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Seen this before?
Seen this before?
Patterns help us make sense of the world around us. We notice when things repeat, when things are similar and when something doesn't quite fit.
Pattern recognition is the process of identifying similarities, differences and repeated features in information or problems.
Recognising these patterns can help us make predictions and use what we already know to solve new problems.
Your brain loves a shortcut. This is one of the useful ones.
We do this all the time.
We do this all the time.
What comes next?
What comes next?
BLUE → GREEN → BLUE → GREEN → BLUE → ?
Most people quickly predict GREEN.
Why?
You recognised something that was repeating.
Pattern recognition isn't only about finding what comes next. It is also about noticing similarities between different situations or problems.
So, what does this have to do with coding?
So, what does this have to do with coding?
Quite a lot.
Imagine a character needs to move through a grid:
Rather than treating every movement as completely new, we can recognise that:
keeps repeating.
Recognising repetition can make problems easier to understand and solutions more efficient. Later, when we explore loops, we'll see how coding can make use of repeating patterns.
Spotted the repetition? Keep that thought. We'll need it later.
And in the early years?
And in the early years?
Young children already encounter patterns throughout their day.
Music
Clap → clap → stomp → repeat
Children listen for repeating sounds and rhythms.
Movement
Jump → turn → jump → turn
Children recognise and continue movement patterns.
Stories
Repeated characters, phrases or events help children anticipate what might happen next.
Daily routines
Children notice that familiar activities often contain similar actions and structures.
Pattern recognition helps children move beyond simply noticing repetition. It encourages them to compare, predict and use previous experiences to understand new situations.
Imagine that we want to draw a whole group of dachshunds.
Imagine that we want to draw a whole group of dachshunds.
Strictly for computational thinking purposes, obviously.
Dachshunds share some very recognisable characteristics. They have long bodies, short legs, floppy ears and long snouts. And, of course, many seem to be completely unaware of how small they actually are.
Because we recognise these common features, we can make a pretty good attempt at drawing a dachshund simply by following the pattern we already know.
In computational thinking, pattern recognition helps us identify these similarities. Once we know the general pattern of a dachshund, we can use it again and again. What changes are the details.
For example:
One dachshund might have black and tan fur, brown eyes and very floppy ears.
Another might have chocolate fur, greenish-brown eyes and slightly shorter ears.
Another might be dappled, long-haired and considerably more convinced that it owns the house.
Despite these differences, we still recognise all three as dachshunds because they share important characteristics.
Why does this matter?
Why does this matter?
If we want to draw ten dachshunds, we don't need to work out what makes a dachshund a dachshund every single time. We recognise the pattern and reuse what we already know, changing only the details.
That's the power of pattern recognition: when we recognise similarities, we can use what we've learned before to approach new problems more quickly and efficiently.
Long body + short legs + floppy ears = suspiciously familiar pattern.
I'm beginning to see a pattern here.
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