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Unit 4 Programming assignment 1 distinction example
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A detailed example of assignment 1 distinction for BTEC level 3 ICT unit 4
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nameComputational thinking skills
Computational thinking skills are using methods that a computer would use to solve complex
problems. Which is basically breaking down a problem to smaller problems and making it more
manageable to be able to apply logical solutions.
Decomposition
Decomposition means breaking down a complex problem into smaller tasks in order to make the
whole problem more approachable.
To use decomposition first you have to identify and describe the problem and processes that you’re
trying to solve. Then you can start breaking down the problem into smaller more manageable tasks,
which allows you to describe them even in greater detail and create a set of structured steps based
on the priority.
Reasons why you should use decomposition:
- Makes it easier to focus on one thing rather than focusing on the whole problem and not
knowing where to start.
- By breaking down problems it allows you to examine everything in greater detail.
- The smaller the tasks are the easier it is to understand and solve them.
- It also makes the problems more manageable and it allows you to set priorities for tasks.
- We use decomposition in everyday tasks and we don’t even realise it. E.g. Going to any set
destination of yours, we use some sort of method to get there. We don’t go straight path to
our destination (Unless you live very close to it then the problem is too small to break it
down even more). We break it down to smaller sets and methods that would help us to get
to our destination in less time and effort.
Comparing to just simply trying solve the problem without breaking it down to decomposition. It is
far more difficult if the problem is not broken into smaller tasks, because it might be too big and
overwhelming to people to tackle such error straight away. Also people who don’t use
decomposition are more prone to mistakes. Since without breaking down the task into smaller tasks
they tend to miss some details.
I think decomposition is necessary for every big task or problem you are doing. This method is really
simple and efficient. It can reduce a lot of stress and wasted time on tasks. A lot of people tend to
ignore this method or just don’t know about it which is really bad and they are just making
themselves the task harder. By breaking down the task into smaller tasks and slowly solving them it
gives a feeling of actual progress and makes you want to keep going. This type of effect it does to the
person who uses decomposition is really beneficial, because it makes them feel less stuck and
wanting to quit the task.
Pattern recognition
After we decomposed the problem we need to look at the smaller problems in order to find any
similarities or patterns.
Patterns are similar characteristics that could be found anywhere (E.g. all trees have leaf’s, all dogs
have tails, noses, eyes and fur.). Simply by knowing these types of characteristics we can try to
replicate them by any way. The only things that could be different are the specifics that are unique
for each object such as: Some trees might be bigger than others, some might have more branches,
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some dogs are bigger and some are smaller etc. These types of small specifics aren’t used in
computational thinking unless they have a pattern. The reason why they aren’t used is because the
whole point of pattern recognition, is to make everything more simple and straight forward.
Reasons why you should look for patterns:
- Problems are easier to solve if they share the same characteristics which allows you to apply
them to other problems.
- By finding more patterns we make the whole task overall much easier to solve.
- If we try to reproduce an object or describe it, we can find its main characteristics(pattern)
to make the whole task easier.
- We know each object has a pattern so we don’t have to create unique objects every single
time.
- When designing new object, you can use an existing pattern of similar object.
Comparing pattern recognition to just making unique patterns every single time to meet some
similarities. Pattern recognition is a lot easier and widely used than any other method. It’s most
commonly used in factories, where machines produce objects that fits the same pattern. If factories
wouldn’t use pattern to produce products, they would make more products with defects. Also
without pattern recognition you could not use machines to manufacture anything, because it’s
impossible for them to produce something that is completely unique each time. They have to follow
specific pattern. If factories wouldn’t use machines it would massively reduce the production rate,
that is why pattern recognition is important.
I believe pattern recognition is a good method for looking into similarities of objects or tasks and
applying previous methods to creating the same object or solution depending on the task you do. By
recognizing patterns anywhere in life, you become more familiar with things and less lost by
unnecessary factors. It helps to solving some problems instantly and applying solutions from
previous patterns. Even babies use pattern recognition without knowing it. They copy patterns
through perceiving how their parents talk, walk, act etc. And they slowly learn those patterns and
apply them.
Generalisation and abstraction
After finding a pattern it is necessary to only have in the pattern what is the most important. You can
do that by applying generalisation and abstraction.
Generalisation is following the pattern and ignoring confusing details.
Abstraction is filtering out unnecessary characteristics in order to concentrate on more important
ones.
Generalisation and abstraction are usually used together since they have some similarities in their
purpose. The main idea of generalisation and abstraction is to simplify complex processes by
ignoring confusing details and filtering out unnecessary characteristics. For example, humans have
main characteristics such as: we walk on two legs, have 2 arms 1 head, a torso etc. These
characteristics are really basic and not as detailed, but it is still enough to understand that it’s
probably a human and all other information that comes after its unnecessary detail that can be
filtered out.
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