Zhou, Xuan2023-09-052023-09-052023-05-17https://hdl.handle.net/2249.1/156906TCDL 2023 Session 2A, Wednesday, 5/17/2023, 9:00 am to 9:45 am | Moderated by Heidi Winkler, Texas Tech University | Presentation | Research, ScholComm, & Digital HumanitiesProviding ongoing data management instruction for graduate students has become increasingly prominent in research projects. In Research Data Management (RDM), many researchers have identified different data management skill sets required for data curators, researchers, or students. Yet, literature does not provide sufficient evidence for determining the need for RDM training from social science student researchers’ perspectives. To our knowledge, few empirical studies exist that examine social science graduate students’ RDM practices. Understanding students’ experiences with research data and research data training, and their perception of RDM—identifying their data core competency status—can help develop a knowledge base for RDM education. Our research designed a pilot study for a data core competency measurement to examine how important data competence was regarded by social science graduate students and the status of their data core competence. Results demonstrated the importance of building an academic atmosphere where RDM best practices are valued in graduate social science programs. Additionally, we launched a pilot exam to evaluate students' data core competency using 16 questions to address each stage of the research data life cycle. Future studies on the development of standardized data core competencies measurement are suggested to build on our preliminary findings.en-USresearch data managementdata literacygraduate studentssocial sciencedata core competenciesPresentation