文章基本信息

标题：Data Management Education from the Perspective of Science Educators
本地全文：下载
作者：Carol Tenopir ; Suzie Allard ; Priyanki Sinha 等
期刊名称：International Journal of Digital Curation
印刷版ISSN：1746-8256
出版年度：2016
卷号：11
期号：1
页码：232-251
DOI：10.2218/ijdc.v11i1.389
语种：English
出版社：University of Edinburgh
摘要：In order to better understand the current state of data management education in multiple fields of science, this study surveyed scientists, including information scientists, about their data management education practices, including at what levels they are teaching data management, which topics they covering, and what barriers they experience in teaching these topics. We found that a handful of scientists are teaching data management in undergraduate, graduate, and other types of courses, as well as outside of classroom settings. Commonly taught data management topics included quality control, protecting data, and management planning. However, few instructors felt they were covering data management topics thoroughly, and respondents cited barriers such as lack of time, lack of necessary expertise, and lack of information for teaching data management. We offer some potential explanations for the existing state of data management education and suggest areas for further research.
其他摘要：In order to better understand the current state of data management education in multiple fields of science, this study surveyed scientists, including information scientists, about their data management education practices, including at what levels they are teaching data management, which topics they covering, and what barriers they experience in teaching these topics. We found that a handful of scientists are teaching data management in undergraduate, graduate, and other types of courses, as well as outside of classroom settings. Commonly taught data management topics included quality control, protecting data, and management planning. However, few instructors felt they were covering data management topics thoroughly, and respondents cited barriers such as lack of time, lack of necessary expertise, and lack of information for teaching data management. We offer some potential explanations for the existing state of data management education and suggest areas for further research.