A personalized test recommendation method based on user learning behavior

A recommendation method and technology for test questions, applied in data processing applications, instruments, predictions, etc., can solve problems such as inability to find suitable test questions and recommendations

Pending Publication Date: 2019-03-22
SUN YAT SEN UNIV
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AI Technical Summary

Problems solved by technology

[0004] In order to solve the problem that it is impossible to find suitable test questions to recommend to target users among numerous test question resources, the present invention provides a personalized test question recommendation method based on user learning behavior, which can be used in many test questions according to the degree of knowledge points mastered. Find suitable test questions from test question resources and recommend them to target users

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  • A personalized test recommendation method based on user learning behavior
  • A personalized test recommendation method based on user learning behavior
  • A personalized test recommendation method based on user learning behavior

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Embodiment 1

[0067] Most of the existing test question recommendation systems are for primary and middle school students in school education, and the types of questions are basically traditional subjects in exam-oriented education. In the existing online education platforms, although there are some integrated test question recommendation modules The platform does not fully consider the individual uniqueness of users and the commonality between users. Therefore, a personalized test item recommendation algorithm based on user learning behavior is designed, such as figure 1 , figure 2 As shown, the steps of the method for recommending personalized test questions are as follows:

[0068] Step 1: Obtain user historical test data, test questions and knowledge point information from the online education platform;

[0069] Step 2: Construct the user-examination score matrix R according to the user's historical test data, and construct the test question-knowledge point correlation matrix Q accor...

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Abstract

The invention discloses a personalized test question recommendation method based on user learning behavior, the method is as follows: obtaining user history problem data, test questions and knowledgepoint information from an online education platform; constructing a user based on user history data data; R, according to the relationship between the test questions and the knowledge points, constructing the test questions-Knowledge point correlation matrix Q; constructing the user cognitive diagnosis model through the DINA model, obtaining the user knowledge point mastering matrix A; obtainingthe user adjacent test set according to the matrix A, according to Matrix Q the test questions-Adjacent test sets, constructing alternative test sets; non-negative matrix decomposition of matrix R, obtaining the implicit feature matrices W and H of users and test questions, find the estimated values of W and H matrices, and get the score prediction Model; calculating the potential answering situation of the user, and recommending the test questions of the target user's own difficulty range to the target user. The invention can accurately recommend the test questions suitable for the target user to the user. The invention is applicable to the field of online education.

Description

technical field [0001] The present invention relates to the field of online education, and more specifically, to a method for recommending personalized test questions based on user learning behavior. Background technique [0002] With the popularization of computer technology and the rapid development of the mobile Internet, many traditional industries are gradually moving closer to the direction of the Internet, and the education industry is one of these traditional industries. In recent years, many online education platforms have emerged at home and abroad, and many successful practices have been carried out. The popular online education platforms in China include Netease Cloud Classroom, Tencent Classroom, MOOC, MOOC China and so on. The more popular online education platforms abroad include Coursera, Edx, Udacity, Khan Academy and so on. The content of the online education platform covers various disciplines and age groups, with rich and diverse functions, including on...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q50/20G06Q10/06G06Q10/04
CPCG06Q10/04G06Q10/063G06Q50/205
Inventor 吴迪杨敏
Owner SUN YAT SEN UNIV
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