Thoughts from ICTLT 2012: The similarity between deep learning and slam dunking

Even if you’re not  basketball fan like me, that photo above of Blake Griffin tomahawking over a hapless Channing Frye surely rouses some emotion in you. Be it awe at the power or amazement at the athleticism, you feel something.

The just concluded 2012 ICTLT conference left quite a deep impression in me. Different presentations touched on various ideas, ICT tools and organisational systems in support of innovation but the main theme I discern is that we’re all interested in authentic deep learning. Learning for its own sake, learning that takes root and leaves a deep impression in the student. I feel like this deep learning is analogous to the slam dunk in basketball.

In basketball as in education, which team wins depends on the score, the end result. A slam dunk, no matter how graceful, how powerful, is just worth 2 points on the scoreboard. Deep learning of a topic or concept, no matter how spine-tingling, how inspiring, often just shows up as maybe 5 marks on the scoresheet. And if your topic of deep learning was unfortunately not asked in the exam questions, it may be worth nothing on the scoresheet.

A true basketball aficionado will of course tell you that a slam dunk is worth way more than 2 points. It rallies the crowd, transmits energy to the rest of the team and satisfies that psychological need for creativity (a dunk is often the result of creative play rather than just raw power). A true educator will of course tell you that deep learning is worth more than what might be displayed on a results slip. Many an educator has experienced that indescribable feeling when a student points out something he/she discovered on their own that you did not even consider in your mental schema.

So teachers, educators, when you feel like giving up on deep learning and just succumbing to society’s penchant for only focusing on academic results, remember that nobody will watch basketball without slam dunks and similarly nobody is truly educated without deep learning.

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