Patterns exist both in the natural world and in human-designed systems. Scientists observe these patterns and use them to describe various phenomena. Additionally, patterns serve as evidence to support scientific explanations.

Through our research presentations, we can delve deeper into patterns by exploring their similarities and differences. We will study how scientists use patterns for sorting, classifying, communicating, and analyzing simple rates of change in both natural phenomena and human-designed products. Furthermore, scientists discover that patterns of change enable them to make predictions about future outcomes. As they continue their scientific inquiries, they recognize that patterns serve as crucial evidence to support their explanations of various phenomena.

Scientists build on the foundations created by other scientists before them and apply the concept of patterns in new ways. They explore the interconnectedness between macroscopic patterns and the underlying microscopic and atomic-level structures. Also, they learn that patterns in rates of change and numerical relationships offer valuable insights into both natural phenomena and human-designed systems. By recognizing patterns, scientists can identify cause-and-effect relationships, crucial for understanding the world around us. They utilize graphs, charts, and images as tools to identify patterns in data, facilitating their analysis and interpretation of complex information.

By studying and observing patterns, scientists grasp that various scales of observation unveil different patterns within systems, offering evidence for causality in explaining phenomena. They understand that classifications or explanations might falter when information from different scales is introduced, prompting the need for enhanced investigations and experiments.

Furthermore, scientists analyze and interpret patterns of performance in designed systems, utilizing them to refine and enhance the functionality of these systems. Mathematical representations serve as essential tools for identifying certain patterns, while empirical evidence remains crucial in the process of pattern recognition.

Real-World Examples of Patterns in Science

It isn’t difficult to recognize patterns in the world around us. But sometimes, having explicit examples from different disciplines helps to makes connections to the Crosscutting Concept more clear. So, here are some examples of connections for you to explore as a starting point for your projects.

Patterns in Life Science

Biology: Let’s take a look at MS-LS4-3. In this performance expectation, students are asked to analyze pictorial data to compare patterns of similarities in the embryological development across species. This allows students to identify relationships between species that aren’t as obvious in full-grown organisms.

As we observe patterns in this drawing by Ernst Haekel (1892), notice that the embryos are most similar in the earliest stages of development.  You might also notice that the mammals look very similar throughout their development.  We can use these observations to ask questions.  For example, “Why do the tortoise and the chick look so similar?”

Physical Science Examples of Patterns in Science

Chemistry: The periodic table exhibits patterns in the properties of elements based on their atomic structure, such as atomic number, electron configuration, and chemical reactivity.

Physics: Waves exhibit various patterns, such as interference, diffraction, and standing waves, which help physicists understand the behavior of light, sound, and other wave phenomena.

Patterns in Earth and Space Science

Astronomy: Patterns such as the apparent motion of stars across the sky due to Earth’s rotation and the predictable orbits of planets around the Sun provide a basis for understanding celestial mechanics.

Plate Tectonics: The movement of Earth’s lithospheric plates follows recognizable patterns, leading to phenomena such as earthquakes, volcanic eruptions, and the formation of mountain ranges.

Patterns in Science & the Connection to Other CCCCs & SEPs

I love using in my classroom for many reasons.  The concept of patterns is familiar to us, and, it connects to almost every other concept in some way. This CCC, the Crosscutting Concept of Patterns, overlaps with other science and engineering practices. Let’s take a closer look at the connections.

Connections to Other CCCs

• Cause and Effect

• Scale, Proportion and Quantity

• Stability and Change

Connections to Science and Engineering Practices

• Asking Questions

• Math and Computational Thinking

• Analyzing and Interpreting Data

• Constructing Explanations