At Griffith, we found that it was hard to crack a lot of silos hidden in our institutes. While we advertised widely, it was worth going into HDR rooms that were likely to be doing R or Python (usually your data scientists) and talking to them.
The areas of research that you will find get the most attendance from Hacky Hours:
- Environment
- Bioinformatics
- Chemoinformatics
- Allied Health
- Medical
- Psychology
- Social Marketing
Please do add other areas to target.
Career path wise, we found most people who attended were Higher Degree Researchers and Early Career Researchers. The occasional Professor will stop by but not often. We also get Librarians and other general staff stopping in from time to time, either to catch up or share the work they are doing.
Dr Nick Hamilton at University of Queensland has shared his poster of demographics . He has highlighted many of the problems faced at Hacky Hour are R related (24), Python related(13) and HPC/Cloud related (13) which closely reflects our findings. He also found many of the attendees were female at 65.2% however the helpers were still male orientated.
Another finding which at was also reflected at other universities was that the bioscience field was highly represented in attendees.
As we generally get a similar crowd to those doing Software Carpentry, you may find this article interesting on the demographics and languages people learnt from Software Carpentry https://zenodo.org/record/1039944#.WgIpSN9fhhF Otherwise, there have been studies such as https://zenodo.org/record/14809#.WevWzZ8xDCJ that can highlight areas to target.
Here is a suggested list of demographics to collect each session:
- Date
- Name
- Male/Female
- Attended prev (Y/N)
- Type (Helper/Problem)
- School/Group/Institute
- University
- Subject of Problem
- Feedback/Notes