David and I came to recognize that these three ways in which to conceive and construct a curriculum were actually paradigms! It seems that paradigms exist not only in scientific realms, but also in areas of diagnosis and design. We went further in our analysis and identified a process for working with academic teams. We noted that specific Models seem to emanate from (or help to modify) the fundamental paradigm. The models, furthermore, are often imported from other fields. When they are imported these models bring with them some underlying assumptions, ideas and perspectives from their original field. With the models in play and with one or more underlying paradigms informing and reinforcing these models, a community (such as an academic department) can produce specific Practices (what Kuhn called “normal science”).
Halliburton and I began to refine this Three Assumptive Level framework. We proposed that Paradigms in a particular field or discipline tend to be:
(1) Few in number,
(2) Quite simple in construction, and
(3) Very powerful.
As an example, David and I often pointed to the analytic tradition that is to be found in many of the physical, biological and behavioral sciences: we break things down to their fundamental parts in order to best understand them and then we reassemble them. David always pointed to the “smashed frog” critique in biology: when we dissect a frog in the biology class, we might find out how the frog’s leg works and how the frog’s brain is connected to other parts of its body via the spinal cord. However, we can never bring the frog back to life. The parts can never be reassembled to create a living organism. This failure to create life remains a mystery and relates to what some philosophers and scientists refer to as “emergence” (the unexpected creation of new, higher order phenomena by integrating several lower order phenomena: the whole can’t be predicted from the parts)
In the case of Models, David and I proposed that they are:
(1) Based on paradigms (though the underlying paradigm might not be acknowledged—being part of the tacit knowledge base proposed by Michael Polanyi),
(2) Moderately large and diverse in number,
(3) Moderately powerful and influential, and
(4) Often borrowed from contemporary popular technologies.
