Elementary School Science Quiz: Collecting Design Test Results
20 questions · exam conditions
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Collecting Design Test ResultsQuestion 1 of 20

Keisha tested two designs to hold paintbrushes upright. Problem: store many brushes. Design A: cup with 6 holes. Design B: box with 12 clips. Test: she put 6 brushes in each. Data: A held all 6 steady; B held 6 but 2 tipped. Look at the test results. Which design worked better for keeping brushes steady?

Design B kept brushes more steady
Design A kept brushes more steady
Both designs tipped over all brushes
Design B is best because it has clips
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Elementary School Science Quiz

Elementary School Science Quiz: Collecting Design Test Results

Practice Collecting Design Test Results in Elementary School Science with focused quiz questions that help you check what you know, review explanations, and build confidence with test-style prompts.

What this quiz covers

This quiz focuses on Collecting Design Test Results, giving you a quick way to practice the rules, question types, and explanations that matter most for Elementary School Science.

How to use this quiz

Try each quiz question before looking at the correct answer. Use the explanations to review missed ideas, then come back to similar questions until the pattern feels familiar.

All questions

Question 1

Keisha tested two designs to hold paintbrushes upright. Problem: store many brushes. Design A: cup with 6 holes. Design B: box with 12 clips. Test: she put 6 brushes in each. Data: A held all 6 steady; B held 6 but 2 tipped. Look at the test results. Which design worked better for keeping brushes steady?

  1. Design B kept brushes more steady
  2. Design A kept brushes more steady (correct answer)
  3. Both designs tipped over all brushes
  4. Design B is best because it has clips
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of storing many paintbrushes upright. Design A was a cup with 6 holes and Design B was a box with 12 clips. Tests showed Design A held all 6 steady (strength in steadiness) while Design B held 6 but 2 tipped (weakness in steadiness). Choice B is correct because the test results showed that Design A kept all brushes steady without tipping, performing better than Design B which had two tipped brushes. Choice A represents a data reversal error, which happens when students switch the performance results between designs, claiming Design B was steadier when the data shows otherwise. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 2

Marcus tested two designs to water plants evenly. Problem: water 3 plants the same. Design A: bottle cap with 3 small holes. Design B: cap with 1 large hole. Test: he watered 3 plants with each. Data: A was gentle and even but slower; B was faster but sometimes too much. Look at the test results. Which design is better for even watering?

  1. Design B, because it is faster
  2. Design A, because it is more even (correct answer)
  3. Both designs watered no plants
  4. Design B, because it has three holes
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of watering 3 plants evenly. Design A was a bottle cap with 3 small holes and Design B was a cap with 1 large hole. Tests showed Design A was gentle and even but slower (strength in evenness), while Design B was faster but sometimes too much (weakness in evenness). Choice B is correct because the test results showed that Design A provided more even watering, as it was described as gentle and even compared to Design B's uneven distribution. Choice A represents a priority mismatch, which happens when students focus on a secondary aspect like speed instead of the main goal of even watering stated in the problem. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 3

Emma tested two designs to catch melting ice water. Design A was a shallow wide bowl. Design B was a tall narrow cup. She put one ice cube in each for 10 minutes. Look at the test results data.

Data:

  • What happened: A caught all water; B overflowed.
  • Space used: A used more space; B used less space.
  • Problems: A was big; B was too small.

Based on the test results, which design worked better for saving space?

  1. Design A saved more space than Design B
  2. Design B saved more space than Design A (correct answer)
  3. Both designs saved the same space
  4. Design A overflowed because it was too small
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of catching melting ice water. Design A was a shallow wide bowl and Design B was a tall narrow cup. Tests showed that Design A caught all the water but used more space, while Design B overflowed but used less space, highlighting strengths in capacity for A and space-saving for B. Choice B is correct because the test results showed that Design B used less space than Design A, directly answering which saved more space. Choice A represents a common error of reversing the designs, which happens when students mix up labels and ignore specific data points like 'A used more space; B used less space.' To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 4

Carlos tested two paintbrush holders for the same problem. Design A was a cup with 6 holes. Design B was a box with 12 clips. He put 6 brushes in each. Look at the test results data.

Data:

  • Steady: A steady; B less steady.
  • Capacity: A fits 6; B fits 12.
  • Observation: Two brushes in B tipped.

How are the two designs different based on the test results?

  1. Design A holds more brushes, but tips more
  2. Design B holds more brushes, but tips more (correct answer)
  3. Both hold 12 brushes and stay steady
  4. Design B holds fewer brushes and stays steadier
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of holding paintbrushes. Design A was a cup with 6 holes and Design B was a box with 12 clips. Tests showed that Design A was steady for 6 brushes, while Design B fit 12 but was less steady with some tipping. Choice B is correct because the data highlighted that Design B holds more brushes (12) but tips more, capturing the key differences in capacity and stability. Choice D represents a reversal error, which happens when students invert the data, claiming B holds fewer and is steadier when it's the opposite. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 5

Keisha tested two boot trays to dry wet boots. Design A had raised edges. Design B had holes over a pan. She tested both for 30 minutes. Look at the test results data.

Data:

  • Water location: A water stayed in tray; B water drained to pan.
  • Emptying: A needs dumping; B easier to empty.
  • Parts: B needs tray and pan.

What information did Keisha collect about the designs?

  1. Where the water went and how easy to empty (correct answer)
  2. Which tray was the prettiest color
  3. How fast the boots could run in them
  4. Which design worked best in winter snow
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of drying wet boots. Design A had raised edges and Design B had holes over a pan. Tests showed differences in water location, emptying ease, and parts needed, with B draining to a pan and being easier to empty but requiring two parts. Choice A is correct because it accurately describes the collected data on where water went and emptying ease, matching the test results. Choice B represents including irrelevant factors, which happens when students add personal preferences like color that aren't in the data, ignoring actual observations. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 6

Chen tested two boot-drying designs after recess. Design A was a boot tray with raised edges. Design B was a tray with holes over a pan. He put wet boots in each for 30 minutes. Look at the test results data.

Data:

  • Water: A collected water in tray; B drained water into pan.
  • Emptying: A needs emptying; B is easier to empty.
  • Parts: A is one piece; B needs two pieces.

What is a weakness of Design B based on the test results?

  1. It needs two pieces to work (correct answer)
  2. It keeps all water stuck in the tray
  3. It cannot hold wet boots for 30 minutes
  4. It is harder to empty than Design A
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of drying wet boots. Design A was a boot tray with raised edges and Design B was a tray with holes over a pan. Tests showed that Design A was one piece but needed emptying, while Design B was easier to empty but required two pieces. Choice A is correct because the test results indicated that Design B needs two pieces to work, which is a weakness compared to Design A's single piece. Choice D represents a reversal of results, which happens when students misread data and assign strengths or weaknesses to the wrong design, like claiming B is harder to empty when it's easier. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 7

Jamal tested two designs to keep sand from blowing out. Design A was a solid board fence. Design B was a slat fence with spaces. He used the same fan for 1 minute. Look at the test results data.

Data:

  • Sand blown out: A = none; B = some.
  • View: A blocked view; B allowed view.
  • Air: A blocked air; B let air through.

What do the results show about Design A and Design B?

  1. Design A blocked all sand, but blocked air and view (correct answer)
  2. Design B blocked all sand, but blocked air and view
  3. Both designs let the same sand blow out
  4. Design A let some sand out, but gave a good view
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of keeping sand from blowing out. Design A was a solid board fence and Design B was a slat fence with spaces. Tests showed that Design A blocked all sand but blocked air and view, while Design B let some sand out but allowed air and view. Choice A is correct because the test results showed that Design A blocked all sand (strength) but blocked air and view (weakness), accurately reflecting the data. Choice B represents a reversal error, which happens when students confuse which design corresponds to which results, such as assigning Design A's blocking to Design B. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 8

Sofia tested two designs to hold paintbrushes upright. Design A was a cup with 6 round holes. Design B was a box with 12 small clips. She put 6 brushes in each. Look at the test results data.

Data:

  • Brushes held: A held 6; B can hold 12.
  • Steady: A was steady; B was less steady.
  • Observation: Some in B tipped over.

According to the data, what is a strength of Design B?

  1. It holds brushes more steady than Design A
  2. It can hold more brushes than Design A (correct answer)
  3. It only fits six brushes in the holder
  4. It makes brushes tip over less than Design A
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of holding paintbrushes upright. Design A was a cup with 6 round holes and Design B was a box with 12 small clips. Tests showed that Design A held 6 brushes steadily, while Design B could hold 12 but was less steady with some tipping over. Choice B is correct because the data demonstrated that Design B can hold more brushes (12 vs. 6), which is a clear strength despite its weakness in steadiness. Choice A represents a misconception of ignoring trade-offs, which happens when students claim a design excels in an area where data shows the opposite, like steadiness for B. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 9

Yuki tested two fences to stop sand blowing out. Design A used solid boards. Design B used slats with spaces. She used the same fan for 1 minute. Look at the test results data.

Data:

  • Sand blown out: A = none; B = some.
  • View: A blocked view; B allowed view.
  • Air: A blocked air; B let air through.

Which design would work best if you want air and a clear view?

  1. Design A, because it blocks air and view
  2. Design B, because it allows air and view (correct answer)
  3. Design A, because it lets some sand blow out
  4. Both designs, because they block air and view
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of stopping sand from blowing out. Design A used solid boards and Design B used slats with spaces. Tests showed that Design A blocked all sand but blocked air and view, while Design B let some sand out but allowed air and view. Choice B is correct because the results showed Design B allows air and view, making it best for that priority despite letting some sand through. Choice A represents overlooking trade-offs, which happens when students prioritize blocking sand over the specified needs like air and view, ignoring B's strengths. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 10

Sofia tested two designs to catch water from melting ice. Problem: stop drips. Design A: shallow wide bowl. Design B: tall narrow cup. Test: one ice cube in each, wait 10 minutes. Data: A caught all water; B overflowed. Look at the test results. What is a weakness of Design B?

  1. It overflowed and spilled water (correct answer)
  2. It caught all the water
  3. It took up more space
  4. It melted the ice faster
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of stopping drips from melting ice. Design A was a shallow wide bowl and Design B was a tall narrow cup. Tests showed Design A caught all water (strength) while Design B overflowed (weakness). Choice A is correct because the test results showed that Design B overflowed and spilled water, identifying this as a clear weakness in its ability to catch all the water. Choice B represents an inversion misconception, which happens when students attribute a strength of one design to the other, such as saying Design B caught all the water when the data shows it did not. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 11

Jamal tested two designs to keep sand in a sandbox. Problem: sand blows away. Design A: solid board fence. Design B: slat fence with spaces. Test: he used the same fan for 1 minute. Data: A let 0 scoops out; B let 1 scoop out. Look at the test results. Which design worked better to block sand?

  1. Design B blocked all the sand
  2. Design A blocked sand better (correct answer)
  3. Both designs let out 3 scoops
  4. Design B is better because it looks nicer
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of sand blowing away from a sandbox. Design A was a solid board fence and Design B was a slat fence with spaces. Tests showed Design A let 0 scoops of sand out (strength in blocking) while Design B let 1 scoop out (weakness in blocking). Choice B is correct because the test results showed that Design A blocked sand better by letting zero scoops out compared to Design B's one scoop, directly comparing their performance in blocking sand. Choice A represents a reversal error, which happens when students mix up which design performed better, such as claiming Design B blocked all sand when the data shows it let some out. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 12

Amir tested two designs to dry wet boots. Problem: water drips on the floor. Design A: boot tray with raised edges. Design B: tray with holes over a pan. Test: same wet boots for 30 minutes. Data: A kept water in tray; B drained water into pan. Look at the test results. Which design is easier to empty?

  1. Design A is easier to empty
  2. Design B is easier to empty (correct answer)
  3. Both designs overflowed right away
  4. Design A is easier because it has holes
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of water dripping from wet boots onto the floor. Design A was a boot tray with raised edges and Design B was a tray with holes over a pan. Tests showed Design A kept water in the tray (simple but holds water) while Design B drained water into the pan (easier to empty but more complex). Choice B is correct because the test results showed that Design B drained water into a separate pan, making it easier to empty compared to pouring from Design A's contained tray. Choice D represents an attribution error, which happens when students assign features to the wrong design, such as saying Design A is easier because it has holes when actually Design B has the holes. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 13

Emma tested two designs to dry wet boots. Problem: keep floor dry. Design A: tray with raised edges. Design B: tray with holes over a pan. Test: same wet boots for 30 minutes. Data: A collected water in tray; B drained into pan but needs two pieces. Look at the test results. What is a weakness of Design B?

  1. It needs two pieces to use (correct answer)
  2. It cannot drain any water
  3. It collects water in one tray only
  4. It dries boots by heating them
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of keeping the floor dry from wet boots. Design A was a tray with raised edges and Design B was a tray with holes over a pan. Tests showed Design A collected water in one tray (simple) while Design B drained into a pan but required two pieces (weakness in complexity). Choice A is correct because the test results highlighted that Design B needs two pieces to use, identifying this as a weakness compared to Design A's single-piece simplicity. Choice B represents a factual inaccuracy, which happens when students claim something not supported by data, such as saying Design B cannot drain water when the results show it does drain into the pan. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 14

Maya tested two designs to carry library books. Problem: carry 5 books safely. Design A: bag with two handles. Design B: box with one side handle. Test: she carried 5 books across the room. Data: A felt even but books shifted; B kept books still but felt heavy on one side. Look at the test results. What did Maya learn?

  1. Design B spreads weight evenly and books shift
  2. Design A keeps books still and steady
  3. A is even, but B keeps books stable (correct answer)
  4. Both designs were perfect with no problems
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of carrying 5 library books safely. Design A was a bag with two handles and Design B was a box with one side handle. Tests showed Design A felt even but books shifted (strength in balance, weakness in stability), while Design B kept books still but felt heavy on one side (strength in stability, weakness in balance). Choice C is correct because the test results showed that Design A distributed weight evenly but Design B kept books more stable, accurately summarizing the trade-offs observed. Choice D represents an overgeneralization error, which happens when students ignore weaknesses and claim both designs were perfect, despite the data showing issues like shifting or uneven weight. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 15

Yuki tested two designs to catch melting ice water. Problem: keep water off the desk. Design A: shallow wide bowl. Design B: tall narrow cup. Test: one ice cube in each for 10 minutes. Data: A caught all water but took more space; B saved space but overflowed. Look at the test results. What do the results show?

  1. A caught water; B saved space but overflowed (correct answer)
  2. B caught all water and took more space
  3. A and B both overflowed the same amount
  4. A worked better because it is taller
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of keeping water from melting ice off the desk. Design A was a shallow wide bowl and Design B was a tall narrow cup. Tests showed Design A caught all water but took more space (strength in catching, weakness in space), while Design B saved space but overflowed (strength in space, weakness in catching). Choice A is correct because the test results showed that Design A caught all the water while Design B saved space but overflowed, accurately reflecting the strengths and weaknesses of each. Choice B represents a swapped results error, which happens when students reverse the outcomes between designs, such as claiming Design B caught all water and took more space when the data shows the opposite. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 16

Carlos tested two designs to keep sand from blowing out. Problem: stop sand from leaving. Design A: solid board fence. Design B: slat fence with spaces. Test: same fan for 1 minute. Data: A blocked sand but blocked view; B let some sand through but you could see. Look at the test results. Which design would work best if you want to see inside?

  1. Design A, because it blocks the view
  2. Design B, because you can see through (correct answer)
  3. Design A, because it lets sand through
  4. Both designs, because color helps seeing
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of stopping sand from blowing out of an area. Design A was a solid board fence and Design B was a slat fence with spaces. Tests showed Design A blocked sand but blocked the view (strength in blocking sand, weakness in visibility), while Design B let some sand through but allowed seeing (strength in visibility, weakness in blocking). Choice B is correct because the test results showed that Design B allowed visibility through it, making it better for seeing inside despite letting some sand out. Choice A represents an opposite outcome misconception, which happens when students select a design that directly contradicts the desired feature, like choosing the one that blocks the view when visibility is wanted. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 17

Amir tested two designs to carry 5 library books. Design A was a bag with two handles. Design B was a box with one side handle. He carried each across the same room. Look at the test results data.

Data:

  • Weight feel: A felt even; B felt heavy on one side.
  • Books: A books shifted; B books stayed stable.
  • Problem: B was harder to carry.

Which design would work best if you want books to stay stable?

  1. Design A, because it keeps books from shifting
  2. Design B, because it keeps books stable (correct answer)
  3. Design A, because it is heavy on one side
  4. Design B, because books shift around inside
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of carrying library books. Design A was a bag with two handles and Design B was a box with one side handle. Tests showed that Design A felt even but books shifted, while Design B kept books stable but felt heavy on one side. Choice B is correct because the data showed that Design B kept books stable, making it best for that specific need despite its carrying difficulty. Choice A represents ignoring trade-offs, which happens when students overlook weaknesses and claim a design excels where data shows it underperforms, like stability in A. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 18

Maya tested two watering bottle designs to water plants evenly. Design A had 3 small holes in the cap. Design B had 1 large hole in the cap. She watered 3 plants with each. Look at the test results data.

Data:

  • Speed: A took longer; B was faster.
  • Watering: A was gentle and even; B sometimes poured too much.
  • Observation: B made puddles on one plant.

Based on the test results, which design worked better for even watering?

  1. Design B, because it watered faster each time
  2. Design A, because it watered gently and evenly (correct answer)
  3. Both designs watered evenly every time
  4. Design A, because it sometimes poured too much
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of watering plants evenly. Design A had 3 small holes in the cap and Design B had 1 large hole. Tests showed that Design A was gentle and even but slower, while Design B was faster but sometimes poured too much, creating puddles. Choice B is correct because the test results showed that Design A watered gently and evenly, directly supporting it as better for even watering. Choice A represents prioritizing the wrong criterion, which happens when students focus on speed over the key goal of evenness, ignoring data on puddles in B. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 19

Marcus tested two designs to catch melting ice water. Design A was a shallow wide bowl. Design B was a tall narrow cup. He used one ice cube in each for 10 minutes. Look at the test results data.

Data:

  • Water caught: A = all; B = some spilled.
  • Space: A used more space; B used less space.
  • Observation: B overflowed near the end.

What did Marcus learn from testing the two designs?

  1. Design A caught more water, but used more space (correct answer)
  2. Design B caught more water, but used more space
  3. Both designs caught all water and used little space
  4. Design A overflowed, and Design B caught all water
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of catching melting ice water. Design A was a shallow wide bowl and Design B was a tall narrow cup. Tests showed that Design A caught all water but used more space, while Design B spilled some water but used less space, with B overflowing. Choice A is correct because the data demonstrated that Design A caught more water (all vs. some) but used more space, accurately capturing the trade-offs learned. Choice D represents reversing results, which happens when students mix up which design overflowed, claiming A did when data shows B did. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.

Question 20

Chen tested two designs to hold paintbrushes upright. Problem: brushes fall over. Design A: cup with 6 holes. Design B: box with 12 clips. Test: he put 6 brushes in each. Data: A had 0 tipped; B had 2 tipped. Look at the test results. What is a strength of Design A?

  1. It held brushes more steady (correct answer)
  2. It held 12 brushes at once
  3. It tipped over more than B
  4. It made the brushes dry faster
Explanation: This question tests 2nd grade ability to analyze test data from two designs solving the same problem (NGSS K-2-ETS1-3: Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs). In engineering, we test designs to see how well they work. When we have two different designs for the same problem, we test both under the same conditions and collect results—this is called data. Data can include observations (what we saw happen), measurements (numbers like how much, how long, how many), or ratings (worked well, okay, or not well). We analyze data by comparing results: What worked well? What didn't work as expected? Often, each design has strengths (things it does well) and weaknesses (things it doesn't do well or could do better). Understanding these trade-offs helps us choose the best design for a specific situation or improve designs by combining the best features. In this scenario, both designs tried to solve the problem of brushes falling over. Design A was a cup with 6 holes and Design B was a box with 12 clips. Tests showed Design A had 0 tipped brushes (strength in steadiness) while Design B had 2 tipped (weakness). Choice A is correct because the test results showed that Design A held brushes more steady with zero tipping compared to Design B's two, highlighting this as a strength. Choice C represents a confusion of results, which happens when students reverse the data outcomes, such as claiming Design A tipped more when the data shows it tipped less. To help students collect and analyze test data: Model the process—identify problem, design two solutions, test both the same way, record what happens for each, compare results. Use simple data tables with columns for each design and rows for different test results (how much water collected? how long did it take? did it spill?). Teach vocabulary of analysis: strength (what worked well), weakness (what could be better), trade-off (Design A good at X but not Y, Design B opposite). Practice fair testing—same conditions for both designs, otherwise comparison isn't valid. Have students make observations, then state them as strengths/weaknesses. Emphasize that usually no design is perfect—each has pros and cons. Use results to make decisions: 'If we need to save space, Design B is better even though it overflowed. If we need to catch all water, Design A is better even though it's bigger.' Watch for students who claim one design is better without specifying for what purpose, or who ignore data to state personal preferences.