Abstract cognitive enablers allow us to understand and manipulate multiple abstract concepts simultaneously.
Grasping and manipulating abstract concepts appears self-evident when we think about mathematics.
Multiplication of numbers involves two discrete abstract concepts. First, the concept of a written squiggle on a page being representative of an amount is an abstract concept. We don’t often think of abstraction in that way, but the symbolic representation of numbers, letters, and other symbols are very abstract and the ease at which we acquire the ability to understand and manipulate these abstractions is one of the things that makes us uniquely human. It isn’t that animals can’t be taught abstractions of this type. However, they rarely learn very many of them and it is difficult to teach them to really understand them.
One thing that we often take for granted when it comes to human development is the ease at which children, very young children, develop language skills. An extremely difficult task that is mastered with apparent ease. Moving abstractions from sounds to written symbols is also learned with amazing rapidity.
If we go back to math, children learn math quite quickly. However, we all know that most children struggle with word problems. When something learned in an abstract world is applied to concrete problems, something makes the process difficult. This is where we see the grasping of abstract concepts begin to separate itself from the manipulation of abstract concepts. We can learn and understand increasingly abstract concepts in math, but we have difficulty applying what we know to the concrete, real world.
This becomes increasingly difficult when a real-world problem requires multiple concepts to solve. Using multiple abstract concepts to understand something almost always involves breaking a problem into discrete steps and applying different abstract manipulations at each step of the way.
Adults can learn to manipulate multiple abstract concepts simultaneously, but not without learning how to do it and then putting in the time practicing until the process becomes automatic. Automatic, meaning cutting out numerous steps needed by a naïve learner in order to carry out the process. A good example is the difficult cognitive/motor/ task of navigating a busy intersection in a car that utilizes a standard transmission for the first time. The absolute nightmare that occurs when you first experience this becomes automatic as we carry out the same maneuver repeatedly.
So, how do we learn to complete a complex math problem requiring multiple abstractions? We learn it one step at a time.
The same principle applies to learning abstract cognitive enablers. These tools that can be used to understand and manipulate complex abstract information and processes need to be broken down into discrete abilities that can be learned individually and then combined to solve a problem. As the process is practiced and refined within an individual, the process becomes automatic and can be carried out almost effortlessly – just like turning into busy traffic in your sub-compact equipped with a standard transmission.
Over the next few weeks, I will do my best to outline how to teach and learn these enablers. I’ll begin with critical thinking, the abstract cognitive enabler claimed to be developed by virtually every higher education class in existence but almost never taught. I’ll use the discrete skill model of critical thinking that I have previously written about comprising the sub-skills of planning, cognitive flexibility, persistence, willingness to self-correct, directed and focussed attention, attentiveness, and consensus-seeking. By looking at how each construct is learned, we should be able to teach them.
It is difficult, but it is at least worth a try.
