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Neural Computing and Applications

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22-08-2022 | S.I.: AI based Techniques and Applications for Intelligent IoT Systems

Research on personalized learning path planning model based on knowledge network

Authors: Hui Li, Rongrong Gong, Zhaoman Zhong, Libao Xing, Xing Li, Haining Li

Published in: Neural Computing and Applications | Issue 12/2023

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Abstract

Constructing a personalized learning path is a critical way to solve the problem of cognitive difference and learning disorientation effectively. The construction process of the learning path is closely related to the internal relationship between knowledge and needs to meet different learning scenarios and learning needs. Because of the above requirements, a personalized learning path model based on a knowledge network is proposed in this paper. The algorithm begins by building a knowledge network with learning resource nodes and knowledge points. Following that, the order of the knowledge points was determined using their sequential link. A sequence of learning materials that adhere to user characteristics was eventually acquired by evaluating the learning time limit of various learning contexts. The proposed approach was tested on the data sets of open MOOPer and Python learning platforms. Compared with traditional learning path construction algorithms, the proposed algorithm improves the accuracy and relevance.

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Title: Research on personalized learning path planning model based on knowledge network
Authors: Hui Li
Rongrong Gong
Zhaoman Zhong
Libao Xing
Xing Li
Haining Li
Publication date: 22-08-2022
Publisher: Springer London
Published in: Neural Computing and Applications / Issue 12/2023
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-022-07658-8

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