Data literacy through self tracking
Discovering that teenagers may not be inclined to immerse themselves into data work, we will this Spring be testing new concepts and ideas, to investigate how we might grab their attention.
One topic that seems to transcend age and gender is the universal subject “me”. A deeper understanding of oneself is something most people long for, and is probably part of the reason self-tracking has become such an integrated part of our everyday lives.
Teens are furthermore known for being notoriously self-absorbed, and with that in mind, we wanted to do workshops for schoolchildren using the MUSE headbands. By letting them measure their own brainwaves, we were hoping to titillate their curiosity, and motivate them to working with visualizing the data afterwards.
The MUSE headbands are very easy to set up, and we use the app Muse Monitor to track and record the brainwaves. The recordings can be directly added to a Dropbox in .csv format.
The next step is to import the data into a spreadsheet (e.g. Microsoft Excel), and without detailed knowledge of data cleaning or analysis, convert it into different charts and diagrams.
We were aware, though, that the teens needed precise instructions, in order to perform the tasks in the workshop. Still, we were surprised by how much instruction they actually needed.
They were as expected very interested in the MUSE headbands, actually so excited that they created way too many and inaccurate data sets, instead of following our instructions and focusing on getting two-three useful data sets.
Another challenge was the openness in interpreting brainwaves. The teens were expecting to get a straight answer – e.g. if my brainwaves look like this, it is because I’m [smart or creative or easygoing or…] and working with brainwaves (and especially as your only source of input) there is no clear 1-to-1 mapping. So, they were a little disappointed by the results.
“They were scientists finding out the best ways to get teenagers to be sleepy (and get to bed at an reasonable hour).”
On the positive side, they were engaged and all of them eager to see their own brainwaves. They were also convinced by the frame of the workshop: They were scientists finding out the best ways to get teenagers to be sleepy (and get to bed at an reasonable hour). Though the concept of a study design was both difficult and new to them.
At this moment we are adjusting the scope and structure of the workshop. We need even more detailed instructions and we need to scale down a little to spend more time on the essentials:
- Study design: What does the angle of our research mean in terms of the data we collect?
- Data gathering: Why is it crucial we follow our initial study design instead of just going with the flow and creating lots of excess data?
- Data visualization: What happens when we clean and analyse data, so it can presented in a visually appealing way?
- Datastory: How do we create a context or narrative around our data, to make it compelling?
When we are done adjusting, we will be doing another set of workshops for schools during Fall 2019. We will later this spring also be testing the MUSE headbands with the library users, and see if they will be equally curious to see their own brainwaves.
DataDemocracy 