Teaching Strategies and Practices to Enhance Research Data Analysis Skills Among Civil Engineering Graduate Students
- DOI
- 10.2991/978-94-6463-568-3_31How to use a DOI?
- Keywords
- Civil Engineering; Graduate Education; Data Analysis; Teaching Strategies; Case Library Development
- Abstract
In the course on research data analysis and processing for civil engineering graduate students, current teaching practices exhibit limitations, such as a lack of diverse teaching methods and insufficient case studies. These shortcomings hinder the development of students’ data analysis capabilities and the quality of research output. This paper proposes innovative teaching strategies and practices aimed at improving students’ research data analysis skills. It introduces a hierarchical case library, a diversified teaching approach that integrates theory with practice, and elaborates on the implementation process through specific teaching cases. The results indicate that these strategies effectively enhance students’ data analysis abilities and their capacity to address real-world research problems.
- 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 - Taochun Yang AU - Mingqiang Lin AU - Yongli Li PY - 2024 DA - 2024/11/27 TI - Teaching Strategies and Practices to Enhance Research Data Analysis Skills Among Civil Engineering Graduate Students BT - Proceedings of the 2024 5th International Conference on Modern Education and Information Management (ICMEIM 2024) PB - Atlantis Press SP - 250 EP - 256 SN - 2667-128X UR - https://doi.org/10.2991/978-94-6463-568-3_31 DO - 10.2991/978-94-6463-568-3_31 ID - Yang2024 ER -