized voluntary guidance, school teaching quality analysis and educational resource balanced configuration through multi-view collaborative interaction and dynamic prediction feedback.

This invention provides a differentiated learning content search method based on knowledge state assessment, belonging to the field of intelligent education technology. The method includes: analyzing learning resources based on a pre-set knowledge graph, labeling related knowledge point nodes and difficulty levels, and constructing a three-dimensional virtual coordinate space to complete resource mapping; obtaining users' historical exam scores and browsing records to generate a knowledge state profile and personalized search vectors; parsing search keywords to generate constraints and initial search points, performing vector-oriented retrieval, and capturing suitable resources through Euclidean distance thresholds and constraints; generating personalized tags based on the captured vectors; calculating recommendation scores by integrating difficulty matching degree and interaction intensity, and outputting tagged results after sorting. This invention achieves end-to-end personalization from resource retrieval and sorting to presentation, providing differentiated learning content based on learners' actual ability levels, effectively solving the problems of homogeneous results and lack of adaptability in traditional search systems.

The invention discloses a platform for safety education and training of an industrial control system, and relates to the technical field of education platforms. The platform comprises the following steps: step 1, inputting student information; step 2, basic course learning; step 3, professional course learning; 4, performing practical operation training: performing attack and defense simulation on the trainees and the AI; 5, big data evaluation and analysis: performing learning habit analysis, strong and weak item analysis, micro-expression analysis, character analysis and learning optimization analysis on students; performing course management analysis and teaching optimization analysis on the teacher; step 6, comprehensive learning: courses needing to be remedied by the trainees are analyzed, the courses are sorted according to score proportions and learning strength conditions, and corresponding teaching schemes are produced; in the learning process, comprehensive testing is carried out on trainees; and after the trainees complete the comprehensive training, performing an evaluation test, and analyzing the grades of the trainees according to the test scores of the trainees. The pertinence and practicability of safety education and training of the industrial control system can be effectively improved.

The invention discloses a medical equipment operator qualification management system and method, and particularly relates to the field of medical equipment management, and the medical equipment operator qualification management system comprises an examination management module, a certificate management module, an operation recording module, a scheduling management module, a database, a cloud server, a mobile terminal and a management terminal. The examination management module is used for establishing a medical equipment operation training examination system which comprises question bank management, an online examination platform, a real-time monitoring function and score evaluation and analysis; the certificate management module is used for recording and managing the work license information of the management personnel, including the issuing date, the validity period, the equipment type and the examination score of the certificate; and the operation recording module is used for recording detailed information of each equipment operation in real time. According to the invention, unified operation standard, optimized resource configuration, effective risk prevention and control, precise skill improvement and cross-regional collaborative management are realized, and the management level of medical equipment and the utilization efficiency of medical resources are comprehensively improved.

The invention relates to the field of learning assessment systems, and discloses an information management learning assessment system comprising a user management module comprising a student management module, a teacher management module and an administrator management module; the course management module comprises a course creating and editing module and a course resource management module; the learning management module comprises a learning progress tracking module, a learning path planning module and an interaction module; the assessment management module comprises a question bank management module, an assessment creation module and a scoring module; the score management module comprises a score recording and counting module, a score analysis module and a score notification module; and the information management module comprises a data backup and recovery module and a system log management module. The system can track and evaluate the learning progress and learning effect of students, can record and manage the training courses and examination scores of the students, and can provide personalized learning suggestions. The system integrates information management, learning management and examination and evaluation functions, optimizes the learning process through an informatization means, improves the learning efficiency, and achieves the effective examination of learning results.

The invention discloses a Japanese education precise learning condition analysis implementation method and platform based on big data driving, and the method comprises the following steps: S1, enabling students and teachers to log in a system, enabling the teachers to input examination questions, storing the examination questions in a database, and enabling the students to carry out an online examination from the system; s2, inputting various historical question types in advance by a teacher, and inputting standard spoken language answers and non-standard spoken language answers; s3, training the acquired question types and answers to obtain a standard spoken language training model and a non-standard spoken language training model; s4, analyzing the obtained spoken language features of the students by using the training model, and judging whether the spoken language is standard or not; s5, obtaining score characteristics of each test score of each student, classifying the score characteristics of multiple times, and generating a report and a curve graph; through the system, the oral ability of students after Japanese learning can be assessed online, and the score of each assessment of each student can be analyzed and counted.

The system according to this embodiment aims to provide students with individually optimized problem sets based on their mock exam results. [Solution] The system according to the embodiment comprises a reception unit, an analysis unit, a generation unit, and an update unit. The reception unit uploads the results of the mock exam. The analysis unit analyzes the results of the mock exam uploaded by the reception unit and identifies the student's weaknesses and strengths. The generation unit generates an optimal set of problems based on the weaknesses and strengths identified by the analysis unit. The update unit updates the set of problems generated by the generation unit and adaptively adjusts the difficulty level in accordance with the student's progress.

This invention discloses a multi-crane collaborative operation simulation teaching platform and examination system, belonging to the field of virtual simulation teaching technology. The system includes a collaborative scene construction module, which generates the initial poses of multiple virtual cranes and 3D models of the objects to be lifted based on the teaching task, and establishes motion constraints; an operation data acquisition module captures control commands in real time and generates action sequences; a state synchronization module updates the real-time state of each virtual crane using an event-driven approach and detects state conflict events; a conflict resolution module generates conflict resolution strategies based on a collaborative rule base and forcibly corrects the conflict state when a conflict is detected; and an examination evaluation module collects complete operation process data in examination mode, performs multi-dimensional scoring based on a fuzzy comprehensive evaluation matrix, and outputs examination results. This invention can detect and automatically resolve multi-crane collaborative conflicts in real time, achieving refined automatic scoring of the operation process.