14 results about "Knowledge assessment" patented technology

The invention provides a large language model evaluation set automatic generation method and device, equipment and a medium. Professional documents related to keywords are searched in a retrieval enhancement generation mode, key questions are automatically analyzed from retrieved content, answers are given, original questions do not need to be manually input to serve as starting conditions, the labor cost is reduced, and the efficiency is improved. And meanwhile, large-scale non-tagged corpora in the scheduling field can be utilized, so that the coverage degree of knowledge investigation in the professional field is improved. When the problem is not appropriate, new problem data can be generated in batches instead of rewriting the original problem, so that the problem diversity is further improved. The problem data generation process is based on knowledge points in a keyword form, so that the accuracy and focus of subjects are ensured, and the randomness of large language model generation is avoided. After the keyword is input, the assessment set can be generated in batches by an automatic means, a benchmark is provided for capability assessment in the scheduling large model training and fine tuning process, and the model development and test efficiency is improved.

The invention provides a knowledge tracking method based on knowledge evaluation and learner state evaluation, and relates to the technical field of knowledge tracking, and the method comprises the steps: obtaining and processing an answer record and teaching resources, and obtaining historical answer features and teaching resource features; modeling is carried out on the multi-modal course knowledge point information through teaching resource features, and knowledge point proportion weights are obtained; initializing a state matrix of a learner through the teaching resource characteristics; updating a state matrix through knowledge point proportion weights and historical answer features; and predicting the correct answering probability of the learner through the state matrix after state updating, the knowledge point proportion weight and the teaching resource characteristics. According to the method, the knowledge and the state of the learner in the learning process can be effectively evaluated and modeled, and the answer condition of the learner can be accurately predicted.

Embodiments of the present disclosure relate to a method, a system and a computer program product for generating and / or creating knowledge assessment items for an item bank using artificial intelligence and machine learning.

The invention provides an artificial intelligence auxiliary knowledge assessment method and device for adaptive learning. The problem that a traditional classroom and a traditional intelligent tutoring system cannot provide an adaptive learning environment and cannot timely and effectively assess students is effectively solved. The method comprises the following steps: setting a learning task containing multiple knowledge skills in the digital intelligent courseware system in advance, and obtaining learning data when a student answers the learning task; decomposing the learning task to obtain multiple knowledge skills, mapping the multiple knowledge skills into the learning data, screening out key learning data, and inputting the key learning data into a student model to obtain a corresponding evaluation result; and fusing the plurality of evaluation results to obtain an evaluation level result so as to assist in evaluating the knowledge state of the student based on the evaluation level result, and generating a personalized learning path for adaptive learning of the student.

A system is provided which may include (a) a knowledge database with required knowledge data associated with one or more goals of a user, (b) a skill database including required skill data associated with the one or more goals, (c) an AI bot module configured to generate first user environmental data, first user knowledge data; and first user skill data, (d) an environmental assessment module configured to match the first user environmental data to a current goal, (e) a knowledge assessment module, configure to obtain required knowledge data from the knowledge database based on the current goal and generate a first knowledge assessment as an output, (f) a skill assessment module, configured to select first required skill data from the skill database based on the current goal and generate a first skill assessment, and (g) an awarding module, configured to generate an award associated with the current goal

This invention discloses an intelligent assessment and evaluation system for power safety training based on machine learning, comprising a data acquisition module, a behavior analysis module, a knowledge assessment module, a comprehensive evaluation module, and a feedback generation module. Through the collaborative work of multiple modules, this invention achieves intelligent management of the entire power safety training and assessment process. The system utilizes machine learning technology to conduct multi-dimensional analysis of trainees' theoretical knowledge and practical behavior, significantly improving the objectivity and accuracy of the assessment. By constructing a power safety knowledge graph and an operational behavior standard library, the system can comprehensively cover various safety scenarios and achieve accurate assessment of trainees' safety awareness and operational skills based on deep learning-based multimodal data fusion analysis. The personalized feedback module can generate targeted training suggestions based on trainees' weaknesses, effectively improving training outcomes. Simultaneously, the system supports remote online assessment, greatly reducing training costs and time investment.

Various embodiments of the present disclosure provide a method for service exchange in dormant and untapped labor markets. The method performed by a server system begins with candidate enrollment and form submission, capturing comprehensive information. The server system processes this data through mental health, personality, attribute, competency, or knowledge assessments. A resulting CTP is stored in a database. A gap analysis compares the CTP to a pre-defined Success Talent Profile (STP), identifying deviations. Based on these deviations, candidates are classified: those with skill / knowledge gaps are designated for employment matching, while those with core competency gaps receive targeted training. The server system then matches employable candidates with businesses and training-eligible candidates with service providers, optimizing labor market integration.

The invention discloses a vehicle knowledge quality evaluation method, a server and a computer readable storage medium. The method comprises the steps of obtaining vehicle knowledge information; and based on a preset vehicle knowledge evaluation dimension, according to the vehicle knowledge information and a preset evaluation rule associated with the preset vehicle knowledge evaluation dimension, performing quality evaluation on the vehicle knowledge information. Thus, through automatic quality evaluation, high-quality vehicle knowledge information is obtained, a reliable knowledge base can be constructed, high-quality data is provided for training and application of a large language model in the vehicle-mounted field, the reasoning ability of the large language model is improved, and therefore the user experience is improved.

Various embodiments of the present disclosure provide a method for service exchange in dormant and untapped labor markets. The method performed by a server system begins with candidate enrollment and form submission, capturing comprehensive information. The server system processes this data through mental health, personality, attribute, competency, or knowledge assessments. A resulting CTP is stored in a database. A gap analysis compares the CTP to a pre-defined Success Talent Profile (STP), identifying deviations. Based on these deviations, candidates are classified: those with skill / knowledge gaps are designated for employment matching, while those with core competency gaps receive targeted training. The server system then matches employable candidates with businesses and training-eligible candidates with service providers, optimizing labor market integration.

The invention discloses a student knowledge assessment method and system based on chain reasoning and cognitive enhancement generation, and the method comprises the following steps: obtaining an original question set and an answer record text set of a student, and processing the original question set and the answer record text set to obtain a standard question set and a standard answer set; explicit knowledge point extraction is carried out on the standard question set, implicit knowledge point extraction is carried out on the original question set based on chain reasoning prompt, and then a knowledge point set is formed; performing generative adversarial network modeling on the non-mastered knowledge points based on the standard answer set to generate an enhanced sample set; extracting historical error frequency distribution of similar knowledge points as an auxiliary feature, and further verifying whether a generated error sample is compliant or not; inputting the mastered knowledge point features and the compliant enhanced sample set into a neurocognitive diagnosis model to obtain a mastering probability; and judging the mastering probability, and generating a knowledge state evaluation result. And in combination with a NeuralCD model, inputting student and practice codes and cognitive parameters, and outputting a knowledge mastering state of the student.

The invention discloses a laboratory safety actual-combat skill evaluation system and method based on artificial intelligence, and the system can integrate knowledge graph modeling, multi-modal scene generation, AI proposition, semantic evaluation and reinforcement learning technologies, achieves the closed-loop conversion from knowledge learning to ability cultivation, and improves the ability evaluation efficiency. Actual combat evaluation, intelligent evaluation and personalized enhancement of laboratory safety behaviors are supported, so that an education mode is promoted to be transformed from'knowledge assessment 'to'ability evaluation', and the safety education goal of'life and use and learning to use 'is truly achieved; meanwhile, image and video question surfaces are generated for a real scene and rehearsal materials by calling generative artificial intelligence, hidden danger features are injected, and standard answers are synchronously generated to construct questions, so that the authenticity of the questions is enhanced, and the learning input degree and the situation migration effect of a user are improved.

A system (100) for evaluating music-based skills, aptitude and knowledge of a user is disclosed A receiving module (120) receives a request from the user for evaluating music-based skills, aptitude, and knowledge. A login module (125) queries the proficiency level of the user. An evaluation module (130) generates a test based on a response to the query. An aptitude assessment module (135) includes a recognition module (175) and a demonstration module (180). A knowledge assessment module (140) assesses the user based on music theory, timbre genre and associated musical topics. A skill assessment module (145) assesses the user based on vocals or an instrument. A customization module (150) customizes the test. A result generation module (155) generates the result. A feedback generation module (160) analyzes the performance of the user and generates feedback. A security measure module (165) verifies the identity of the user and secures integrity of the test.

The invention discloses an interactive teaching method and system based on a teaching video, and relates to the technical field of information, and the method comprises the following steps: 1, collecting the surface behavior data of a student watching the teaching video for at least three times recently, and the corresponding knowledge evaluation data; 2, analyzing the collected behavior data and knowledge evaluation data through a machine learning algorithm to obtain a concentration state distribution diagram of students in each section of video class, and judging the knowledge absorption ability of the students in combination with the corresponding knowledge evaluation data; step 3, performing targeted optimization processing on teaching video contents in the video library according to the knowledge absorption capability of the students, and inserting an interaction task set adaptive to the students into corresponding time nodes in the teaching videos; and step 4, pushing the optimized teaching video to a student terminal, receiving task completion data of the student in real time, and continuing to optimize the interaction task according to the task completion data to complete video teaching.

Embodiments of the present disclosure relate to a method, a system, and a computer program product for generating knowledge assessment items for an assessment of candidates in an examination and populating the generated knowledge assessment items in an item bank, the knowledge assessment items including different item types, and the knowledge assessment items being generated using artificial intelligence and machine learning, and further the knowledge assessment items generated (created) by the AI / ML module are authenticated and vetted by a subject matter expert before storing or updating the knowledge assessment item(s) in the item bank.