Equipping for the future: from know-how to judgment
‘Let’s restore learning to the days when it taught practical skills and knowledge.’
That was the message I received last week from an acquaintance, who forwarded a rather amusing test paper, contrasting how the nature of math questions has changed over the last 60 years. It started with the following:
“A logger sells a truckload of lumber for $100. His cost of production is 4/5 of the price. What is his profit?”
Over the years, the problem becomes steadily simpler so that by 1996 it requires students to successfully underline the number 20. By 2016, the question has altered fundamentally:
“A logger cuts down a forest, caring nothing for the habitat of animals or the preservation of our woodlands. He does this so that he can make a profit of $20. What do you think of this way of making a living?”
At first, I had some sympathy with his comment. It seemed quite reasonable to expect children to learn basic mathematical skills, rather than abstract and, in this example, politicised thinking. But as I reflected, I realised how wrong I was to think that way – and how right the test is to move education in the direction it has.
Back in 1956, when the first test question on the sample paper was posed, there was no automation. Mental arithmetic was a fundamental requirement. It was essential to navigate through everyday life. Knowledge workers were largely a thing of the future because most work was manual.
Today’s children live with knowledge at their fingertips. If they want to discover a percentage, or the meaning of profit, they look it up on their phone or laptop. What they increasingly need in order to flourish in a networked world is empathy and judgment – two things that machines cannot yet provide.
So while I may disagree with the way the 2016 question is written, the fact that an answer demands empathy, analysis and judgment is fully reflective of the skills and competencies that young people now need.
This is a salutary lesson for all of us as we think about the elements of our knowledge and work activities that remain relevant in a machine-driven age. While commercial judgment is key and empathy and analysis are critical, traditional management of repetitive or memory-based tasks and processes will soon be consigned to being something we did in the past.