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UNIT 4 Programming Assignment 1
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Level 3 national extended diploma in information technology : UNIT 4 programming
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ASSIGNMENT 1 – M1 AND D1Assess Computational thinking: (M1)
Advantages:
The most well-known and important benefit of computational
thinking is that it improves problem-solving abilities.
Computational thinking, which employs logic, reaves new
information/data from existing data, resulting in real-world
judgments rather than assumptions.
Computational thinking allows users to break down complex
problems into more easy-to-understand sections. Providing a
reliable solution to adapt and cope with different events.
Another major benefit of computational thinking is its
efficiency, which reduces the number of resources needed for
problem-solving. Resource minimization is essential in
computer science and algorithm design for appropriately
solving problems.
Disadvantages:
Although computational thinking brings up a path of problem-
solving possibilities for anyone who utilize it, the predictability
of computational thinking can be challenging sometimes.
It can be difficult to precisely predict markets, patterns, users,
and all technological influences using the computational
thinking approach. As a result, there are far too many factors
that can complicate any scenario in which can make the
accurate analysis impossible to obtain.
Computational thinking is the process of taking a complex
problem and cutting it down into small manageable problems in
which this could be quite difficult for users as they will need to
spent large amounts of time to get better at it.
, Evaluate computational thinking: (D1)
Decomposition does exactly what it's supposed to do as it helps
users to never get caught on a problem. If they do, all they
have to do is break that really difficult problem down into
smaller, more manageable difficulties. This is very useful
because if the user is focused on the main task, the main task
may ask for something very large, and the user will keep trying
to understand but will not be able to because large tasks
require the user to do small tasks first to add up to the big task.
This is where decompression comes in, as the user breaks
down that difficult large task into smaller tasks that turn out to
be rather simple little tasks. For user which user is able to
quickly do because they are really simple and small tasks,
whereas if user wanted to do the big task first, they would not
be able to because the big task is too difficult to do for user
after user does each of these small tasks, they will eventually
solve the complex problem with little hard work as a post to
users who just dive right into the big task and is struggling,
therefore this show how useful decomposition is.
Pattern recognition does a fantastic job at what it's supposed to
do as it helps users to recognise patterns so they can grasp
what they're looking at and get a rough indication of what
they're looking at. This is beneficial since it saves the user time
and allows them to finish work more quickly. With pattern
recognition, the user may solve a difficult problem using the
patterns supplied, making tasks more manageable and easier
to complete.
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