“Visualising knowledge – the next step: turning breadth into depth
And so the image we can use to turn horizontal learning into vertical learning is this: take your horizontal learning, your beads on a chain, and simply turn the chain through 90 degrees so that it is hanging vertically. Now just think of this as depth. What you have is a way to understand, for example and to use the quote above, the entire supply chain of a manufactured product from start to finish. You start with an understanding of engineering in order to consider how your product is manufactured, work up to how you will monetize, promote and sell your product (marketing/psychology) and perhaps end with an appreciation of how the product might be brought to a global market-place (economics and politics). Thus you have deep knowledge of the processes of your supply chain, but this can only be achieved by some understanding of each knowledge ‘bead’ on the chain – a chain which now hangs vertically, remember, giving you that idea of progression upwards, vertically.
This image of breadth giving depth in many real world problems (the sorts of problems that are often addressed in the literature about interdisciplinarity) is powerful. Why, then, is the importance of breadth so little understood or appreciated in universities and, indeed, by many external stakeholders?”
Well actually, ID learning is much more involved that merely changing the order of learning. Beads of a chain? It is not linear. In all life greater complexity usually means that we are greater than the sum of our parts. With ID learning, we are not looking at beads of a chain, we are looking at multiple chains in a web or a network. A better example would be think of a real world situation, such as designing a car.
You need engineers to build an engine, you need accountants to cost it, you need designers and artists to design the look and feel, you need sales people to help promote and sell the product. Anyone of those people on their own cannot design a car.
Take another example, solving Global Warming, you need scientists, you need politicians, you need economists… etc.
Think of another example that’s more personal. When you published your book, you needed to be a writer, an illustrator, a salesperson (to pitch your ideas to a publisher) etc.
I think that author does not really understand ID learning. What do you think ?