Understanding Patterns Across Natural & Engineered Systems

Instructor: Nicholas Amendolare

Nicholas Amendolare is a high school and middle school science teacher from Plymouth, Massachusetts. He has a bachelor's degree in environmental science from Worcester Polytechnic Institute and a master's degree in education from Harvard University. He has been a teacher for nine years, has written for TED-Ed, and is the founder of www.MrAscience.com.

This article describes how patterns are identified in nature as well as what defines a pattern and how patterns are different from randomness. It then goes on to discuss how pattern-recognition is used in both science and engineering. Updated: 06/17/2022

What is a Pattern?

The word pattern has several definitions. Most generally, a pattern is defined as any regularly repeated arrangement. But visually, it refers to a design made from repeating shapes, lines, and colors on a surface. In sewing, the word pattern dates back centuries, referring to a form or model used for imitation. And indeed, this seems to hint at the word's origin. The word comes from the Latin prefix 'patr,' which means father, and the Middle English word 'patron.' In sewing and dressmaking, the original pattern fathers many copies.

In the modern-day, we look for pattern everywhere. Patterns of genes can explain many diseases. Patterns in the stock market, if predicted, can lead to windfalls for investors. And patterns in weather can explain yesterday's heat wave and tomorrow's thundershowers. In science and mathematics, patterns are the opposite of randomness. And proving that observations are due to patterns, due to some sort of cause and effect rather than random chance, is a major part of practicing science in the 21st century.

Patterns in Nature

If you've ever caught a snowflake in your hand, you've probably noticed that it isn't just a random collection of globs of ice. Snowflakes form in particular shapes depending upon the temperature and humidity they experience while they are growing. And although no two snowflakes are perfectly symmetrical, many have six distinct arms, a quality that arises due to the hexagonal crystalline structure of ice.

Many other patterns exist in nature too. Think of the five-fold symmetry in starfish and the spiraling shape of many seashells. Think of the arrangement of petals around a sunflower. Think of the small ripples left behind on a beach at low tide and the massive dunes, sometimes hundreds of feet high, that form in desert sands. All of these phenomena are far from random. In nature, patterns are everywhere.

Patterns in Mathematics

Mathematics has been called 'the science of pattern.' For example, think of the output of any mathematical function: it is predictable and perfectly repeatable and completely non-random. We often even graph these patterns on coordinate planes so that we can see them displayed visually.

Dragon curves are an example of a repeating mathematical pattern known as a fractal.

Fractals are another example. A fractal is defined as a curve or geometric shape in which each has the same character as the whole. But fractals are not only found in the visual realm; they can also be used to describe processes in time. And fractal patterns have been observed and studied in physics, in sound, in architecture, law, and even in nature.

Patterns That Aren't Patterns

Human beings are particularly adept at recognizing patterns. Perhaps too adept. We use both pattern recognition and inductive thinking to, first, find patterns and, second, to use these patterns to predict what might happen next. One can imagine how this is an important evolutionary ability. Seeing patterns could mean following a stream to find fresh water, predicting where the next patch of berries might grow, or knowing to take shelter during a thunderstorm.

However, the human ability to recognize patterns can also lead us astray. Take, for example, confirmation bias, which psychologists define as the tendency to search for evidence that confirms a person's prior assumptions. This leads humans to reach all sorts of incorrect conclusions. One famous example is the apparent connection between a president's performance and gasoline prices. In reality, a president has very little control over the price of fuel. In fact, every United States president since the year 2000 had left office with gas prices higher than when they started. But confirmation bias, particularly in the spring following a new president's inauguration, leads many to blame the seasonal increase in spring and summer fuel prices on politics, mainly when the person in the office is someone they voted against.

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