Implementing a Graduate-Level Research Data Management Course: Approach, Outcomes, and Lessons Learned

Abstract

INTRODUCTIONAs data-driven research becomes the norm, practical knowledge in data stewardship is critical for researchers. Despite its growing importance, formal education in research data management (RDM) is rare at the university level. Academic librarians are now playing a leadership role in developing and providing RDM training and support to faculty and graduate students. This case study describes the development and implementation of a new, credit-bearing course in RDM for graduate students from all disciplines. DESCRIPTION OF PROGRAM The purpose of the course was to enable students to acquire foundational knowledge and skills in RDM that would support long-term habits in the planning, management, preservation, and sharing of research data. The pedagogical approach for the course combined outcomescentered course design with active learning techniques. Periodic course assessment was performed through anonymous student surveys, with the objective of gauging course efficacy and quality, and to obtain suggested modifications or improvements. These assessment results indicated that the course content and scope were appropriate and that the active learning approach was effective. Assessments of student learning demonstrated that all major learning objectives were achieved. NEXT STEPS Information derived from the student surveys was used to determine how the course could be modified to improve student experience and the overall quality of the course and the instruction. INTRODUCTIONThis paper describes the development and implementation of a new course for graduate students in selected aspects of data information literacy. The idea of creating a creditbearing, graduate-level course was conceived during a meeting between two members of the library's Center for Digital Scholarship and Services and two high-level administrators of the Graduate School. Our library-based data services were just becoming established, and we were beginning to open lines of communication with university stakeholders. A major point of discussion during this meeting was the idea of preserving the datasets that underpin graduate student theses and dissertations in our institutional repository (IR). Our Graduate School mandates the deposit of an electronic copy of the thesis or dissertation (ETD) into our IR in order to graduate, and those of us at the meeting were discussing adding a mandate for the deposit of student datasets as well. We all had to concede, however, that many graduate students would probably not be prepared to deposit a dataset into the IR because they would not have received any formal training in data management during the course of their programs, and as such, their data would not be in sufficient condition to be shared (i.e., be well organized and sufficiently documented). If preserving and sharing the datasets produced by graduate students was to be a shared goal of the Graduate School and the library, then we had to develop and provide a mechanism that would empower students to be able to realize that goal.Our libr...

Integrating Data Science Tools into a Graduate Level Data Management Course

“…Teaching research data management to graduate students is a trend within information literacy instruction (Carlson et al 2011;Qin and D'ignazio 2010;Whitmire 2015). A variety of pedagogies have been used, including one shot guest lectures (Westra and Walton 2015), online courses (Johnston and Jeffryes 2014b), traditional courses (Bracke and Fosmire 2015), workshops (Adamick, Reznik-Zellen, and Sheridan 2012), team-based active learning (Clement et al 2017), and blended learning (Zhang, Goodman, and Xie 2015).…”

Teaching Practical Research Data Management Skills through Online Training and Data Management Plan Creation

“…RDM courses primarily fall into two types of instruction format: workshops, either as a standalone course or as a series of sessions (Clement et al, 2017;Goben & Nelson, 2018;Helbig, 2016;Peters, 2017;Southall & Scutt, 2017); or online courses, allowing for learning to take place as it is convenient (Furukawa et al, 2018;Rice, 2014;Si, Xing, Zhuang, Hua & Zhou, 2015) and whenever it becomes directly relevant to research practice (Ward & Freiman, 2011, p. 269). Graduate RDM courses delivered as lecture series by librarians are rarer (Corrall, 2012;Whitmire, 2015), and this format is too resource-intensive for implementation in our institutional context. RDM online courses seem to be of great interest, with greater numbers applying than would be expected (Furukawa et al, 2018).…”

An epic journey in sharing: The story of a young researcher's journey to share her data and the information professionals who tried to help

“…Education about the "what" and "how" of data sharing builds awareness around good practices, resources, and tools. Different pedagogical methods have been used by the RDM community including asynchronous online trainings (EDINA, 2017), in-person workshops and trainings, data management curricula within the classroom (Whitmire, 2015), as well as data stories (DataONE, n.d.). However, conceptual education can only go so far, the actual "doing" of sharing data provides essential real world experience and lays the groundwork for future sharing.…”