The DataUp program visited Old Dominion University on Oct 25-26 to introduce shell, git, R, and the JupyterHub. The workshop included students, faculty and staff eager to engage with the analytical tools. This workshop brought together a ‘melting pot’ of faculty, staff, and students from various corners of the university to engage in a 2-day workshop. The concepts were chosen by ODU as Unix Shell & R are utilized in their High-Performance Computing Center. Even though intensive, one student noted, ‘it’s like drinking from an 8-hour firehouse, but the information is great. I knew nothing before Day 1 and [now I feel] more confident [after the first day]’. The 2-person instructor team led the traditional Carpentries curriculum, but their instruction was magnified by multiple ‘workshop helpers’. In training workshops such as these, learners have various expertise levels and learning styles. Multiple ‘workshop helpers’ and instructors reinforced the concepts as the diverse point of views benefited the wide range of learning styles. This was especially beneficial to a professor who noted that she learned to code about 15 years ago and was very nervous to retool herself but, ‘this workshop helped [her] to remove her fear [of coding]’.
Usually, sharing personal use cases help learners to identify how to implement analytical tools into their research or classroom activities. One instructor shared the benefit of an open-source collaborative tool, such as JupyterHub, was the ability to assist individuals in other disciplines across the world. For example, he developed a code for his GIS research and a ‘community member’ was able to utilize the code for their aquaculture project. Although they’ve never met in person, together they consistently update the code for efficiency and future utilization. As research interests become more global, the ability to build a community and collaborate despite locale peaked individuals interest in the collaborative tool. Themes such as collaboration and connectivity were consistently highlighted throughout the workshop. It is no doubt learners and ODU will continue to harness these themes and work to increase their capacity for data analysis.