Research on personalized learning path planning model based on knowledge network-Reference-Cited by-同舟云学术

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Research on personalized learning path planning model based on knowledge network

Published:2022-08-22 Issue: Volume: Page:
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

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

Funder

National Natural Science Foundation of China

Cooperation and Education Project of Ministry Education

Natural Science Foundation of the Jiangsu Higher Education Institutions of China

Jiangsu Province “333” project

Lianyungang “521 project”, Science and Technology project of Lianyungang High-tech Zone

Teaching reform research project of Huaihai Institute of Technology

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-022-07658-8.pdf

Reference33 articles.

1. Nabizadeh AH, Leal JP, Rafsanjani HN et al (2020) Learning path personalization and recommendation methods: a survey of the state-of-the-art. Expert Syst Appl 159:113596

2. Vedavathi N, Kumar KA (2021) An efficient e-learning recommendation system for user preferences using a hybrid optimization algorithm. Soft Comput 25(14):9377–9388

3. Dwivedi P, Kant V, Bharadwaj KK (2018) Learning path recommendation based on modified variable-length genetic algorithm. Educ Inf Technol 23(2):819–836

4. Niknam M, Thulasiraman P (2020) LPR: A bio-inspired intelligent learning path recommendation system based on meaningful learning theory. Educ Inf Technol 25(5):3797–3819

5. Yu Z, Joohyun L, Wei C (2021) Q-greedyUCB: a new exploration policy to learn resource-efficient scheduling. China Commun 18(6):12–23

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dynamics Personalized Learning Path Based on Triple Criteria using Deep Learning and Rule-Based Method;TENCON 2023 - 2023 IEEE Region 10 Conference (TENCON);2023-10-31

2. Knowledge structures construction and learning paths recommendation based on formal contexts;International Journal of Machine Learning and Cybernetics;2023-10-21

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