Teaching researchers essential skills for digital science
With increasing number of data sources and digital tools playing a key role in today’s scholarly research, mastering the essential skills to efficiently deal with such data and tools becomes indispensible for academic researchers. To run our research projects at the eScience Center in an efficient way, it is important that also our collaborators at universities develop the right digital skills. These skills include
For this purpose we organized three workshops for our project members based on the Software and Data Carpentry model. The workshops focused on Version Control with Git & GitHub, Scientific data analysis with Python and Unix Shell & Task Automation.
In this blog post we share some experiences of our essential skills workshops so far.
Note: On 6 November 2017 the workshop Research Data Handling will be held (you can still register).
Demagification of essential skills
The workshops covered the topics of Github, Shell and Python, giving the participants the basic knowledge of these topics. So, were participants experts in Python after the training? Of course not — it takes years of practice to become an expert in any of these topics. Why then run such a short workshop? Well, our aim is for participants to have a good basis to start learning by themselves after the workshop.
Mateusz Kuzak demagifies digital science
Mateusz Kuzak (instructor) calls this the “demagification process”: at first, it looks like magic — an engineer types some magic commands on a black screen and poof magic happens. But when you start to understand that these commands are nothing magical and that they are just like a recipe, it feels less like something magical and unachievable and more like a super power which you can also learn. In the end our aim is for learners to understand that they can also learn how to use these powers (although, not from a Jedi).
“After the course I found that it is much easier for me to learn and use Python”
That is exactly what we are aiming for!
Personal interaction for maximal learning experience
The workshops were attended by 15–20 people, which enabled the various instructors from the eScience Center to spend sufficient time with individual participants. Afterwards, workshop participants pointed out that this was really beneficial to them because in this way they could maximize their learning experience. One participant commented:
“I sincerely appreciated the amount of staff around. Besides being absolutely up-to-par for the job, the amount of people covered issues very well which resulted in quick help, where help was allowed to breathe and explain things properly instead of rushing to finish problems due to understaffing.”
What feedback told us
After the workshops, participants shared their feedback on the workshops through a short suvey. Overall, participants indicated that having attended the workshops will really help them to do much of their work in a more efficient way. Also the hands-on approach, insteading of lecturing, was highly appreciated. Furthermore, the Python workshop participants appreciated the use of Jupyter Notebooks and the introduction into data analysis with Pandas. Also the introduction to Make in the Shell & Task Automation course was positively reviewed and could perhaps receive some more attention in the future.
For the Python course, various participants suggested to split up the workshop in two levels: a Beginner and an Intermediate/Advanced Python workhop. Perhaps the most positive reviews were probably coming from the workshop on Version control with Git & GitHub. One participant wrote:
“This workshop is very helpful and in time. I have been trying to teach myself about git and github for a while and I was able to use it to some extend. But only after attending this workshop, I have a crystal-clear idea about the whole framework! Attending this workshop greatly shortened my learning curve. I will be able to use git and github in a much more efficient way now. My students and I will now be able to collaborate better on github now. This also will contribute to my on-going e-Science project. I will highly recommend it to my colleagues and students.”
What’s next?
For our learners, we hope that this workshop has been only the first step on the learning path and that they will be able to continue on this path. For us this was also a learning experience and we will strive to run more workshops aimed to increase knowledge and improve the quality of science!
Want to learn essential skills for digital science as well? Stay up to date! Sign up for our newsletter in which we will announce future workshops.
