Unit Plan 35 (Grade 7 Science): Evolution Engineering Challenge

Focus: Use the engineering design process to model or design adaptations that help organisms or systems solve real environmental challenges, and use mathematical representations to compare how well different designs support survival or performance.

Grade Level: 7

Subject Area: Science (Life Science — Evolution Applications • Engineering Design)

Total Unit Duration: 5 sessions (one week), 50–60 minutes per session

I. Introduction

In this unit, students act as “evolution engineers,” designing structures, behaviors, or systems that function like adaptations to help organisms survive in specific environments. Given a real or realistic environmental challenge (e.g., heat waves, flooding, predators, urban hazards), teams define a design problem with clear criteria and constraints, brainstorm multiple solutions, and construct simple models or prototypes. They then test and collect data on how well their designs perform, use math to compare designs (e.g., success rates, distances, times), and iterate to improve. Throughout, they connect their designs to ideas about trait variation, selection, and survival probabilities, integrating MS-ETS1-1–4 and MS-LS4-6.

Essential Questions

• How can we design structures or behaviors that function like adaptations to solve environmental challenges?
• What does it mean to define a good design problem with clear criteria and constraints?
• How can data and math (fractions, percentages, graphs) help us decide which designs best support survival in a given environment?
• How is the engineering design process similar to how evolution changes populations over time?

II. Objectives and Standards

Learning Objectives — Students will be able to:

1. Analyze an environmental scenario and define a design problem with clear criteria (what the solution must do) and constraints (limits like materials, time, or size).
2. Brainstorm, sketch, and describe multiple design ideas that model possible adaptations to the challenge.
3. Build a model or prototype that represents a trait or adaptation and test it under conditions that mimic the environmental challenge.
4. Collect and organize quantitative data from tests (e.g., number of successful trials, distance traveled, time to complete a task) and compute fractions, ratios, or percentages to represent performance.
5. Use graphs and numerical comparisons to evaluate and improve designs, explaining how design “traits” change the chance of success in the modeled environment, aligned with MS-LS4-6.
6. Communicate a final Evolution Engineering Design Brief that explains the problem, solution, test data, and how the design models an adaptation.

Standards Alignment — 7th Grade (NGSS-based custom)

• MS-ETS1-1 — Define design problems with criteria and constraints that reflect a need or want.
  • Example: Identify criteria (stay upright, protect from heat) and constraints (limited materials, size) for an organism shelter model.
• MS-ETS1-2 — Evaluate competing design solutions using a systematic process.
  • Example: Compare two wing-shape models using the same test and choose one based on data.
• MS-ETS1-3 — Analyze data from tests to determine similarities and differences among designs.
  • Example: Use success rates to decide which “beak design” picks up the most food items.
• MS-ETS1-4 — Develop a model and use testing data for iterative improvements to a proposed object or tool.
  • Example: Modify a prototype after test data shows weaknesses.
• MS-LS4-6 — Use mathematical representations to support explanations of how trait variations affect population survival.
  • Example: Represent design performance as a survival percentage and relate it to adaptation.

Success Criteria — Student Language

• I can clearly state the problem, including what my design must do (criteria) and what limits I have (constraints).
• I can sketch and describe at least two design ideas that act like adaptations to an environmental challenge.
• I can build and test a model or prototype, then record data from each trial.
• I can use fractions, ratios, or percentages and graphs to compare how well different designs work.
• I can explain how my design’s “traits” change the chance of success or survival in the modeled environment.