Ad hoc efforts for advancing data science education

With increasing demand for training in data science, extracurricular or “ad hoc” education efforts have emerged to help individuals acquire relevant skills and expertise. Although extracurricular efforts already exist for many computationally intensive disciplines, their support of data science education has significantly helped in coping with the speed of innovation in data science practice and formal curricula. While the proliferation of ad hoc efforts is an indication of their popularity, less has been documented about the needs that they are designed to meet, the limitations that they face, and practical suggestions for holding successful efforts. To holistically understand the role of different ad hoc formats for data science, we surveyed organizers of ad hoc data science education efforts to understand how organizers perceived the events to have gone—including areas of strength and areas requiring growth. We also gathered recommendations from these past events for future organizers. Our results suggest that the perceived benefits of ad hoc efforts go beyond developing technical skills and may provide continued benefit in conjunction with formal curricula, which warrants further investigation. As increasing numbers of researchers from computational fields with a history of complex data become involved with ad hoc efforts to share their skills, the lessons learned that we extract from the surveys will provide concrete suggestions for the practitioner-leaders interested in creating, improving, and sustaining future efforts.Author summary: Large datasets are becoming integral to society broadly and to biological sciences in particular. As a result, demand for sophisticated data skills and experience has skyrocketed and left some individuals scrambling to cross-train and acquire more computational skills. While universities are racing to develop formal curricula to meet this demand, diverse informal efforts have emerged to fill the immediate demand for skills and experience. These “ad hoc” efforts have been playing a vital role in data science education, especially for domain scientists. While some studies have shown specific ad hoc formats to have considerable impact, few studies have focused on these efforts holistically. Here, we survey effort organizers from leading data science institutes and collect lessons learned. We find that efforts are commonly reported to successfully provide opportunities in difficult areas where curricula could improve, such as providing approachable introductions to new skills, increasing diversity of backgrounds, and fostering heterogeneous communities. However, efforts also report challenges fulfilling diverse needs and offer suggestions. In total, the lessons that we collect from these efforts are useful to improve future ad hoc efforts and to inform formal programs, which may be looking for inspiration to design innovative educational formats.