379 results about "Learning resource" patented technology

An interactive learning platform comprises a teacher terminal, a student terminal and a server. The teacher terminal and the student terminal are in communication connection with the server. The server is used for storing teaching resources uploaded by teachers, information of schools, information of teachers and information of students. The teacher terminal and the student terminal are in communication connection with the server so as to achieve interaction of teaching information. The teacher terminal uploads sorted knowledge resources to the server and directly carries out one-to-one or one-to-many interactive teaching communication, electric board writing, document labeling and the like with students through a video mode. The student terminal can obtain learning resources, or carry out one-to-one communication with a teacher or watch the process of answering questions by the teacher through communication connection with the server, and the students do not need to spend time going to a training mechanism or get a private teacher for learning. Meanwhile, the mastering situation of the students on each knowledge point can be known by the platform through data analysis, targeted learning is achieved, time of the students is saved, and the learning efficiency of the students is improved.

A management system of learning comprises resource storage module for storing some learning resources being organized to be multiple metadata as each metadata corresponding to a knowledge point, adaptive management module for collecting information of learner's ability and for providing proper learning resource to learner as well as for providing information of knowledge point requiring learner to be learned.

A course guiding system based on non-zero start point and knowledge point in network education belongs to the field of computer technologies. The invention includes an initial knowledge domain construction module, an individualized knowledge domain generation module, an individualized learning route generation module, a history learning record module, a knowledge structure level evaluation module, and an individualized learning resource recommendation module. With knowledge point as the core, the invention constructs courses into the corresponding knowledge point tree and graph among knowledge points; learners are examined on knowledge points at each stage; by the analysis of learners' learning data and test of learning effect, the system obtains the learning status of learners at each knowledge point, their learning prediction result and knowledge point structure, recommends the corresponding learning resources and students to learners, and helps learners form the self-organized learning community to enhance the learning quality.

The invention discloses a network fault diagnosis method based on deep learning in a network virtualization environment. The network fault diagnosis method comprises the steps of: dividing a network into a physical network and a virtual network, combining the characteristics of occurrence of network faults, considering the time influencing factor, network topological connection characteristics and a mapping relation between the virtual network and the physical network, and comprehensively evaluating the network faults by means of a fault severity grading probability; regarding network characteristic parameters with influence degrees as a model learning resource, paying attention to the correspondence between variation trend of network historical data and fault tags, establishing a network fault diagnosis model with multiple fault grading probabilities in the network virtualization environment based on a viewing angle of deep learning, and training network parameters by using the network fault diagnosis model; and adjusting a fault prediction model in the training process, and utilizing an optimized and adjusted deep learning network to realize fault diagnosis in the network virtualization environment. The network fault diagnosis method can carry out deep analysis on the network parameters in the network virtualization environment, therefore the network fault diagnosis method has higher precision in predicting the network faults.

A services-oriented system structure for knowledge assessment and learning comprises a display device for displaying to a learner at a client terminal a plurality of multiple-choice questions and two-dimensional answers, an administration server adapted to administer one or more users of the system, a content management system server adapted to provide an interface for the one or more users to create and maintain a library of learning resources, a learning system server comprising a database of learning materials, wherein the plurality of multiple-choice questions and two-dimensional answers are stored in the database for selected delivery to the client terminal, and a registration and data analytics server adapted to create and maintain registration information about the learners.

The invention discloses a mobile terminal comprehensive learning system based on massive learning resources. The learning system comprises a resource library system, an intelligent knowledge diagnosis system, an online tutoring system, a student management system, a teacher management system, a parent management system, a learning PK system and an infinite extension system. According to the learning system, a learning resource library and a teacher team platform need to be built first, and after logging into the learning system, students acquire various learning resources such as synchronous videos, synchronous teaching materials, synchronous auxiliary teaching materials, synchronous question banks, knowledge points and micro videos. Questions which the students encounter in the learning process can be solved in two ways; in one way, the students communicate with teachers in a one-to-one mode through online tutoring, and in the other way, the students submit the questions to the question banks of the system and wait for other students or teachers to answer the questions. The students can carry out intelligent knowledge diagnosis on knowledge they have learnt to examine the knowledge mastering condition of themselves and can also interact with other students in communities.

The invention discloses a personalized network learning resource recommendation method which comprises the following steps: analyzing behavioral data of learners for visiting a network leaning system based on expanded theme pictures, acquiring leaning interest path changing patterns of the learners and groups of the learners on concepts and knowledge elements related to learning contents, and then realizing active personalized recommendation of proper learning resources to the learners according learning interest path changing patterns of the learner individuals and the groups of the learners individuals, sequence of learning objects of the expanded theme pictures and the like. The personalized network learning resource recommendation method can provide personalized learning service for network learners, thereby improving learning efficiency of the network learners.

The invention relates to a method for realizing concentrated searching on a handheld learning terminal, in particular to a method for realizing concentrated searching including test searching, extracurricular knowledge searching and knowledge explanation searching on the handheld learning terminal based on the sharing of learning resources in multi-functional areas. A compressed and unified learning resource information database is memorized in a memory of the handheld learning terminal, and the learning resource information database is an organic body formed by combining a plurality of relevant and complemented data memory units of a knowledge concept element database, a learning assessment resource repository, a knowledge explanation resource repository, a test relevance database and an extracurricular knowledge database. By the method provided by the invention, the effective range for searching on the handheld learning terminal by a user can be no longer limited by a test searching packet, and the user can perform test self-selection, individual test paper grouping, learning diagnosis and intelligent testing by combining other relevant learning functions, so that individual learning is realized really.

The invention discloses a task-driven precise classroom teaching cloud educational management system. The system comprises a cloud server, a student terminal and a teacher terminal, wherein the student terminal and the teacher terminal are connected with the cloud server. The student terminal can be used for searching for resources stored in the cloud server, and conducting loading, checking and editing within permission scope. The teacher terminal can be used for uploading resources to the cloud server, and conducting management, editing and information push on the resources within permission scope. The cloud server is used for storing learning resources to be acquired by the teacher terminal. The system solves the problems that the effect of preparation of students before class is not ideal, teaching progress is slow, a teacher can not comprehensively learn the learning condition of all students, objective and fair quantitative evaluation of students can not be achieved, and after-school review is inconvenient.

The invention discloses a pushing method and device for learning resources. The method includes the steps that through learning operation performed on a learning machine by a user, user learning information is collected, stored and analyzed, the learning speed and / or interest trend of the user is obtained, and according to the learning speed and / or interest trend, the matched learning resources are obtained and provided for the learning machine of the user. The learning resources can be pushed in a targeted mode according to learning progresses and characteristics of the user himself, so that the utilization rate of the learning resources and learning efficiency of the user are improved.

The invention provides a multi-level automated assessing and training integrated service method and system. The method comprise the first step of establishing a question bank, the second step of extracting test questions in line with test paper composition setting parameters from the question bank according to a preset test paper composition strategy to form appointed test papers, the third step of pushing the appointed test papers to question answering clients and calculating the grades of final papers when the final papers, fed back by the question answering clients, filled in test question answering information are received to figure out the grades of the test papers, the fourth step of establishing a capability assessing model, the fifth step of calculating assessing index scores of all terms of capacity, and the sixth step of pushing obtained learning resources to learning clients. By the utilization of the method and system, the learning and training mode is automated in the whole process, and a learning effect and learning efficiency are improved. In addition, as human intervention is not required in the assessing process, the credibility of assessing results is improved, and the assessing results can more objectively, truly and comprehensively reflect the capacity of assessed persons. Besides, the learning effect and learning efficiency are further improved.

The present invention helps generate connected communities of students and educators through access to an increased pool of granular learning resources that benefit from standardization of formats for creating and utilizing individual discussions on individual topics. The present invention also circumvents the complexity of existing repository systems by creating a standard platform format. Because this format is de facto implemented for any educator using the platform, standardized question types (e.g., discussion types or topic types) become functionally interchangeable notwithstanding any particular individuals utilizing the invention. The interchangeability of individual topics allows for creation of a global “topic library,” which may be made available to any educator using the system. This global topic library contains the standardized questions or discussion topics thereby allowing for quick review, selection, and incorporation into the individual teaching environment of any teacher utilizing the invention.

The invention discloses an intelligent English teaching system which includes a teacher terminal, a server and a student terminal. The teacher terminal and the server are connected via the Internet, and the server and the student terminal are connected via the Internet. The teacher terminal includes a human-computer interaction module, a teacher communication module, a difficult problem answering module, a task allocation module, a student assessment module, a voice / video call module, and a courseware sharing module. The student terminal includes a human-computer operation module, a student communication module, an individual intensive training module, a comprehensive training module, an oral English training module, a difficult problem summary module, a measurement and control module, a voice / video call module, a learning material call module, and a custom module. The sharing of English teaching resources and learning resources is realized. Targeted training is realized. The learning efficiency and learning interest of students are improved.

The invention provides a simulation teaching system based on an immersive VR (virtual reality) technology. The system comprises a head-mounted VR device, a simulation teaching resource cloud platform and a personal database. The system takes famous teacher teaching live action as a key line, generates famous teacher teaching VR resources with a three-dimensional digital technology and stores the famous teacher teaching VR resources in a server, and the simulation teaching resource cloud platform is established; a user downloads required study resources from the cloud platform according to personal demands, the personal study database is established, and immersive study experiences are acquired by means of the head-mounted VR device. Besides, personal information, study content and study progress data information are uploaded to the cloud platform, a discussion community is established with other users, and online guidance by famous teachers is realized. By means of the system, conventional education systems are supplemented and perfected, students and school age crowds in different regions can visually and vividly study in a three-dimensional scene in a human-computer interaction manner and can get high-quality education without going across regions, and the problem of education resource differentiation among regions is effectively solved.

The invention requests to protect a learning resource recommendation system based on user portraits, which is used for accurately and personally recommending course resources and comprises four levels, namely a data acquisition layer, a data processing layer, a model algorithm layer and a personalized service layer. The method comprises the following steps that: basic information of a user, browsing behavior information of a website, viewed content information and evaluation communication information are collected; data is classified and gathered through the collected information, a corresponding label library is established for each learner, resources in the label libraries are associated, personal portraits are established for the current learners along with continuous increase of the access frequency of the users, and meanwhile group portraits are also established. A course resource list obtained by a recommendation algorithm is recommended to the learners. According to the method,the feedback and click records given by the learners are recorded, so that better personalized service and accurate recommendation can be realized, the resource searching time of the learners can be saved, and meanwhile, the learning condition of the learners on knowledge can be known in a portrait mode.

The invention provides a learning resource recommendation method, which comprises the following steps: collecting the learning information of a user; preprocessing the learning information to obtain effective learning information; analyzing the effective learning information to extract knowledge points; according to the effective learning information, obtaining the weight of each knowledge point; according to association strength among the knowledge points and the weights of the knowledge points, forming a knowledge point undigraph; and according to the weights of the knowledge points in the knowledge point undigraph, recommending learning resources to a user. The invention further provides a learning resource recommendation system, and the system independently establishes the knowledge point undigraph which conforms to own personality characteristics for different users and records and tracks the learning dynamics of the users in real time so as to improve learning resource recommendation accuracy and improve the learning efficiency and the experience degree of the user.

The invention discloses a teaching method and system based on cross-media dynamic knowledge graph. The method comprises the following steps of constructing the cross-media dynamic knowledge graph; storing entity related information in the knowledge graph, and returning attribute values corresponding to entities through subject knowledge questions and answers; obtaining feedback information of students and knowledge points, calculating the knowledge point recommendation degree and the learning resource recommendation value score, and therefore, constructing a knowledge point recommendation listand a learning resource recommendation list and returning the lists to learners; constructing a course knowledge card; recommending friends, and recommending other users with similar learning progress and learning conditions to the current user. The teaching system comprises a data layer, a data analysis layer, an application layer and a user layer. The teaching method can be realized through a computer-readable storage medium. The problem that in the prior art, a teaching scheme cannot be formulated in a targeted mode according to learning characteristics is solved, the individualized teaching can be achieved, and the teaching level is effectively improved.

The invention provides a system combining intelligent knowledge diagnosing and teacher online tutoring. Basic information of a student is acquired first, required information is extracted from a massive resource library according to the information of the student so as to perform intelligent test paper composition, an intelligent diagnosing report is generated after the answers of the student are acquired, and learning resources corresponding to the weak knowledge links of the student are pushed to the student; the student can also transmits the intelligent diagnosing report to an online teacher for one-to-one communication, the teacher analyzes the diagnosing result again to increase the accuracy of the result, and the teacher can also push targeted resources to the student after the diagnosing. The method has the advantages that the convenience of the Internet is fully utilized, the student's time is utilized in a fragment manner, comprehensive intelligent knowledge diagnosing can be provided for the student fast, the student can find the weak knowledge links conveniently, and learning efficiency of the student is increased.

An ambient help application selects and displays learning resources to an end-user of a software application that are relevant to the current activities of the end-user in the software application. The ambient help application selects the learning resources based on computed relevance scores of each learning resource and displays the learning resources in a dedicated help space. The learning resources may include video- and text-based instructional information, and may be sized and positioned in the help space according to relevance score.

The invention relates to a network curriculum learning platform and a communication method. The network curriculum learning platform comprises a WEB server, a logic server, a database server, a content integration server, a content publishing server, a material server, a streaming media server and a network curriculum packet server, wherein the network curriculum packet server stores a network learning content packet. The network curriculum learning platform is characterized in that: the network learning content packet and the WEB server perform interactive communication through an application program interface; and the network curriculum learning platform reads basic information of a user to the network learning content packet through the application program interface on the WEB server and receives dynamic learning information of the user transmitted by the network learning content packet. By the networking learning platform and the communication method, the modularization degree is high; the network curriculum is easy and convenient to transplant; and learning resources can be shared highly.

The invention relates to an adaptive learning path planning system based on reinforcement learning. The system comprises an environmental simulation module, a strategy training module and a path planning module. In the whole process, the ability value of the student at each moment is obtained according to the improved project reflection principle; based on a Markov decision process, a complex learning environment is simulated, a reinforcement learning algorithm is reasonably applied to be combined with a student historical learning track offline training path planning strategy, and finally, alearning path is adaptively planned for the student online according to the trained strategy. Finally, based on the idea of reinforcement learning, the complex scene learned on the online education platform is constructed in the framework of the Markov decision process, the purpose of improving the efficient obtaining capability is achieved, continuous recommendation of learning resources is provided for students, the optimal learning path is planned, and therefore the learning effect and learning efficiency of the learner are improved.

The invention belongs to the field of personalized intelligent recommendation, a collaborative filtering recommendation method and system for learning resources based on knowledge association are disclosed. By combining with the relationship between knowledge and the relationship between resources and knowledge points, the information of knowledge points associated with learners is introduced intothe methods of user similarity calculation and interest calculation, and then the nearest neighbor user group of target learners is obtained, and learner-Learning resource interest score matrix is constructed. Then, the interest score of the resources that the current users are not yet learning and may be interested in is predicted by the knowledge points preference of the similar user groups. Finally, N results with higher interest score are recommended to the current learners. The invention designs a collaborative filtering recommendation algorithm of learning resources based on knowledge association according to the relationship among learners, knowledge points and learning resources, so that the recommendation result is more in line with the actual learning needs of learners.

The invention discloses a recommendation method and device of learning resources. The method comprises the following steps: receiving a query content picture shot by a user terminal; carrying out image identification on the query content picture to obtain query contents, and judging whether the query contents are in the present in a database or not; and if the query contents are in the presence in the database, according to the query contents, retrieving a query result matched with the query contents from the database, and pushing learning materials associated with the query result to a user terminal according to the individual learning information of a user. The query contents are identified from the picture shot by the user, the query result matched with the query contents are retrieved if the query contents are in the present in the database, the learning materials associated with the query result are pushed to the user terminal, difficulty for the user to select the learning contents is lowered, learning efficiency is improved, and personalized pushing is realized.

An automated resource resolver system receives a client request for a learning resource. The system selects a format for a target resource, to be delivered to the client device, based on user information and context information for the client device. Thus, the selected format will be accessible by the client device, utilizing the capabilities of the device, and will be the best-fit format for the user. After the system selects the format, the system determines whether the target resource stored at a resource repository is in the selected format. If not, then the system selects an instance of the target resource, not in the selected format, to convert to the selected format. The system converts the selected resource instance to produce an instance of the target resource that is in the selected format. The system makes the target learning resource, in the selected format, available to the client device.

The invention relates to an intelligent large-scale shield tunnel management system based on BIM and AI. The system comprises a time management subsystem used for regulating and managing the construction process and construction matters, a BIM management subsystem used for planning and managing the space position of materials and equipment and mobilisation & demobilisation, and an AI intelligent subsystem used for predicting resources needed by future construction and optimizing resource configuration in advance according to learning about known engineering. Compared with the prior art, the system is advantaged in that the time is the main line, the integral construction process is regulated and managed, and man-machine-material regulation is carried out; the space is the support, the BIM management subsystem is used for planning and managing the space position of the materials and the equipment and mobilisation & demobilisation; data is taken as the root, an engineering information database is managed and is taken as learning resources of the AI intelligent subsystem, an intelligentization level is improved continuously, the three are mutually independent and are associated through the data, visual management and monitoring on the tunnel shield construction process are facilitated, and construction experience references for subsequent engineering are facilitated.

The invention provides an online course management method and system, wherein the online course management method comprises the following steps: when receiving an instruction of learning a random course, obtaining the total learning time of each learning resource in a learning resource packet corresponding to said course; counting the learning time of each learning resource cost by a user in real time; calculating the learning progress of each learning resource according to the total learning time of each learning resource and the learning time of each learning resource; and showing the learning progress of each learning resource to the user. By means of the technical scheme provided by the invention, the user can directly know the learning progress of each learning resource in the learning resource packet; therefore, the user can reasonably manage self learning time; the online learning efficiency of the user is increased; and the learning experience of the user is improved.

The invention discloses a method for obtaining user specific metaknowledge interest. The method is specific to a learner in a network learning system, aims at exactly identifying and obtaining learning interest of the network learner, predicts the future interest change of the learner, and improves learning efficiency and performance of the network learner. In the aspect of user model, a user interest model facing the network learner group is adopted. In the interest omission algorithm of dynamic interest perception, an interest omission algorithm featuring automatically discovering and omitting the threshold is adopted. In the interest prediction algorithm, a prediction method featuring user collaborative prediction is adopted. The invention analyzes blogs of the learner to exactly identify the interest change of the user towards metaknowledge, conception and learning resource, reflects interest degree in a quantitative way, predicts the interest change of the learner, improves defects of the existing technologies, and has good application prospect in the network learning system and network individual service.

The invention discloses an automatic generation method and system based on personalized learning process of mapping knowledge domains. The method includes: on the basis of personalized mapping knowledge domains described by a directed hypergraph, utilizing a relation between knowledge elements and learning activities, and automatically generating corresponding learning process frames according to personalized characteristics like learning performance targets, learning capability, learning habits and learning modes of learners; on the frames, automatically generating all possible supporting resources of activities according to characteristics of the learners, the knowledge elements learned by the activities and activity type; utilizing relation among learning resources, the learners and learning activity attributes, relation between the activity attributes and process attributes and the personalized objects of the learners for optimization of process structure and learning resources to generate optimized learning process. By the method, huge personalized learning process can be generated automatically; the method is used for optimizing the learning process structure and the learning resources according to specific conditions of the learners, and learning is analyzed and optimized globally. In addition, the automatic generation method and system is a foundation for formulating further personalized learning schemes.