Construction of AGIL Model of “Post-00” College Students’ Patriotic Education Discourse Based on Big Data Technology
- DOI
- 10.2991/978-94-6463-040-4_6How to use a DOI?
- Keywords
- Big data; Post-00 College students; Patriotism; Educational discourse; AGIL
- Abstract
According to the requirements of the era of patriotic education in colleges and universities in our country, this paper takes the undergraduates majoring in electronic science and technology in our school as the research object to explore the application of electronic information technology means and uses the school's big data student management platform and questionnaire feedback to fully explore the daily life of "post-00" college students behavioral data information and student characteristics. Establish a data mining model, traverse and analyze the collected data information and the logical relationship they reflect. Then, based on the data mining model, the AGIL model of patriotism education for "post-00s" college students is designed and constructed from four aspects: content, expression, system and model, so as to realize the scientific, efficient, precise and intelligent of patriotic education for college students.
- 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
TY - CONF AU - Xiling Liu AU - Yiqiao Hu PY - 2022 DA - 2022/12/27 TI - Construction of AGIL Model of “Post-00” College Students’ Patriotic Education Discourse Based on Big Data Technology BT - Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022) PB - Atlantis Press SP - 27 EP - 34 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-040-4_6 DO - 10.2991/978-94-6463-040-4_6 ID - Liu2022 ER -