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3 Looking Outward
Pages 33-44

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From page 33...
... The conceptual space to which computational thinking applies is much broader than most people imagine, and many of the advances are independent of the usual constraints on natural science. 3.1.1 Mathematical Thinking Computational thinking is closely related to, but not identical with, mathematical thinking.
From page 34...
... . Paulo Blikstein highlighted that since both mathematics and computational thinking are tools for representation, there may be an opportunity to use computational thinking to represent complex processes and relationships in a more comprehensible manner than mathematics.
From page 35...
... Peter Lee noted that several of the 14 engineering grand challenges for the 21st century identified by the National Academy of Engineering had a strong information technology/computer science/computational thinking flavor to them. These included reverse engineering of the human brain; advancing personalized learning; securing cyberspace; enhancing virtual reality; advancing health informatics; and engineering the tools of scientific discovery.1 One important aspect of the computational thinking–engineering connection is managing complexity.
From page 36...
... On a small scale, the task of cross-matching multiple donors and patients is a relatively simple computational thinking exercise. At the large scale at which the medical profession would need to perform these matches to improve donation matching across the nation, this type of matching poses a sig nificant intellectual challenge for computational thinking practitioners.
From page 37...
... • Music. Peter Lee described a summer program where young students attempt to write computer programs that allow computers to compose original music.
From page 38...
... "Legal problem solving is highly context-dependent in ways that may not be anticipated. As a law professor, I have to be very cautious about recommending computational thinking to law students, because it might lead them to focus more on a mechanical application of a predefined method rather than on the context and the opportunities in the actual problem to be solved.
From page 39...
... Since simulated annealing is analogous to asexual reproduction and genetic algorithms to sexual reproduction, this approach suggests that rather than maximization of fitness, sexual reproduction favors adequacy, or more specifically the ability of a genetic variant to function adequately in the presence of a wide variety of genetic partners. -- In economics and social science, the Internet -- an IT artifact constructed but never designed -- must be studied using the methods of natural science (e.g., observation and experimentation)
From page 40...
... Indeed, those other disciplines provide a context for computational thinking that often leads to new discoveries in computer science and information science themselves. 3.3 COMPUTATIONAL THINKING ACROSS DIFFERENT DISCIPLINES The subsections below are organized around different elements of computational thinking that have widespread application in multiple disciplines.
From page 41...
... In both cases, Wolz suggested that their successes in understanding concurrency and parallelism were due not so much to the Scratch graphical environment as to the metaphors that help convey understanding of the underlying concept. Mitchel Resnick described a simple programming exercise in which the user choreographs a dance for an animated cat.
From page 42...
... I just have another stack that says I want to forever change the color. So it takes some of the computational ideas of sequencing, and parallelism, and tries to make it very easy to put together and explore these ideas." 3.3.5 Modeling To illustrate computational thinking, Mitchel Resnick used a personal example based on his standing Monday tennis match.
From page 43...
... (Bottom) Image of a computational model of the force of impact on an aircraft; image courtesy of Christopher Hoffmann, Purdue University.
From page 44...
... about computational thinking for everyone and kind of as a goal for citizenship [in] that citizens need to also understand how decisions are being made and what some of the pitfalls in the models will be." Wilensky added that computational thinking involves more than using models, experimenting with models, or even constructing them; it also involves creating a culture of model critique.


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