34. Building an Integrated Data Training and Support Model for Graduate Students

Graduate and undergraduate researchers often lack formal training in data, analysis, and coding, and have limited training in statistical applications. Departments, student groups, libraries, and research computing units occasionally and sporadically address these gaps, offering workshops, online learning materials, etc. While well intentioned, these can lack a connected and scaffolded pedagogical approach, in particular one that connects this work throughout the research life cycle and to broader campus computing supports. The result is often task-oriented, as opposed to conceptually oriented learning opportunities generating transferable skills that traverse specific tools.

At the University of British Columbia’s Okanagan campus, the Library and Research Computing have partnered to build an array of supports – workshops, consultations, drop-ins, and online learning materials – designed to meet learners at their point of need and support them through the early stages of their research careers. Principles of RDM, transparency, and reproducibility are woven throughout, and each support is integrated with the next: learn foundational concepts for RDM, data analysis and statistical computing, as well as the tools to interface with HPC infrastructure at a workshop, book a consultation to map these to a specific project, revisit online materials for a refresher, and drop in to ask follow-up questions.

This pilot project, funded through internal grants, provides experiential learning opportunities for graduate students, connects early career researchers with research support units, and bridges gaps in the transition from core subject area learning to computational approaches to expand the breadth of how research is conducted and disseminated.

Our poster will discuss our experiences building relationships across research support units, how we’ve implemented our pilot, uptake across faculties, and future directions.