Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022)

<Previous Article In Volume
Next Article In Volume>

Prediction of Students' Academic Learning Performance Based on Big Learning Data

Authors
Jing Sun1, *
1College of Information Science and Engineering, Northeastern University, Shenyang, P.R. China
*Corresponding author. Email: sunjing@mail.neu.edu.cn
Corresponding Author
Jing Sun
Available Online 27 December 2022.
DOI
10.2991/978-94-6463-040-4_160How to use a DOI?
Keywords
Prediction; Learning Data; ROC
Abstract

With the development of computer technology and network technology, intelligent teaching platform is gradually applied to the field of education, such as classroom on rainy days. It collects and records a large amount of classroom data, such as student attendance, classroom interaction and classroom tests. How to analyze and make use of these data is very important to understand students' learning status and predict their final achievements in the future. In this paper, 171 students majoring in electrical engineering in a university are selected to evaluate the correlation between their final grades and the three indicators in the classroom data. The results show that there is a strong correlation between the final score and the test score. The students with lower class test scores may have a higher risk of failing the final score, which provides useful experience for the judgment of failing the final score, and actively takes preventive and control measures in the follow-up teaching process to urge students to pay attention to classroom teaching.

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.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
27 December 2022
ISBN
978-94-6463-040-4
ISSN
2589-4900
DOI
10.2991/978-94-6463-040-4_160How 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  - Jing Sun
PY  - 2022
DA  - 2022/12/27
TI  - Prediction of Students' Academic Learning Performance Based on Big Learning Data
BT  - Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022)
PB  - Atlantis Press
SP  - 1063
EP  - 1068
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-040-4_160
DO  - 10.2991/978-94-6463-040-4_160
ID  - Sun2022
ER  -