Learn on PengiAmplify Science (California) Grade 7Chapter 2: Using Models as Evidence

Lesson 3: Evaluating Models

Key Idea.

Section 1

Simplicity vs. Complexity

Key Idea

A model is useful precisely because it is simple, but this simplicity creates a gap between the model and the real world. A stream table has water and sand, but it lacks the wind, vegetation, and temperature changes found in nature.

Scientists must identify these differences to understand what the model is missing. Acknowledging that a model is an approximation helps scientists avoid making overconfident claims. It reminds them that the model shows only part of the picture, not the entire complex system.

Section 2

Defining Limitations

Key Idea

Every model has limitations, which are the specific boundaries of what it can and cannot show. For instance, a small stream table cannot show the effects of a process that takes a million years.

Identifying limitations is a critical skill in evaluating evidence. When scientists present their findings, they must be transparent about these constraints. This ensures that the evidence derived from the model is applied correctly and not stretched to explain things outside its scope.

Lesson overview

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Section 1

Simplicity vs. Complexity

Key Idea

A model is useful precisely because it is simple, but this simplicity creates a gap between the model and the real world. A stream table has water and sand, but it lacks the wind, vegetation, and temperature changes found in nature.

Scientists must identify these differences to understand what the model is missing. Acknowledging that a model is an approximation helps scientists avoid making overconfident claims. It reminds them that the model shows only part of the picture, not the entire complex system.

Section 2

Defining Limitations

Key Idea

Every model has limitations, which are the specific boundaries of what it can and cannot show. For instance, a small stream table cannot show the effects of a process that takes a million years.

Identifying limitations is a critical skill in evaluating evidence. When scientists present their findings, they must be transparent about these constraints. This ensures that the evidence derived from the model is applied correctly and not stretched to explain things outside its scope.