Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023)

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Potential Information Mining with Heuristic Causal Inference for Longitudinal Education Research

Authors
Jianping Wu1, Xinrui Shi1, Yunjun Lu1, *, Dezhi Li1, Liang Guo1, Wenlu Zhou1
1Institute of Information and Communication, National University of Defense Technology, Wuhan, 430000, China
*Corresponding author. Email: luyunjun@nudt.edu.cn
Corresponding Author
Yunjun Lu
Available Online 4 September 2023.
DOI
10.2991/978-94-6463-230-9_81How to use a DOI?
Keywords
heuristic causal inference; causal network; causal pathway contribution degree
Abstract

This paper reports on a study aimed at elucidating complex causal relationships between variables in an educational dataset (National Education Longitudinal Study: 1988, NELS: 88). A heuristic causal inference method is proposed, the core of which is to calculate the causal pathway contribution degree of direct and indirect causes to the selected target variable. In the process of our research, the experimental dataset is determined based on prior knowledge, and the global causal network among variables in the dataset is obtained by using FCI algorithm. Our ultimate goal was to identify the key factors affecting student achievement, and we achieved this by defining and calculating the causal pathway contribution degree. The experimental results show that many factors jointly determine students’ learning performance. In order to improve students’ learning performance, it is necessary to improve the quality of education itself, and relevant parties should pay more material and spiritual support.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023)
Series
Atlantis Highlights in Social Sciences, Education and Humanities
Publication Date
4 September 2023
ISBN
978-94-6463-230-9
ISSN
2667-128X
DOI
10.2991/978-94-6463-230-9_81How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Jianping Wu
AU  - Xinrui Shi
AU  - Yunjun Lu
AU  - Dezhi Li
AU  - Liang Guo
AU  - Wenlu Zhou
PY  - 2023
DA  - 2023/09/04
TI  - Potential Information Mining with Heuristic Causal Inference for Longitudinal Education Research
BT  - Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023)
PB  - Atlantis Press
SP  - 673
EP  - 684
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-230-9_81
DO  - 10.2991/978-94-6463-230-9_81
ID  - Wu2023
ER  -