CorrelAid-Data-Meetup with tidytuesday
Getting people involved with CorrelAid - an example from CorrelAid X Bremen
2020-01-06 | Hendrik
The CorrelAid Data Meetup is a format from the local chapter Bremen that started out in October 2019. Its scope is to establish a regular peer-learning course for beginners and advanced R users at the University of Bremen. We wanted to create an open space where attendees could learn from each other face-to-face.
Beginnings: Talking and networking
In a first step, we contacted university staff from the Faculty of Social Sciences. With them, we discussed possible formats. Holger Döring, Political Science lecturer, offered us to introduce CorreLAid X Bremen in his seminar about data visualisation as an example for data science in practice. Beyond that, he also let us reference to his name in order to have better access to university institutions.
Meanwhile, we contacted Birgit Ennen, who is in charge of an office for the integration of academia and job practice at our faculty (“Zentrum Studium & Praxis für Fachbreich 8”). She offered us a time slot for a regular meeting and access to official university facilities).
The meetup format would be presented on the University of Bremen E-learning platform and distributed through the faculty newsletter. Now, our job was to fill the blanks: What would the open meetup exactly be about? How could we achieve something that attracts students of different fields and expertise and spark their interest in joining CorrelAid?
With the assistance of Birgit Ennen and Holger Döring we created a seminar plan and an instructive discription for an open peer-learning experience:
1) Appearance on the E-learning platform StudIP.
2) Description of CorrelAid with dates and location.
Building on existing ideas
At the time of the initiation, we also picked up on tidytuesday. It was already an existing idea in the CorrelAid network to invite those interested in CorrelAid to weekly challenges as an accesible alternative to the skilled-volunteering projects. Tidytuesday we therefore considered to be a fitting existing framework. It is a repository of weekly challenges hosted by the R for Data Science community, including access to tidy data sets and some additional links that include examples of visualisations to replicate. The challenges mainly focus on data wrangling and visualisation with the tidyverse package.
Tidytuesday was first proposed as an online opportunity for individuals or groups in Slack. Based on that, we decided to present tidytuesday challenges as the core element of our meetup. On the other hand, participants should be encouraged to communicate their needs. The direction of the course should be open for discussion. The main goal was to foster self-organisation. That way, the group would decide what they wanted to learn and ideally assign tasks to each other.
Work in progress
We have seven sessions altogether planned for one semester. We meet regularly every two weeks for 4 hours (including breaks ;-)). There were 20 registrations for the course beforehand. By now, seven people are continuously participating. The attendees are practicing self-organisation. Throughout the session, participants are presenting some introductory input by themselves. At the end of every session, we gather open questions and assign the input for the next meeting.
That way, the focus of the course evolved. We did not yet do a tidtuesday challenge in a coordinated group efort. It was agreed amongst the participants that the group was not prepared enough to face the tidytuesday challenges right away. We have, by now, held four sessions with introductory input and learning examples provided in parts by the tutor and in parts by the participants themselves. The first dive into an actual tidytuesday challenge is set to take place in the upcoming fifth session.
To document our agreements and provide easy access to the results of our sessions, we use the E-learning platform StudIP. This service is offered by the university IT and is accesible for every regular student. The dashboard features a section for files, where we collect code examples, and an online pad for group interaction (StudIPad):
3) Access to studIPad on the E-learning platform.
4) Example of a pad created by the participants.
Some adjustments of expectations were necessary throughout the process. The tidytuesday challenges are barely the core element of our sessions by now. The goal has rather shifted towards preparing the participants for a future group coordinated tidytuesday challenge. It also turned out to be important to leave enough time for small talk and networking. I argue that the prospects of such a course rely very much upon the actual motivation of the participants. This motivation should be addressed right from the start, so the group can define their own goals.
I recommend to other CorrelAid X local chapters to try out a variation of this format. It proved to be a good way to get new people involved with CorrelAid, especially because participants value the opportunity to discuss various questions in a non-competetive learning environment. The peer-to-peer setting encourages less advanced participants to get involved. The tutoring of the course itself also turned out to be very useful for the deepening of my own understanding of the R programming language and its surrounding tools.
Hendrik is a sociology student at the University of Bremen and your contact person for the far north. He is enthusiastic about the idea of improving the world with data analysis and building a peer-learning network of motivated people in the North.