Personalized learning path optimization method based on improved particle swarm optimization algorithm

A technology for improving particle swarm and learning path, which is applied in the field of personalized learning path optimization based on improved particle swarm optimization algorithm, to achieve the effect of search accuracy and search success rate advantages

Active Publication Date: 2016-10-12
ANHUI EDUCATION NETWORK PUBLISHING
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0011] In order to solve the above-mentioned technical problems, the present invention provides a personalized learning path optimization method based on the improved particle swarm optimization algorithm. This algorithm is to solve the local optimum defect in the optimal learning path based on the PSO algorithm in the intelligent learning system and improve the search accuracy. and search success rate

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  • Personalized learning path optimization method based on improved particle swarm optimization algorithm
  • Personalized learning path optimization method based on improved particle swarm optimization algorithm
  • Personalized learning path optimization method based on improved particle swarm optimization algorithm

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Embodiment 1

[0057] The present invention provides a personalized learning path optimization method based on the improved particle swarm optimization algorithm, and its optimization method is as follows:

[0058] Step 1: Establish a mathematical model of the learning path optimization problem

[0059] In an online learning system, in order to be able to recommend personalized learning resources and paths to learners, on the one hand, it is necessary to consider the knowledge mastery and learning costs of the learners themselves, and on the other hand, it is necessary to consider the learning sequence of the target knowledge points. existing literature [5,8,9] Among them, when scholars established the mathematical model of the learning path optimization problem, they took into account factors such as concept relevance, learning difficulty, and learner knowledge level, but did not take the order relationship into the mathematical model as an essential constraint relationship. To a certain ex...

Embodiment 2

[0119] Select 10 knowledge points of mathematics in junior high school as the target knowledge points, each knowledge point has 5 learning resources of different difficulty, the sequence relationship between each knowledge point, the difficulty of learning resources, the relationship between learning resources and knowledge points Relevance, the student's level of mastery of knowledge point pairs, etc. are all known conditions, and the details are as follows.

[0120] (1) Select 10 knowledge points from the "Space and Graphics" part of junior high school mathematics as the experimental data. These 10 knowledge points are: ① straight lines and line segments; ② measurement and representation of angles; ③ parallel and vertical; ④ properties of triangles ; ⑤ properties of parallelograms; ⑥ properties of circles; ⑦ congruent triangles;

[0121] This article uses {k 1 , k 2 ,...,k 10}Represent the above knowledge points in turn, and the learning sequence diagram of the knowledge ...

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Abstract

The invention discloses a personalized learning path optimization method based on an improved particle swarm optimization algorithm, comprising the following steps: (1) building a mathematical model of a learning path optimization problem; (2) performing learning path optimization based on an improved particle swarm optimization algorithm; and (3) analyzing the time complexity. According to the invention, by improving a standard particle swarm optimization algorithm, the defect that the standard particle swarm optimization algorithm is easily trapped into local optimum when solving an optimization problem is solved, and the method is advantaged in accuracy and success rate of search.

Description

technical field [0001] The present invention relates to the technical field of particle swarm optimization algorithm, and more specifically relates to a personalized learning path optimization method based on improved particle swarm optimization algorithm. Background technique [0002] The online learning system is a knowledge service method that relies on emerging media such as the Internet to deliver learning content. Driven by information technology, online learning has gradually become a mainstream way of acquiring knowledge. Although the online learning system has accumulated a large number of learning resources, it is often difficult for learners to quickly find the appropriate learning path and learning content from the massive resources. Therefore, the intelligence and personalization of online learning systems have become a research hotspot for scholars at home and abroad. A key issue in the study of intelligent learning systems is the optimization of learning pat...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/00
CPCG06N3/006
Inventor 吴雷阮怀伟昌磊孙智骁
Owner ANHUI EDUCATION NETWORK PUBLISHING
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