Using models in science
In this topic you will
In this lesson, you will learn why scientists use models to study the natural world. You’ll explore different types of models, including physical, diagrammatic, simulation, and mathematical forms. You’ll also find out how scientists test and improve these models and how to judge their strengths and weaknesses.
Keywords
- Model
- Representation
- Physical Model
- Diagram
- Simulation
- Mathematical Model
- Assumption
- Accuracy
- Limitation
- Analogy
Why Do Scientists Use Models?
Scientists often study things that cannot be directly observed or touched. Some systems are too small, like atoms and molecules. Others are too large, such as planets or ecosystems. Some are too dangerous to experiment with directly, like radioactive materials, or too abstract, like gravitational fields. In these cases, scientists use models — simplified versions of reality — to explore how things work. A model helps scientists explain, predict, and communicate complex processes or systems in a more understandable way.
Quick Fact
The famous double helix model of DNA, proposed by Watson and Crick in 1953, changed the course of biology. They built it using cardboard cutouts, sticks, and wire — showing that even the simplest materials can build revolutionary models.
What Makes a Good Model?
A useful scientific model focuses on the key features of a system and is grounded in real data and observations. It must be simple enough to use but detailed enough to reflect the core behavior of what it represents. A good model allows scientists to make predictions, test ideas, and explain real-world phenomena clearly. However, no model is perfect. Every model includes limitations, such as simplifications, missing details, or incorrect assumptions. That’s why models are often revised or replaced over time.
Example
The particle model of matter shows solids, liquids, and gases as collections of perfect spheres. This helps us explain changes of state and particle motion. But in reality, particles interact through forces, they aren't perfectly spherical, and they follow the laws of quantum mechanics — all things the model doesn't show.
Physical Models
Physical models are three-dimensional objects that can be touched, rotated, and explored. These models are especially helpful for visualizing the shape, scale, or structure of something. A globe can show the continents and oceans of the Earth. A plastic model of a human heart helps students learn anatomy. Molecular models made of sticks and balls help us understand how atoms connect and form shapes. While physical models are great for learning and demonstration, they usually can’t show how things behave dynamically or at microscopic scales.
Analogy
A model of a car engine can help a mechanic understand its structure and parts — but it doesn’t actually run or drive. The same idea applies to physical models in science: they show us how something is built, not how it works in every detail.
Diagrammatic Models
Diagrammatic models are two-dimensional visual representations, such as drawings, sketches, or simplified diagrams. These are used to highlight structure, sequence, or key relationships in a system. Common examples include food chains, electric circuit diagrams, and the Bohr model of the atom. Diagrams help reduce complexity by focusing on the most important features, making it easier to teach or explain a concept. However, they are not always realistic or complete, and students must be careful not to take them too literally.
Common Mistake
Some students believe the Bohr model is exactly how atoms look. In reality, electrons don’t follow perfect circular paths like planets. They exist in cloud-like regions with unpredictable motion.
Simulations
Simulations are dynamic, digital models that often change over time or respond to different inputs. They are especially useful when testing ideas in the real world would be too expensive, dangerous, or impractical. For example, scientists use climate models to predict future temperatures based on carbon dioxide levels. Earthquake simulations help architects test building designs for safety. These models rely on powerful computers and lots of data to make predictions. However, if the underlying assumptions are flawed or incomplete, simulations can be misleading.
Alert
Even simulations that look impressive can be wrong if they are based on incorrect assumptions or missing data. Always ask what a simulation includes — and what it leaves out.
Mathematical Models
Mathematical models use equations, graphs, and data to describe patterns in the world. These models are especially powerful when making predictions. For example, the equation speed = distance ÷ time helps us calculate how long a journey will take. In physics, force = mass × acceleration explains how objects move when pushed or pulled. Mathematical models are often developed by analyzing patterns in experimental data, and they become more accurate as more data is added. They are widely used in physics, biology, economics, and many other sciences.
How Do Models Help Science?
Models help scientists form hypotheses, test ideas, and communicate theories to others. They are used to explain observations, predict new outcomes, and even design experiments. But models must be constantly evaluated. When a model fails to explain new data or leads to incorrect predictions, it needs to be updated or replaced with a better one.
Quick Fact
For centuries, scientists believed in the geocentric model — with Earth at the center of the universe. Eventually, this model couldn’t explain planetary motion. It was replaced by the heliocentric model, which made better predictions and matched observations more accurately.
Think Like a Scientist
The Bohr model of the atom shows electrons moving in neat, circular orbits around a nucleus. It’s a simple model that helps explain atomic structure and energy levels — but it’s also outdated. Modern physics says electrons don’t orbit in circles. Instead, they exist in “clouds” of probability, with uncertain positions.
Still, the Bohr model is taught because it helps beginners understand basic ideas. But now it’s your turn to think like a scientist. Can you improve the model?
Your Task:
- Look at a Bohr model diagram.
- List what it explains well.
- List what it gets wrong or leaves out.
- Design a better model. How could you show uncertainty or cloud-like electrons?
Reflect and Discuss:
Show Answer
Because it's easy to draw and helps students understand energy levels, even though it doesn’t show the true behavior of electrons.
Show Answer
They may lead to misunderstandings or incorrect conclusions if students don’t realize the model is a simplification.
Show Answer
Yes — if it helps people understand a concept or predict behavior, it still has value, even if it isn’t fully accurate.