Courage, Failure and Trying Again — When the barriers are high, soldier on.
My DMI Goals
the very beginning of this module, Dr. Burke began with a little pop-quiz to test our ignorance of the world. Suffice to say, most of the class did not fare well, myself included. The exercise he brought us through was inspired by Hans Rosling, a professor of international health among many other achievements, lifelong work on how we use information and how to do that better.
Known for his famous ‘bubble’ charts which capitalise on huge data sets and eye-opening software, Rosling’s TED talks are full of lofty idealism and a healthy optimism. Crucially, it is how he challenges assumptions through “unveiling the beauty of statistics for a fact-based world view” (as poetically put by the mission statement of the independent educational non-profit he is associated with) which makes him an inspiration for any budding data scientist out there. International audiences consistently overestimate the figures for world poverty, underestimate the global averages for life expectancy, and in general, assume a quantitative pessimism towards the world than what is reality, as indicated by data. In the posthumous book “Factfulness”, the Rosling family unpack the various cognitive biases that colour our worldview in black and white and encourage a more interrogative thinking habit which they (of course) term as ‘factfulness’.
What does this all mean for my own experience in UQR2215?
Well, to begin with, much of my own journey with data and numbers have begun with fear and ended in more fear. I have never considered myself data literate, and my technical skills are very much on a beginner’s level. Hence, when I had first stepped into the Meaningful Indicators class, I had no idea what to expect. But as time progressed, I found myself paralysed with fear — fear of not knowing what to do, and not knowing how things would turned out.
I then decided that I should return to where we first began with this module and break out of this box of fear through some of the excitement that Rosling provided with his take on the world. I read Rosling’s book in hope that I would receive some inspiration on how to move forward with the rather daunting and overwhelming catch-up I would need to play in UQR2215. To my surprise, Rosling had addressed the crippling fear I had with regards to data by emphasising the fear instinct and had suggested some solutions! He defines fear as a predisposition to systematically overestimating risks of attention-grabbing circumstances.
Notably, his recommended solution in overcoming the fear instinct is to calculate risks. His insight on what risk is was particularly insightful:
Risk = danger x exposure. The risk something poses to you depends
not on how scared it makes you feel, but on a combination of two
things. How dangerous is it? And how much are you exposed to it?Get calm before you carry on. When you are afraid, you see the
world differently. Make as few decisions as possible until the panic
has subsided.
What were the risks when it came to making own data visualisations?
The things that had paralysed me in fear were bound in these thoughts — If don’t have enough context, and don’t really know what the topic is about, can I make a meaningful visualisation? What happens if the chart is not aesthetically pleasing? What if I have an idea but do not have the technical skills to carry it out? What if public opinion about the chart becomes so bad I get kicked out of Reddit? :O
And then, I realised — the What-Ifs have loomed so large in my head that I had failed to truly consider and manage the risks.
When, really, the only thing I can do for this class is to simply try, try, and try again.
This is a class — and what a class does is that it creates healthy boundaries and a safe space to fail.
The fear of failure has caused my own perspective to be coloured by a distinct lack of agency and control. What I simply needed to learn in the 4 walls of DMI was the courage to breathe, fall, and get back up.
In another USP class I had attended , Prof Bart hadintroduced us to Sternberg’s article on “Why Schools Should Teach for Wisdom: The Balance Theory of Wisdom in Educational Settings” and it reminded me a lot about the workload for Developing Meaningful Indicators.
Sternberg defines wisdom as “a particular kind of practical thinking that (a) balances competing intrapersonal, interpersonal, and extrapersonal interests, (b) over the short and long terms, © balances adaptation to, shaping of, and selection of environments, in (d) the service of a common good.”
In my opinion, DMI is an educational setting which provides a ‘safe’ environment for failure are an ideal setting for teaching wisdom.
Why so? Because, if one believes Sternberg (as I’m inclined to), the heart of wisdom is tacit, informal knowledge learned in the school of life, and these tend to be sharpened by hardship/failure.
Then, there is the analytical thinking also required in wisdom. In this case, analytical thinking would refer to the “analysis of real-world dilemmas where clean and neat abstractions often given way to messy and disorderly concrete interests”. The exposure to multiple roads an individual can take and the teaching of how to form your own interpretive framework to guide your choices seem to suggest an element of learning how to fail when you make the choices with more difficult journeys.
Yes, I may lack the technical skills or contextual knowledge. But that’s okay.
The point of this class is to dip my toes in academic terrain that both intimidates and is unfamiliar.
The point is to be exposed to the new and many wonders of data visualisation and how data can inform better choices and more informed opinions.
The point is for courage.
The courage to pursue new interests and the things I love and make meaning in gaining clarity on the things I value and hold dear.
With that in mind, here are my objectives for the class:
- Technical Skills. Improve the time I take in crafting a visualisation, exposing myself to skills like data-cleaning and data literacy, and trying out different styles of visualisations and visualisation tools.
- Meaning. Finding out my voice and story I want to tell with the data I visualise.
- Courage. This here is the goal that underlies and propels my every opportunity for learning in this class. The determination to learn from anyone, anything and everything!
