10 results about "Lesson study" patented technology

The present application relates to the technical field of intelligent management of teaching data, and particularly relates to a method and system for integrated teaching intelligent management suitable for courses, posts, competitions and certificates, wherein the method for integrated teaching intelligent management suitable for courses, posts, competitions and certificates comprises the following steps: S1: obtaining a student portrait set containing multi-dimensional individual information of students, and connecting a preset external information base; S2: calling the external information base, and generating an optimal learning path for the students according to the student portraits and preset time nodes; S3: obtaining multi-dimensional individual information of the students when the students learn according to the optimal learning path, and updating the student portraits. The present application can integrate course learning, competition practice, certificate taking and post employment in the same framework, thereby solving the problem of fragmentation of each link in traditional teaching management, and enabling further optimization of the optimal learning path at different time nodes, so that the generated optimal learning path is always matched with the actual progress and final goal of the students.

The application discloses a small sample text classification method fusing data expansion and course learning, first expands data of a labeled sample set by using a strategy, then divides the data set according to a change degree of the expanded sample, then constructs a neural network classifier and trains a classification model, and finally classifies new samples by using the trained model. The learning method is improved and reconstructed, on one hand, data expansion is performed by using multiple strategies, and on the other hand, samples are divided into grades according to change degrees from small to large, and in the learning process, a course learning strategy is used to learn gradually from easy to difficult, and the classification accuracy is significantly improved.

The invention discloses an audit field-oriented data distillation method based on knowledge enhancement and course learning. The method comprises the steps of inputting unknown audit data into a trained small model; wherein the trained small model is obtained through training according to the large language model, the fusion data and the thinking chain; the fused data is obtained by performing semantic fusion on audit data in a pre-established audit database and corresponding law and policy knowledge; the auditing database is constructed according to bidding and tendering files, contract performance data and compliance review records; the thinking chain is obtained according to the large language model and the fusion data; and obtaining a reasoning result of the unknown audit data. According to the method, a high-quality and highly-adaptive data basis is provided for small model training; the reliability of the model in a complex audit reasoning scene is effectively improved; the migration capability and the generalization level of the small model are enhanced, and the stability and the high efficiency of the data distillation process are realized; and the bottleneck of the small model in auditing application is broken through.

The invention discloses a heterogeneous edge calculation multi-teacher federated distillation method based on course learning, and aims to reduce the influence of statistical heterogeneity on model performance on the premise of protecting the heterogeneity of an edge device model. The method specifically comprises the following steps: S1, a client performs local training by using a private data set and global knowledge, and then transmits output obtained by reasoning on a public data set to a server; s2, the server evaluates the quality of the output uploaded by each client by taking a sample as a unit, and then performs weighted aggregation to generate comprehensive knowledge; and S3, the server follows the thought of course learning, dynamically trains a global model by using comprehensive knowledge, and then sends global knowledge output by the global model to the client. And repeating the above process, and training until the global model converges. Compared with a previous federated learning method, the method has the advantages that the performance on four data sets is obviously improved, and the method is generally suitable for various training tasks.

The invention discloses a course recommendation method and system for a teaching integrated platform, and belongs to the technical field of teaching recommendation. The method comprises the following steps: establishing a link between a user port and a course interface, generating an initialized course learning packet set, collecting user learning behaviors to form a behavior chain, verifying a user learning behavior state, evaluating the acceptability of a course learning packet in a user group, and quantifying and displaying a collaborative recommendation degree based on a knowledge point nesting relationship. The corresponding system comprises a port link and course package initialization module, a learning behavior chain processing module and a course recommendation evaluation module. According to the method, accurate curriculum recommendation can be realized, the learning efficiency of the user is improved, the problem that the existing recommendation technology neglects knowledge point association and lacks group acceptance evaluation is solved, and the method is suitable for curriculum recommendation scenes of various teaching integrated platforms.

We provide the system. [Solution] A means for the user to input the desired program learning content, A generative artificial intelligence means that generates customized lesson content based on the input preferences, A means for providing the user with lesson content generated by the aforementioned generative artificial intelligence means, A system that includes this.

This invention discloses a teaching evaluation method for reinforced concrete structure courses, comprising: collecting teaching process data generated by students during their learning of reinforced concrete structure courses; the teaching process data including theoretical test data, experimental operation data, and structural design result data; preprocessing the teaching process data to generate a standardized teaching evaluation dataset; extracting feature parameters reflecting students' theoretical mastery, practical operation stability, and structural design rationality from the standardized teaching evaluation dataset; inputting the feature parameters into a pre-established teaching evaluation model to output theoretical ability scores, practical ability scores, and innovation ability scores respectively; and generating a comprehensive evaluation result for students based on the theoretical ability scores, practical ability scores, and innovation ability scores. This invention can integrate multi-source teaching process data to achieve quantitative analysis of multi-dimensional abilities, thereby improving the objectivity and accuracy of the evaluation.

This invention provides an e-commerce teaching system and method based on ADDIE, relating to the field of e-commerce service technology. The system includes: an acquisition unit for acquiring first interactive data; a capability analysis unit for obtaining corresponding capability analysis results based on the first interactive data; a course matching unit for performing course recommendation analysis based on the capability analysis results to conduct course testing and obtain simulated test results; and a teaching evaluation unit for matching and detecting the second interactive data during the course learning process with the business capabilities corresponding to each business project type. When the second interactive data matches the target business capability, a comprehensive evaluation of the learning effect is performed based on the second interactive data and the simulated test results corresponding to the target learning course group to update the advanced courses for continued teaching. The system and method of this invention can ensure the reliability of students' knowledge and skills mastery during e-commerce learning.

The invention relates to the technical field of large model training, in particular to a large model customized training method and system for industry application, by constructing a hierarchical knowledge graph, a model can systematically master an internal organizational structure and complex association of industry knowledge, an association prediction auxiliary task based on the graph is introduced in the training process, and the training efficiency is improved. The method comprises the following steps of: firstly, selecting a lesson and integrating the lesson into main semantic understanding, and meanwhile, ensuring progressive and stable convergence of model learning by adopting a dynamic course learning strategy; finally, optimization is carried out by fusing a loss function of knowledge association constraints, so that the model not only deeply understands a hierarchical system of industry knowledge, but also can reliably generate answers which conform to industry specifications, are strict in logic and are high in specialty; in this way, the technical problems that in the prior art, it is difficult to deeply understand and follow the internal hierarchical structure and complex incidence relation of domain knowledge, and consequently the output of the domain knowledge is insufficient in professionality, consistency and logicality are solved.