Big Data Personalized Teaching Under the Guidance of Ideological and Political Courses
- DOI
- 10.2991/978-94-6463-238-5_75How to use a DOI?
- Keywords
- curriculum ideology; big data; Kolb learning style; personalized education
- Abstract
To implement the fundamental task of cultivating students with moral character and the goal of constructing new engineering disciplines, this paper addresses the issue of how to apply teaching methods to students with diverse backgrounds. With the guidance of curriculum ideology, based on the teaching objectives of cultivating innovative electrical engineers in accordance with the Washington Accord, process-oriented big data analysis is used to analyze the learning situation and students’ learning styles, driving the teaching mode of designing grouping and layering according to students’ characteristics, ultimately crystallizing the personalized education model of new engineering disciplines driven by big data. The results showed that the proposed teaching mode can promote the progress of all students with Kolb learning style based on big data.
- Copyright
- © 2024 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 - Qin Zhang PY - 2023 DA - 2023/09/26 TI - Big Data Personalized Teaching Under the Guidance of Ideological and Political Courses BT - Proceedings of the 2023 4th International Conference on Big Data and Informatization Education (ICBDIE 2023) PB - Atlantis Press SP - 542 EP - 547 SN - 1951-6851 UR - https://doi.org/10.2991/978-94-6463-238-5_75 DO - 10.2991/978-94-6463-238-5_75 ID - Zhang2023 ER -