The Design and Effects of Educational Data Science Workshops for Early Career Researchers

Abstract

We report on the design, development, implementation, research, and iteration of two educational data science (EDS) workshops focused on using R and RStudio for 44 doctoral students with limited and varied EDS backgrounds. Through qualitative and quantitative analysis of pre- and post-workshop surveys, we found that participants in EDS workshops are concerned and even fearful, yet possess relevant assets that come from a wide range of background experiences. Pedagogical factors—including being patient amidst errors, coding collaboratively, and explaining technical concepts in an accessible and rigorous manner—were strengths of the workshops, while the need for more time was a key possible improvement. Furthermore, participants’ self-reported confidence grew from before to after the workshop. Based on our initial design, revisions, and research findings, we describe five formative design guidelines for educational data science workshops that address doctoral students’ goals and needs. In total, this work implies that well-designed workshops and short courses can offer opportunities for a wide range of educational researchers to extend their expertise with newer methods to carry out impactful work—in turn shaping the emerging EDS field.