Question pushing method and device, electronic equipment and storage medium

A topic push and topic technology, applied in the field of education and learning systems, can solve the problems of ignoring the relevance of topics and not considering the degree of mastery of knowledge points.

Active Publication Date: 2020-01-07
浙江学海教育科技有限公司
View PDF8 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method of topic push does not consider that students' mastery of the knowledge points in the topic will change dynamically with the learning time, and ignores the relevance between the topics

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Question pushing method and device, electronic equipment and storage medium
  • Question pushing method and device, electronic equipment and storage medium
  • Question pushing method and device, electronic equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0059] Embodiment 1 provides a topic push method, aiming at classifying the topic data containing the same knowledge points and then inputting them into the cyclic neural network model in time order to obtain the correlation characteristics between topics, based on the correlation characteristics and preset The current answer characteristics of the question bank data, and obtain the question status s of the question bank data t , according to the topic state s t With the Markov decision process, the queuing sequence of the questions is obtained, and the target topic is selected from the queuing sequence, so as to effectively push the target topic to the students. This way of pushing questions, considering that students’ mastery of the knowledge points of the questions will change dynamically over time, according to the characteristics of students’ current answering questions and the changing characteristics of historical answering questions, pushing questions according to diff...

Embodiment 2

[0074] Embodiment 2 is an improvement made on the basis of Embodiment 1. The answer time and answer results of the question data set are extracted, and the relevance features of the question data set are obtained through the cyclic neural network model.

[0075] Extract each topic data set Q i (i=1,...,N) corresponds to the answer time and answer results of historical question data, N is the number of knowledge points, the knowledge points of the question data set, the answer time and answer results Input the preset cyclic neural network model in time order to obtain the correlation feature H of each topic data set i4 =[H i1 ,...,H i4 ], i=1, .

[0076] The correlation feature can also include the answer time change feature, then the correlation feature is H i5 =[H i1 ,...,H i5], i=1,...,N. Furthermore, the relevance feature can also be other description features of knowledge point mastery obtained through certain technical means through probability calculation. For exa...

Embodiment 3

[0078] Embodiment 3 is an improvement on the basis of Embodiment 1. The current answer features and correlation features of the acquired preset question bank data are input into the recurrent neural network model to obtain the question status s of the question bank data. t .

[0079] Get the current answer feature X of the question push object practice preset question bank data t =[X i1 ,...,X im ], i=1,...,M, M is the number of questions in the question bank data, m is the number of features contained in the current answer feature, X i3 =[X i1 ,...,X i3 ], i=1,...,N, the current answer feature includes three features: answer knowledge points, current answer time and current answer result.

[0080] The current answer feature X t With the associativity feature H in (i=1,...,N, N is the number of knowledge points, and n is the number of related features) input to the cyclic neural network model to obtain the item features of the item bank data, and the item status s is fo...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a question pushing method. Education learning system, the method is used for obtaining relevance characteristics among questions and effectively pushing the questions accordingto changes of knowledge point mastering degrees of different students along with time, and comprises the following steps that historical question data are obtained, the historical question data are classified according to knowledge points, and each knowledge point forms a corresponding question data set; inputting the question data set into a preset recurrent neural network model according to a time sequence to obtain relevance characteristics; obtaining a question state st of the question bank data based on the relevance characteristics and preset current answering characteristics of the question bank data; and according to the question state st and the Markov decision process, obtaining a question queuing sequence, and selecting the front question in the queuing sequence as a target question for pushing. The invention further discloses a question pushing device, electronic equipment and a computer storage medium. The questions are effectively pushed for different students.

Description

technical field [0001] The present invention relates to an education and learning system, in particular to a method, device, electronic equipment and storage medium for pushing questions. Background technique [0002] With the rapid development of computer technology and network, Internet-based online education has been widely used. Students can use the online education and learning system to conduct online learning, online quizzes, online exams, etc., which is convenient for students to conduct personalized learning and evaluation. Because different students have different mastery of knowledge points, the education and learning system needs to push questions suitable for students' abilities for different students. Only when the pushed questions match the students' mastery of knowledge points can students gain effective ability through practice exercises. promote. [0003] Existing education and learning systems usually regard students' answers to different questions as in...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F16/2457G06N3/04
CPCG06F16/2457G06N3/044
Inventor 王伟松金苍宏
Owner 浙江学海教育科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap