Recent research found little carry over from short-term trainings or bootcamps into daily research activities of PhD students (Felton et al. 2017 PNAS). The National Ecological Observatory Network (NEON) offers annual week-long data intensive trainings (NEON Data Institutes) that aim to teach key analytical techniques for working with NEON and NEON-like data within a reproducible science framework. A key learning objective of the trains ins that the participants will learn important skills related to reproducible science including version control, scripted workflows, and best practices for data management. Importantly, the training is designed so that participants work with the data of interest in this reproduce framework throughout the training and will then incorporate the reproducible research framework into their own research workflows after the NEON Data Institute. This paper aims to measure the effectiveness of the training on reproducible research and carry over into participants’ post-training research workflows. We conducted surveys before, immediately after, and 6-months after the training to measure perceived importance of the topic, gain/retention of knowledge, and implementation of practice.
Results/Conclusions
A total of 50 people (advanced undergraduates, graduate students, post-docs, faculty, and agency researchers) have participated in NEON Data Institutes since 2016. In total 88% of participants completed the immediate post-survey and 56% completed the 6-month follow up survey. Paired sample t-test showed that participants’ knowledge in areas taught in the institute had significantly improved in both years (2016: μpre=0.70±0.40; μpost=0.90±0.25; t=-37; p<0.01; 2017: μpre=0.82±0.02; μpost=0.89±0.2; t= -2.45; p<0.01). On the 6-month follow-up 96% of respondents stated that they had shared skills or knowledge gained with colleagues. This demonstrates a broader impact of these training programs through a transfer of knowledge. Of respondents to the 6-month follow up survey, 91% respond that they sometimes (40%) or frequently (51%) apply the skills learned in the NEON Data Institute. After 6 months, we also found increases in the number of individuals who applied reproducible research practices like commenting their code. The number who did so at least weekly increased from 40% to 70% and the percentage who never commented code decreased from 12% before the Institute to 0% after the Institute. Overall participants going through the week-long Data Institute report application of reproducible research skills into their research workflows after completing the training.