Students who demonstrate understanding can: Analyze data from tests to determine similarities and differences among several design solutions to identify the best characteristics of each that can be combined into a new solution to better meet the criteria for success.
Official wording from the Next Generation Science Standards (NGSS Lead States, 2013). NGSS is a registered trademark of WestEd. Neither WestEd nor the lead states and partners that developed the NGSS were involved in the production of this page, and they do not endorse it. View on nextgenscience.org
Three teams build three different paper towers, and each one is best at something different: one is tallest, one survives a fan, one uses the least paper. Rather than simply picking a winner, students analyze test data to see which characteristics made each design succeed or fail, and then combine the strongest features into a new design that better meets the criteria.
Good analysis starts with fair tests, where the same conditions and measurements are used for every design. Students organize results in tables or graphs, compare them against the criteria, and look for causes: did the wide base explain stability, or the triangle bracing? Repeated trials help separate real differences from chance. The goal is not to prove one design is perfect, but to learn which features deliver which benefits.
This is how real products improve from one version to the next: engineers test, compare, and blend the most effective ideas.
A design might win on one criterion but fail another. Every criterion must be considered together.
Results vary from trial to trial. Averaging several trials gives a more reliable picture of how a design performs.
A design that fails overall can still contain a feature that works well and is worth combining into the next version.
If the test conditions differ, such as a stronger fan for one tower, the comparison is not fair.
Three model cars are tested on the same ramp, 3 trials each. Car A (large wheels): 210, 190, 200 cm. Car B (light frame): 160, 170, 150 cm. Car C (narrow body): 180, 175, 185 cm. Which features should be combined?
Answer: Car A averaged 200 cm, Car C 180 cm and Car B 160 cm; combining A's large wheels with C's narrow body is a promising new design to test.
Run a short design challenge where teams must share results on a class data table. Ask each team to name one feature from another team's design they would borrow and why. Graphing means with the range of trials makes both performance and consistency visible.
Assessment items often give a table of test results for several designs and ask which features to combine, with justification from the data.
Original questions written for this standard. Choose an option or type your answer, then press Check. Every question has a worked explanation.
Answer: C) To make the test fair so results can be compared
Keeping conditions the same means differences in results come from the designs, not the test.
Answer: 5 (also accepted: 5 kg)
(4 + 6 + 5) ÷ 3 = 15 ÷ 3 = 5 kg.
Answer: A) Look for features that give strength without much weight and combine them
Analyzing what makes each design succeed lets you combine strengths into a better solution.
Answer: D) Results vary, so averages are more reliable
Repeated trials reduce the effect of random variation.
Answer: iteration (also accepted: iterate, redesign, optimization, improving)
Engineers iterate, using test data to make improved versions.
Answer: B) A wide base improves stability
The data link the wide base to surviving the wind, so it is a feature worth keeping.
Evaluate a solution to a complex real-world problem based on prioritized criteria and trade-offs that account for a range of constraints, including cost, safety, reliability, and aesthetics as well as possible social, cultural, and environmental impacts.
A full lesson with slides, activities and an exit ticket on comparing design test results, pitched to grades 6-8 and editable in PowerPoint or Google Slides.
Make a lesson →A printable, differentiated worksheet on MS-ETS1-3 with an answer key, ready in about a minute.
Make a worksheet →Turn comparing design test results into a quiz students answer online that marks itself, with a class summary for you.
Build a test →To analyze data from tests of several designs and identify the best characteristics of each so they can be combined into a better solution.
Any measured results against the criteria, such as distances, loads held, times or temperatures, organized in tables or graphs.