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Commit 6e3977f2 authored by Benhui Wang's avatar Benhui Wang
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<title>Computational Thinking</title>
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<h1><a href="homepage.html">Computational Thinking</a></h1>
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<li><a class="main" href="#Guide">Guide</a></li>
<li><a href="AlanTuring.html">Turing</a></li>
<li><a href="Reflection.html">Reflection</a></li>
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<h1>
<span class="mainfont">Hello Computing World</span>
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“A man provided with paper, pencil, and rubber, and subject to
strict discipline, is in effect a universal Turing Machine.”
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;——Alan Turing
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<h2><span class="mainfont">What should I do?</span></h2>
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With the rapid development of artificial intelligence and
computer-related technology in recent years, more and more jobs are
being replaced by computers and machines, I gradually realized that I
would be out of touch with the times if I did not learn some computer
skills
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<a class="button" href="Reflection.html">Find more</a>
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<h1><span class="mainfont">What is Computational Thinking?</span></h1>
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From my point of view, computational thinking is a logic of
algorithms. It's like opening the fridge, shoving the elephant in
the fridge and closing the door. It is sequential and the sequence
of actions combine to accomplish an overall goal - stuffing the
elephant into the fridge. Although this is a seemingly impossible
task, when we break the problem down into smaller modules, our
thinking becomes clearer and it is easier to find a solution to the
problem.
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Any complex problem is translated by the computer into code 0 and
code 1 to calculate the problem. Computational thinking does not
require humans to process problems in the same way that computers
do, and the human brain cannot do that either. But the logic with
which computers approach problems is worthy of deeper consideration.
Transforming complex problems into problems of 0s and 1s is a
process of simplifying. This leads me to think that computational
thinking is about reinterpreting a seemingly difficult problem into
one that we know how to solve, by means of simplification,
embedding, transformation and simulation.
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<p>
Computational thinking has actually permeated every aspect of our
lives for a long time, but I hadn't thought about it systematically
until then. For example, choosing which queue to queue up in when
going to the supermarket checkout is a performance model for
multi-server systems. Losing something on the road and going back
one step at a time to find it is pushback. Why does the phone work
when the power goes out? It's about error irrelevance. If we can
summarise these patterns of thinking and optimise them, we can be
more effective in both learning and work
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<p>
However we need to understand that computational thinking is
fundamental, not a stereotypical skill. We need to integrate this
way of thinking organically into our learning and our lives. If we
treat it as a skill and repeat it in a stereotypical way, our
thinking becomes truly mechanical. Computational thinking is a way
for humans to solve problems, but it is not meant to make them think
like computers.We need to remember that it is humans who bring
computers to life.
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<h4>Thanks to below</h4>
<h5>Photo by @h heyerlein on Unsplash</h5>
<h5>Photo by @MARIOLA GROBELSKA</h5>
<h5>Photo by @Pietro Jeng</h5>
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<p>Copyright &copy; 2022 Benhui Wang</p>
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