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Osman Yaşar ( firstname.lastname@example.org) is an Empire
Innovation Professor at the State University of New York,
The College at Brockport.
The author thanks Jose Maliekal, Peter Veronesi, and
Leigh Little for their collaboration and comments;
also grateful to Pınar Yaşar, who helped form the
epistemological perspective expressed here.
Support was received from the National Science
Foundation via grants EHR 0226962, DRL 0410509,
DRL 0540824, DRL 0733864, DRL 1614847, and
DUE 1136332. The author’s views expressed in
this Viewpoint are not necessarily those of his employer
or the U.S. federal government.
Copyright held by author.
An interdisciplinary perspective on
the cognitive essence of CT has been
presented here based on the distributive and associative characteristics
of information storage, retrieval, and
processing by a network of neurons
whose communication for searching,
sorting, and analogies is driven by
neural connectivity, richness of cues,
a trade-off between simplification and
elaboration, and a natural tendency
to minimize energy usage. This broad
approach might help clear some of the
trouble spots with CT while putting it
on a higher pedestal through a link to
cognitive competencies involved in science and engineering.
Everyone cognitively benefits from
CT by the virtue of having a computational mind. All we need is to help them
use it in a more systematic way in their
lives and professions. Since M&S facilitates an iterative and cyclical process of
deductive and inductive reasoning, it
could be used to teach novices not only
critical CT skills (for example, abstraction and decomposition) but also ST
and ET skills, including formation and
change of hypothesis, concepts, designs, and models. While these are no
different than cognitive processes of
ordinary thinking, 26 not everyone uses
them as consistently, frequently, and
methodologically as computer scientists, natural scientists and engineers.
The good news is they can be improved
later through training and education.
CT’s universal value is far beyond
its relation to cognition. I argue that
all heterogeneous stuff behaves computationally, regardless of what drives
it. And, iterative and cyclical form of
such behavior appears to be the essence of natural dynamism of all discrete forms. M&S is such a pattern, and
putting computation in this fashion at
the heart of natural sciences provides
an opportunity to claim that computer
science deals with natural phenomena, not artificial (digital). The computational revolution started by Turing
may eventually be how our knowledge
can come together to make more sense
of our world.
One of the calls for action here
for the CS community is to put more
emphasis on M&S as a crucial part
of student practice and education.
This may help pave the way to teach
computing principles to non-CS stu-
dents. 12 Furthermore, while educa-
tional researchers have done a good
job of measuring the impact of M&S
on learning, a focus by the CS commu-
nity can help generate interest among
educational researchers to do similar
research by measuring M&S’s impact
on conceptual change, abstraction,
decomposition, and metacognitive
skills, particularly in relation to CT
and programming education. The
second call is that prior to teaching
students electronic CT skills, we need
to teach them a habit of conceptual
change through iterative and cyclical
practices of inductive and deductive
reasoning. Besides M&S tools, re-
searchers should explore other modu-
lar and scalable design toys as well as
reading and writing practices to offer
similar CT practices.
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