Racing to Keep Up
From a learning perspective, learning as we did 30 or 40 years ago is not going to help us keep up with the volume of knowledge being generated. No, our learning needs to text two step improvements and more important then ever is going to be for us to decide what to learn and focus on and when to switch.
When I was learning Control Systems in school, I struggled. I applied the learning mode that I knew: sit down, read, and do problems. I tracked the the time I sat in that seat and focused on learning. I took breaks every 50 minutes to maintain focus. For one of the five control courses, I spent well over 100 hours sitting and preparing for the exam (that’s also with four other exams being written that needed similar attention). I still failed miserably.
I was reading but getting nowhere. My eyes would glaze over but I’d keep pushing thinking that just a few more hours would lead to a breakthrough. Nothing. It was only until one prof used metaphor to help me understand the concepts that everything clicked into place. It then required only a few dozen hours of practice to master the material vs potentially limitless amounts.
Why is this relevant today? We have new concepts that are being developed that are puzzling to many of us and were hardly on our radar a decade ago. AI, blockchain, quantum computing, CRISPR, and more are just vague buzzwords to most of us but will have profound impact. How are we to learn what they are?
New learning might involve super short clips, immediate knowledge tests, and developing metaphors. It might involve presenting us with 10 different modes of learning to hone in on the best. It won’t be static.
What we can hope for is that existing topics will be mastered much more quickly and that new concepts will use these teaching methods to get us caught up as new subjects come to the fray.
