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Title:Exploring Data Science Learning Objectives in LIS Education
Author(s):Khan, Hammad
Subject(s):Data librarian
Research data services
Research data lifecycle
Data management
Data science
LIS curriculum
Abstract:The significance of this exploratory research is that it provides educators and curriculum developers an overview of topics, activities, and research data lifecycle stages that are represented in the library and information science (LIS) data science syllabi. The results from this study may be used for innovating new curriculum to prepare LIS students for jobs as data librarians in the 21st century library. This preliminary study gathered 128 syllabi from United States LIS programs offering data science courses for the year 2019. The research uses content analysis. Syllabi are analyzed for content through the list of weekly topics and expected learning outcomes. A list of content areas was developed from the syllabi, and then all documents were reviewed and coded against the selected content areas. Learning outcomes and objectives were then paired to the research data lifecycle stages to see how much representation of the research data lifecycle is covered in the syllabus. Course descriptions and syllabi offer insight into the goals and intended outcomes of the course, as well as detailing the content covered. The results show that LIS educators and curriculum developers are focused heavily on data analysis. While data analysis is valuable, and the analytical tools used are important, it is only one part of the research data lifecycle. Data librarians work process includes the entire research data lifecycle. Curriculum developers can benefit from this study by focusing on the areas of the research data lifecycle that is least represented in their data science syllabi to better prepare LIS students for data librarian positions in the 21st century library.
Issue Date:2020-10-13
Series/Report:Data Curation
Data Mining
Curriculum
Education Programs/Schools
Academic Libraries
Genre:Conference Paper / Presentation
Type:Text
URI:http://hdl.handle.net/2142/108828
Date Available in IDEALS:2020-10-09


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