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1. PATTERN
RECOGNITION,
GENERALISATION &
ABSTRACTION

2. Pattern Recognition
Patterns exist everywhere & recognising patterns is a key aspect of computational thinking.
The process of recognising patterns in computing has five steps.
Identify common elements in
problems
Identify & interpret common
differences in problems
Identify individual elements
within problems
Describe patterns that have
been identified
Make predictions based on
identified patterns
This pattern holds true for each day of the week for most students in most schools and colleges.
If you were to look at how your day is organised in your School or College:
Your day will start at a set time.
It will be broken up into a no. of lessons of a set
length.
Each lesson will have a teacher who takes a register.

3. Patten Abstraction
Abstraction means hiding the complexity of something away from the thing that is going to be
using it.
There are two parts to this:
Identify the information required to solve a
problem
Filter out information you do not need.
In computational thinking, abstraction is a technique where we split individual
parts of the program down into imaginary ‘black boxes’ that carry out operations.

4. Pattern Generalisation
Generalisation happens when you can spot common themes between patterns.
Both of these involve some form of searching, the only thing that differs is
what you are searching for.
If we had a student search pattern in a school MIS, we might want to search for:
Students in a class. Students taught by a specific teacher.

5. Representing Parts of a Problem
We want to represent parts of a problem or system in general terms.
Variables - values that
will change.
Constants - something
that is likely to remain
fixed for a while.
Key Processes - things
that are critical to the
system.
Repeated Processes -
things that happen
multiple times.
Inputs - values entered
into the system.
Outputs - information
produced by the
system.