According to research on naturalistic decision making, proficient
decision makers are recognitionally skilled.
They are able to recognize a large number of situations as
familiar and to retrieve an appropriate response. In these
kinds of situations, they are able to act quickly and effectively
Recognition falls short, however, in unfamiliar, novel, and
uncertain situations, where no pre-existing pattern fits.
The classical point of view is that decision makers must then
switch from intuition to analysis: They break
the proplem down into components, make judgments regarding
each component, and then put the pieces back together again
by a mathematical formula that leads to an "optimal"
solution. This analytical process is time consuming and demanding.
There is often no more reason to trust the inputs to such
an analysis as there would be to trust a direct judgment about
the best decision. And the results are typically not in a
form that can directly support concrete anticipation and planning.
According to naturalistic decision making models, on the
other hand, analysis is not the only tool available for real-world
decision making in novel and complex environments. Another
key component of proficiency or expertise is the ability to
adapt pre-existing knowledge to fit new circumstances. The
Recognition / Metacognition model, developed
by CTI, provides a general, systematic, and precise account
of processes that decision makers use to understand and plan
in such situations.
According to the Recognition / Metacognition
model, proficient decision makers are both recognitionally
and metacognitively skilled. Proficient decisions
makers adopt a two-tiered strategy: (1) recognitional activation
of expectations and associated responses, accompanied by (2)
an optional process of critiquing and improving the products
of recognition when necessary. Together, these processes build,
verify, and modify mental models (or "stories")
to account for a relatively novel set of events and to construct
effective plans. Decision makers reflect on and improve the
results of recognition, but do not reject recognition altogether
(as in analysis-based approaches). Also by contrast to analysis,
a soltuion is always available if time runs out: immediate
action can be taken on the best solution so far. No matter
how they evole, the decision maker always has a situation
picture and plan together with an appreciation of its strengths
We have developed a computational
model of these critical thinking processes and have created
and tested training
and decision support
methods based on the model.