11 results about "Student assessment" patented technology

The invention discloses an education evaluation method and system based on visual identification data analysis, and relates to the technical field of education analysis, and the method comprises the steps: presetting the understanding difficulty for each mapping node, and taking the understanding difficulty as a teaching path reference; performing semantic analysis on the explanation scheme, extracting knowledge points and secondary and supplementary key phrases, and associating the knowledge points and the secondary and supplementary key phrases to corresponding mapping nodes to realize content structuring; acquiring real-time classroom voice information, extracting and analyzing characters to determine real-time keywords, positioning corresponding nodes in the mind map, sequentially connecting the nodes to form a real-time map node sequence line, and capturing an actual explanation path; calculating student initial state evaluation, combining node difficulty correction to obtain final evaluation, and accumulating all student evaluation as a teaching effect; taking a preset explanation order line teaching effect corresponding to the real-time order line as a standard, determining the relative positioning of actual evaluation, and achieving deviation quantification; according to the invention, through multi-modal fusion and a dynamic order line mechanism, the real-time performance and accuracy of evaluation are improved, and teaching improvement guidance is provided.

The application discloses a Bloom cognitive hierarchy constraint-based achievement-oriented education diagnosis method and system. The method takes course outline text and student evaluation data as input, and realizes the automatic diagnosis of course goal achievement through three structural modifications in the large language model Transformer architecture: the logarithmic value of the cognitive hierarchy transfer matrix is embedded as a learnable bias item in the attention score calculation path to realize feature coding of cognitive hierarchy perception; the continuous differentiable relaxation technique is used to establish an end-to-end differentiable inference path for the course goal achievement weight; and the Bloom partial order constraint is coded as a training loss, so that the diagnosis result meets the cognitive hierarchy progressive relationship. The three modifications are optimized by a joint loss function, which significantly improves the diagnosis accuracy and promotes the interpretability and scientificity of the large language model diagnosis in the achievement-oriented education scene.

The invention discloses a medical internship student assessment management method and related equipment. The method comprises the following steps: acquiring an operated object key point, a student hand key point and an instrument target in an operation video of a trainee, and identifying each operation action step of the trainee; identifying the medical care document content of the trainee, and obtaining a simulation object and peripheral sensor data for practical operation of the trainee, so as to respectively calculate a sensor quantitative index vector and a document quality vector of the trainee; and inputting a video score vector, a sensor quantitative index vector and the document quality vector obtained based on the operation action step analysis into a multi-modal fusion model based on an attention mechanism to obtain a comprehensive assessment score of the student. The problems that assessment of medical skills of students seriously depends on subjective observation and manual recording of teachers, objective, quantitative and traceable assessment means are lacked, and evaluation consistency and fairness are difficult to guarantee can be solved.

This invention discloses a course recommendation method and system for an intelligent construction education platform, relating to the field of intelligent education information technology. The method includes constructing a knowledge graph to establish multi-level associations between tasks and knowledge points; analyzing assessment data, setting score thresholds to identify students' weak knowledge points, integrating knowledge point weakness weights and job weights to generate comprehensive knowledge point weights; generating course recommendation results based on these comprehensive knowledge point weights, updating score data during student assessments after course completion, and using feedback to optimize the recommendation logic in real time. The method described in this invention implements a multi-dimensional weight-driven course recommendation path construction mechanism; employing dynamic feedback and real-time scoring algorithms, it establishes a closed-loop logic of recommendation, assessment, and re-recommendation, effectively improving the personalization and job matching of recommendations, and solving the problems of untraceable knowledge points, weak job adaptability, and singular recommendation strategies in existing platforms.

A computer-implemented method for an online student assessment includes: using a server computer for: gaining access to an information processing apparatus; the information processing apparatus having an output device, a camera, and at least one input device; identifying processes running on the information processing apparatus; stopping the processes on the information processing apparatus that have been determined as being unallowed during the online student assessment; verifying an identity of a user of the student computer; if the identity of the user is confirmed then, while remotely monitoring the user via the camera, displaying questions on the display monitor, and receiving answers via the at least one input device; restarting at least one of the unallowed processes; and restoring access to the student computer.

Technical field: The invention relates to the use of artificial intelligence (AI) in education for the objective evaluation of student performance and the generation of detailed feedback. Abstract: The present invention describes an AI-supported assessment system for the objective analysis and evaluation of student performance. The system comprises a data acquisition component for collecting performance data from various sources such as tests, homework, and oral contributions. A machine learning component analyzes this data to assess specific learning aspects such as comprehension, application, and creativity. A natural language processing (NLP) component evaluates students' written and oral contributions with regard to their language skills and content comprehension. Based on these analyses, a feedback generation component generates personalized feedback that includes strengths, weaknesses, and suggestions for improvement. A teacher adaptation component provides teachers with insights into the performance data and suggests targeted teaching strategies and materials to address the individual learning needs of the students. Inventive achievement: The proposed system improves the objectivity and detail of student assessments through the use of advanced AI technologies and offers personalized feedback as well as targeted lesson adjustments.

The present disclosure relates to a method of predicting a user's score on a question by an electronic device. The method includes: training a DP-multi tasking learning (DP-MTL) model; verifying the DP-MTL model; receiving choice selection information related to the question from the user through the terminal, and predicting 1) a probability that the user answers the question correctly and 2) the user's score related to the question using the verified DP-MTL model based on the choice selection information, and the DP-MTL model may be a model for predicting the user's score based on 1) information on whether the user answers the question correctly, 2) information on which incorrect answer is selected among choices of the question when the user selects an incorrect answer, and 3) a skill level of the user.

This disclosure relates to a method for generating lesson plans, as well as an electronic device and computer program product, belonging to the field of intelligent education technology. The method includes: acquiring student assessment data, which includes baseline data for all students and target group assessment data corresponding to the target student group; comparing and analyzing the baseline data for all students and the target group assessment data to construct a teaching deviation feature vector corresponding to the target student group; performing attribution diagnosis processing on the teaching deviation feature vector to obtain lesson plan optimization strategy instructions; and iteratively updating the original lesson plan corresponding to the target student group based on the lesson plan optimization strategy instructions to obtain an updated lesson plan. This disclosure can automatically convert multi-dimensional assessment data into lesson plan optimization strategy instructions and can verify the effect, significantly improving the personalization of teaching content and the iteration efficiency of lesson plans.

A computer-implemented method of providing automatic evaluation of student assessment based on multiple independent large language model (LLMs), the method including transmitting one or more questions to a user device associated with a student; receiving, from the user device, a data object comprising one or more text answers, each to a corresponding one of the one or more questions; generating one or more prompts comprising the one or more questions and the corresponding one or more text answers and predefined scoring points; initiating a plurality of LLMs to independently evaluate the one or more text answers based on the predefined scoring points; receiving evaluation outputs for an individual question of the one or more questions respectively from the LLMs; selecting a first evaluation output from among the evaluation outputs from a first LLM of the LLMs; and outputting the first evaluation output for the individual question to the user device.

The present invention relates to the technical field of remote teaching. Disclosed in the present invention is a management system for college English teaching. An input end of a student information module is separately connected to an input end of a score management module and an input end of a student profile management module. According to the management system for college English teaching, timely archiving and feedback of student evaluation results are achieved by means of bidirectional connection between a student management unit and an assessment and evaluation unit, making evaluation results and student profile management synchronous, and ensuring the accuracy of the evaluation results and the integrity of student profiles; the cooperation of a courseware browsing module, an online assignment module, a discussion area module, and a leaning progress tracking module can fully support online learning and course exchange activities of students; the discussion area module provides a communication and discussion platform for the students, promoting interaction and cooperation among the students, and broadening the learning horizon; and the learning progress of the students is tracked in real time, helping teachers to know the learning conditions of the students.