CN-121998800-A - Courseware recommendation method, device and system

CN121998800ACN 121998800 ACN121998800 ACN 121998800ACN-121998800-A

Abstract

The invention provides a courseware recommending method, a courseware recommending device and a courseware recommending system, wherein the courseware recommending method comprises the steps of obtaining a user personalized data information file and a courseware content management model, carrying out content matching on the courseware content management model according to the user personalized data information file, and recommending the content matched with the courseware content management model to a user. By matching the personalized data information file of the user with courseware content in real time, the knowledge mastering condition, skill improvement condition, emotion attitude and the like of the user are analyzed in real time to dynamically adjust learning paths and recommend resources, and the utilization efficiency and teaching effect of teaching resources are improved; in addition, the invention constructs an immersive learning scene by integrating Virtual Reality (VR), augmented Reality (AR) and other multimedia technologies, thereby promoting effective integration of the technologies and deep fusion with teaching.

Inventors

HE GUANGHUA
XIAO HE
LI SISI

Assignees

北京卅三智慧教育科技有限公司

Dates

Publication Date: 20260508
Application Date: 20241108

Claims (11)

1. A courseware recommendation method, comprising: Acquiring a user personalized data information file and a courseware content management model; according to the user personalized data information file, the courseware content management model performs content matching; Recommending the content matched with the courseware content management model to a user.
2. The courseware recommendation method of claim 1, wherein the user personalized data information archive comprises a user learning activity record, a user behavior analysis, a user evaluation report, a user feedback and self-evaluation, a cognitive load measurement, a social interaction analysis and an emotion attitude evaluation, and the courseware content management model comprises: Acquiring a user personalized data information archive set and a courseware content set; creating a learning resource and context library, wherein the resource and context library comprises video learning content, in-voice learning, picture learning content, three-dimensional stereo learning content, virtual or real scenes related to the learning content, role playing, interaction elements, feedback mechanisms and learning path planning; storing the courseware content set in the learning resource and the context library; And establishing a matching relation between the user personalized data information file set and the courseware content set to complete training of the courseware content management model.
3. The courseware recommendation method of claim 2, further comprising: presetting a timer; acquiring a current user personalized data information file of a user according to the preset time; Updating matching content by the courseware content management model according to the personalized data information file of the current user; And recommending the matched content updated by the courseware content management model to a user.
4. The courseware recommendation method of claim 2, further comprising: and carrying out learning analysis according to the learning behavior and knowledge mastering condition of the user, and outputting a learning analysis report.
5. The courseware recommendation method of claim 4, further comprising: acquiring user requirements in real time; providing a solution in real time according to the user demand; And forming the user requirements and the corresponding solutions into learning behaviors of the user.
6. The courseware recommendation method of claim 2, further comprising: the method comprises the steps of acquiring an evaluation report of a user at regular time, wherein the user evaluation report comprises a self evaluation report, a companion evaluation report and/or a teacher evaluation report, and outputting a learning analysis report according to the evaluation report of the user, the learning behavior and knowledge grasping condition of the user.
7. The courseware recommendation method of claim 1, further comprising: The user personalized data information archive is created and maintained, and comprises user attributes, role allocation and authority management.
8. A courseware recommendation device, comprising: The information acquisition module is used for acquiring the personalized data information file of the user and the courseware content management model; the information matching module is used for carrying out content matching according to the user personalized data information file and the courseware content management model; And the information recommending module is used for recommending the content matched with the courseware content management model to the user.
9. The courseware recommendation device according to claim 8, wherein the user personalized data information file comprises a user learning activity record, user behavior analysis, user evaluation report, user feedback and self-evaluation, cognitive load measurement, social interaction analysis and emotion attitude evaluation, wherein the courseware content management model acquires a user personalized data information file set and a courseware content set, creates a learning resource and a context library, wherein the resource and context library comprises video learning content, in-voice learning, picture learning content, three-dimensional learning content, virtual or real scenes related to the learning content, role playing, interaction elements, feedback mechanisms and learning path planning, stores the courseware content set in the learning resource and the context library, establishes a matching relationship between the user personalized data information file set and the courseware content set, and completes the courseware content management model training; and the information matching module is used for matching corresponding contents for the user personalized data information file based on the courseware content management model.
10. The courseware recommendation device of claim 9, further comprising: the user management module is used for creating and maintaining the user personalized data information archive, wherein the user personalized data information archive comprises user attributes, role allocation and authority management; The system comprises a task allocation and adaptation module, a recommendation module, a courseware content management module, a matching module and a user management module, wherein the task allocation and adaptation module is used for presetting a timer, acquiring a current user personalized data information file of a user according to the preset time, and indicating a courseware content management model of the information matching module to update matching content according to the current user personalized data information file; And the learning analysis module is used for carrying out learning analysis according to the learning behaviors and knowledge mastering conditions of the user and outputting a learning analysis report. The interaction and feedback module is used for acquiring user demands in real time, providing solutions in real time through the learning analysis module according to the user demands, forming learning behaviors of users by the user demands and the corresponding solutions, and sending the learning behaviors to the learning analysis module and the user management module. The system comprises a learning analysis module, an evaluation module, a content recommendation module and a content push module, wherein the learning analysis module is used for acquiring a user evaluation report at regular time, sending the user evaluation report to the learning analysis module and the user management module, outputting the learning analysis report by the learning analysis module according to the user evaluation report, the learning behavior and knowledge grasping condition of the user, and carrying out content matching by the user management module and carrying out content push by the information recommendation module.
11. A courseware recommending system, comprising the courseware recommending device according to any one of claims 8 to 10.

Description

Courseware recommendation method, device and system Technical Field The application relates to the technical field of information processing, in particular to a courseware recommending method, device and system. Background With the deep fusion of big data and machine learning technology in the education field, learning modes such as an adaptive learning system (ADAPTIVE LEARNING SYSTEM, abbreviated as ALS) are applied. The ALS is a system for providing personalized learning paths and resources for learners by collecting and analyzing the learner data, and can dynamically adjust learning content and difficulty according to the learning progress, capability level and preference of the learners, so that the learning effect and satisfaction of the learners are greatly improved. The appearance of ALS is remodelling the educational field. The learning revolution represented by the ALS is comprehensively renovated and upgraded by means of data driving, personalized customization, intelligent adjustment, continuous optimization and the like, and a more flexible, efficient and high-quality learning experience is provided. The unique nature of ALS has prompted a new learning model, i.e., adaptive learning. In the ALS environment, a learner may obtain learning support that more closely fits his own needs. However, in the implementation process of the prior art, the inventor of the invention finds that at least the following technical problems exist in the prior art, namely in the learning scene based on the self-adaptive learning system, although personalized learning path planning and resource recommendation can be performed to a certain extent according to learner data, the data collection and analysis of the system are not comprehensive and deep enough, and the complex learning requirement and potential capability of the learner cannot be accurately known. Disclosure of Invention In order to solve the technical problems, the invention provides a courseware recommending method, device and system, which solve the problem that the complex learning requirement and potential capability of a learner cannot be accurately mastered in a learning scene based on a self-adaptive learning system in the prior art. In one aspect, the present invention provides a courseware recommendation method, which includes: Acquiring a user personalized data information file and a courseware content management model; according to the user personalized data information file, the courseware content management model performs content matching; Recommending the content matched with the courseware content management model to a user. The user personalized data information file comprises a user learning activity record, a user behavior analysis, a user evaluation report, user feedback and self-evaluation, cognitive load measurement, social interaction analysis and emotion attitude evaluation, and the courseware content management model comprises: Acquiring a user personalized data information archive set and a courseware content set; The method comprises the steps of creating a learning resource and a situation library, wherein the resource and situation library comprises video learning content, picture learning content, three-dimensional stereo learning content, virtual or real scenes related to the learning content, role playing, interaction elements, a feedback mechanism and learning path planning; And establishing a matching relation between the user personalized data information file set and the courseware content set to complete training of the courseware content management model. The method further comprises the steps of presetting a timer, obtaining a current user personalized data information file of the user according to the preset time, updating matching content according to the current user personalized data information file, and recommending the matching content updated by the courseware content management model to the user. The method further comprises outputting a learning analysis report according to learning behaviors and knowledge mastering conditions of the user. The method further comprises the steps of obtaining user requirements in real time, providing solutions in real time according to the user requirements, and forming learning behaviors of the users by the user requirements and the corresponding solutions. The method further comprises the steps of acquiring the evaluation report of the user at regular time, wherein the user evaluation report comprises a self evaluation report, a peer evaluation report and/or a teacher evaluation report, and outputting a learning analysis report according to the evaluation report of the user, the learning behavior and knowledge grasping condition of the user. The method further comprises the steps of creating and maintaining the user personalized data information archive, wherein the user personalized data information archive comprises user attributes, role allocation and authority management