Data Literacy is the ability to read and make sense of data. With data being ubiquitous, this is a fundamental skill for our times.
The emergence of cloud technologies, real-time dashboards and the expectation of making data-driven decisions is something that affects most professions.
In education, we can no longer submit to teaching data like this:
Before we embark on planning data lessons (and maybe all lessons), we need to ask ourselves 3 questions :
- Who cares?
In the example above, we would be asking, ‘Why is this data important?’ If it’s not, let’s not bother to examine it or bother to collect it.
2. Why are we gathering data?
If it’s not to help us understand a problem or solve a problem, it’s probably pretty useless.
3. What is the most useful way to share the data?
Data doesn’t really get shared in traditional formats (like the example above) anymore. A couple of sources have really challenged our thinking about graphs and data. So much so that I’ve started to refer to graphs as ‘data displays’.
So, where to now?
We went to youcubed.com to check out their examples of data science lessons. I was challenged on my perceptions about data by this activity about an emoji graph.
Is this even a graph? I wondered.
So, I investigated further… The New York Times suggests brilliant learning engagements about Data called ‘What’s Going On In This Graph’. Here’s an example:
There are some surprising and challenging examples on their site that we, as a Year 1 cohort, examined. It helped us to think about why, what and how we would collect data. And, how we might best share it with others.
Now, I bet you’re asking, so can the students interpret regular data displays?
As Jo Boaler’s research confirms, based on a follow-up interview 4 weeks later, every student was able to interpret a regular data display at 12 months above their grade standard. And, they can interpret contemporary data, too. What a gift!