ABSTRACT
Acquiring powerful abstractions — i.e.. representations that enable one to reason about key aspects of a domain in an economical and generic form — should be a primary goal of learning. The most effective means for achieving this goal is not, we argue, the “top-down” approach of traditional curricula where students are first presented with an abstraction, such as F=ma. and then with examples of how it applies in a variety of contexts. Nor do we advocate the “bottom-up” approach proposed by situated cognition theorists. Instead, we argue for a “middle-out approach where students are introduced to new domains via intermediate abstractions in the form of mechanistic causal models. These models serve as “conceptual eyeglasses” that unpack causal mechanisms implicit in abstractions such as F=ma. They are readily mappable to a variety of real-world contexts since their objects and operators are generic and causal. Intermediate abstractions thus give meaning to higher-order abstractions as well as to real-world situations, provide a link between the two, and a route to understanding.
