The Path of Improving the Quality of Education Management in Artificial Intelligence Era

In artificial intelligence era, the learning methods of learners have deeply changed. Many learners choose to learn through many kinds of ways, such as online education platforms. Although learners may enjoy more high-quality educational resources, when they are faced with an abundance of resource information, they are prone to become lost in knowledge. To solve this problem, a multi-algorithm collaborative, personalized, learning path recommendation model is proposed to provide learning guidance for learners of online learning platforms. First, the learner model is constructed from four perspectives: cognitive level, learning ability, learning style, and learning intensity. Second, the association rule algorithm is employed to generate a sequence of knowledge points and to plan the learning sequence of knowledge points for learners. Last, the swarm intelligence algorithm is utilized to ensure that each knowledge point is matched with personalized learning resources with a higher degree of adaptability so that learners can learn using a more targeted approach. How to slove the problems that learning we want to know is the point of this papar.

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Publication Details

Published
2024-08-04
DOI
https://doi.org/10.23919/picmet64035.2024.10653222
Primary Topic
Educational Technology and Pedagogy
Type
article
Field-Weighted Citation Impact
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article

The Path of Improving the Quality of Education Management in Artificial Intelligence Era

XU Zhong-yuan
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Educational Technology and Pedagogy
article

The Path of Improving the Quality of Education Management in Artificial Intelligence Era

XU Zhong-yuan
article en

Abstract

In artificial intelligence era, the learning methods of learners have deeply changed. Many learners choose to learn through many kinds of ways, such as online education platforms. Although learners may enjoy more high-quality educational resources, when they are faced with an abundance of resource information, they are prone to become lost in knowledge. To solve this problem, a multi-algorithm collaborative, personalized, learning path recommendation model is proposed to provide learning guidance for learners of online learning platforms. First, the learner model is constructed from four perspectives: cognitive level, learning ability, learning style, and learning intensity. Second, the association rule algorithm is employed to generate a sequence of knowledge points and to plan the learning sequence of knowledge points for learners. Last, the swarm intelligence algorithm is utilized to ensure that each knowledge point is matched with personalized learning resources with a higher degree of adaptability so that learners can learn using a more targeted approach. How to slove the problems that learning we want to know is the point of this papar.

Harbin Engineering University (CN)
Openalex Percentile: Top 88%
Educational Technology and Pedagogy
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