Developing data literacy competencies to enhance faculty collaborations

Abstract

In order to align information literacy (IL) instruction with changing faculty and student needs, librarians must expand their skills and competencies beyond traditional information sources. In the sciences, this increasingly means integrating the data resources used by researchers into instruction for undergraduate students. Open access data repositories allow students to work with more primary data than ever before, but only if they know how and where to look. This paper will describe the development of two IL workshops designed to scaffold student learning in the biological sciences across two second-year courses, detailing the long-term collaboration between a librarian and an instructor that now serves over 500 students per semester. In each workshop, students are guided through the discovery and analysis of life sciences data from multiple sites, encouraged to integrate text and data sources, and supported in completing research assignments.

The Development of Data Science Education in China from the LIS Perspective

“…Regarding computer science education, Wang et al (2017) identified data scientists, big data system engineers, big data algorithm engineers, machine learning engineers and big data algorithm scientists as five distinct data talents, and suggested enhancing the big data abilities of computer science students by developing course architecture with a focus on big data and big data tools. In addition to these two disciplines, with the significant impact of the new science paradigm, educational programs in journalism, economic management, business, publishing science, biological sciences and social science also become more data-centric with more concentration on their students' awareness and abilities to tackle big data problems (Shen et al., 2014;Kirkpatrick, 2015;Bichler et al, 2017;Yu, 2017;Macmillan, 2015, Stephenson & Caravello, 2007.…”

Are you ready? Tasks and roles for academic libraries in supporting Research 2.0

“…A 2014 review article on data management issues by MacMillan (2015) shows -among others -that librarians have to develop new expertise and much deeper understandings of the research lifecycle, if they want to remain relevant. As Ramírez (2011) put it, with the exponential growth of digital data and a higher use of digital repositories, librarians have to become expected liaisons between data authors and users.…”

Adapting data management education to support clinical research projects in an academic medical center

“…To address this need, librarians from academic institutions have been working to provide data management education and support to their communities. By developing specific approaches to creating data management education, libraries have found successful avenues in implementing stand-alone courses and one-shot workshops [7], integrating research data management into an existing curriculum [8], and offering domain-specific training [9]. Libraries have offered these training programs by providing general data management training to undergraduate and graduate students [10–12], doctoral scholars [13], and the general research community [14–20], whereas domain-specific data management can be seen most prominently in the life sciences [21], earth and environmental sciences [22, 23], social sciences [24], and the digital humanities [25].…”