Internet College Education Based on Artificial Intelligence and Social Computing

DOI

10.2991/978-94-6463-172-2_160How to use a DOI?

Keywords

Internet education; Artificial intelligence; Social computing; Graph learning

Abstract

Internet education in colleges and universities is the inevitable result of the high popularization of college students' network use, and it is an important strategy for colleges and universities to actively adapt to the networked education environment. With the rapid development of artificial intelligence, traditional Internet education technology is no longer suitable for the increasingly large information scale of the modern education system, and new computer technologies need to be assisted in the completion of Internet education. To solve this challenge, we propose a novel internet education platform based on artificial intelligence and social computing, which can be utilized to mine students’ interaction information and predict their future evolutions. In particular, we introduce the state-of-the-art graph learning models as the pre-training model in our platform. Such models can generate node embeddings in the student social graph, and these embeddings usually contain important information for future prediction. In the experiments, we demonstrate the models’ performance and effectiveness. In addition, we also discuss what datasets can be used in our platform pre-training.

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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TY  - CONF
AU  - Liming Jiang
AU  - Zhilin Zheng
PY  - 2023
DA  - 2023/06/30
TI  - Internet College Education Based on Artificial Intelligence and Social Computing
BT  - Proceedings of the 2023 4th International Conference on Education, Knowledge and Information Management (ICEKIM 2023)
PB  - Atlantis Press
SP  - 1468
EP  - 1474
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-172-2_160
DO  - 10.2991/978-94-6463-172-2_160
ID  - Jiang2023
ER  -