Elementary School Science Quiz: Comparing Design Strengths
20 questions · exam conditions
0:00
Comparing Design StrengthsQuestion 1 of 20

Keisha and Carlos read the funnel results. Design A (wide opening) spilled 2 tablespoons. Design B (narrow opening) spilled 5 tablespoons. They say a weakness is what doesn't work well, shown by more spilling. They connect the narrow opening to missing the cup. From the testing, what weakness did Design B show?

A weakness of Design B is more spilling because the data shows 5 tablespoons.
A weakness of Design B is less spilling because the data shows 2 tablespoons.
A weakness of Design B is being wide, so it catches too much.
A weakness of Design B is it looks small, not from data.
← Back to quizzes

Elementary School Science Quiz

Elementary School Science Quiz: Comparing Design Strengths

Practice Comparing Design Strengths 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 Comparing Design Strengths, 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 and Carlos read the funnel results. Design A (wide opening) spilled 2 tablespoons. Design B (narrow opening) spilled 5 tablespoons. They say a weakness is what doesn't work well, shown by more spilling. They connect the narrow opening to missing the cup. From the testing, what weakness did Design B show?

  1. A weakness of Design B is more spilling because the data shows 5 tablespoons. (correct answer)
  2. A weakness of Design B is less spilling because the data shows 2 tablespoons.
  3. A weakness of Design B is being wide, so it catches too much.
  4. A weakness of Design B is it looks small, not from data.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two funnel designs for pouring - Design A had wide opening, Design B had narrow opening. The test data showed: Design A spilled 2 tablespoons; Design B spilled 5 tablespoons. Based on this data, Design B's weakness is more spilling due to narrow opening (data shows 5); Design A's strength is less spilling (data shows 2). Choice A is correct because it correctly identifies Design B's weakness with evidence; it states more spilling as weakness because data shows 5 tablespoons. Choice B represents wrong data; this error typically occurs when students use wrong data. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows 5 tablespoons - that means more spilling is a weakness because it doesn't work well for pouring'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 2

Yuki and Carlos look at shelf tests for storing books. Design A (one shelf): holds 8 books. Design B (three shelves): holds 24 books. They say more books held means it works well for storage. Based on the data, which design holds more books?

  1. Design A holds more books because the results show 24 books.
  2. Design B holds more books because the results show 24 books. (correct answer)
  3. Design A holds more books because it has one shelf.
  4. Both hold 8 books because shelves are the same.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two shelf designs for storing books - Design A had one shelf, Design B had three shelves. The test data showed: Design A holds 8 books, Design B holds 24 books. Based on this data, Design B's strength is holding more books (24); Design A's weakness is holding fewer (8). Choice B is correct because it makes evidence-based comparison; it uses data from both designs to compare performance, correctly identifying Design B holds more with 24 books. Choice C represents wrong feature without data connection, saying Design A holds more based on one shelf but ignoring actual numbers. This error typically occurs when students identify features but don't connect to results, or confuse which design performed better. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows 24 books - that means more shelves are a strength because it holds more'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 3

At a table, Sofia and Chen look at tray test data: Design A (flat board) had 2 of 3 books fall, and Design B (board with edges) had 0 of 3 books fall. They say they must use the numbers as evidence. They notice Design A has no edges, so books can slide. They record strengths and weaknesses from the results. Based on the test results, what is a weakness of Design A?

  1. A weakness of Design A is no edges because the data shows 2 books fell. (correct answer)
  2. A weakness of Design A is edges because the data shows 0 books fell.
  3. A weakness of Design A is it is blue, and blue is bad.
  4. A weakness of Design A is no books fell because the tray is perfect.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two tray designs for carrying books - Design A had flat board, Design B had board with edges. The test data showed: Design A 2 of 3 books fell; Design B 0 of 3 books fell. Based on this data, Design A's weakness is no edges that allowed books to fall (data shows 2 fell); Design B's strength is edges that kept books on (data shows 0 fell). Choice A is correct because it correctly states what design doesn't do well and provides data support; it correctly identifies Design A's weakness as no edges because data shows 2 books fell. Choice C represents opinion without data; this error typically occurs when students give opinions instead of using data. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows 2 books fell - that means no edges are a weakness because they don't work well to keep books on'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 4

Maya and Marcus compare shelf designs using test data. Design A (one shelf) held 8 books. Design B (three shelves) held 24 books. They say a weakness is when a design holds less than needed. They use the numbers as evidence. Based on the data, what is a weakness of Design A?

  1. A weakness of Design A is limited storage because the data shows 8 books. (correct answer)
  2. A weakness of Design A is holding 24 books because it is too strong.
  3. A weakness of Design A is three shelves because it is tall.
  4. A weakness of Design A is it is made fast, not from results.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two shelf designs for storage - Design A had one shelf, Design B had three shelves. The test data showed: Design A held 8 books; Design B held 24 books. Based on this data, Design A's weakness is limited storage (data shows 8 books); Design B's strength is more storage (data shows 24). Choice A is correct because it correctly identifies Design A's weakness with evidence; it uses data showing Design A held 8 books to support limited storage. Choice B represents reversed evaluation; this error typically occurs when students reverse good and poor performance. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows 8 books - that means limited storage is a weakness because it doesn't work well for holding many'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 5

Amir and Maya study container tests. Design A was one box, and items got mixed (yes). Design B had dividers, and items stayed separated (yes). They use the data to find strengths and weaknesses. From the testing, why are dividers a strength in Design B?

  1. Dividers are a strength because the data shows items stayed separated in Design B. (correct answer)
  2. Dividers are a strength because the data shows items got mixed in Design B.
  3. Dividers are a strength because they make the box look pretty.
  4. Dividers are a strength because Design A stayed separated in the test.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two container designs for organizing supplies - A had one space, B had dividers. The test data showed: Design A items got mixed together (yes). Design B items stayed separated (yes). Based on this data, Design B's strength is dividers that kept items separated; Design A's weakness is single space that allowed mixing. Choice A is correct because it correctly states what design does well and provides data support - it identifies that dividers are a strength because data shows items stayed separated in Design B. Choice B represents reversed evaluation - this error typically occurs when students call good performance a weakness or vice versa, saying items got mixed when the data shows they stayed separated. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows items stayed separated - that means the dividers are a strength because they work well to keep items organized'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 6

Carlos and Emma review results: Design A is a narrow base and it tipped over (yes). Design B is a wide base and it stayed standing (yes). They say both were tested the same way. The wide base helped it not tip. Based on the test results, what is a strength of Design B?

  1. A strength of Design B is it tipped over because the data says yes.
  2. A strength of Design B is wide base because the data shows it stayed standing. (correct answer)
  3. A strength of Design B is it is tall, so it stayed standing.
  4. A strength of Design B is narrow base because it stayed standing.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two platform designs for stability - A had narrow base, B had wide base. The test data showed: Design A tipped over (yes). Design B stayed standing (yes). Based on this data, Design B's strength is the wide base that kept it stable (data shows it stayed standing); Design A's weakness is narrow base that made it unstable (data shows it tipped over). Choice B is correct because it identifies strength with evidence - correctly states what design feature works well and provides data support, identifying that Design B's strength is wide base because data shows it stayed standing. Choice A represents reversed evaluation. This error typically occurs when students call poor performance a strength, confusing that tipping over is bad performance, not good. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows it stayed standing - that means the wide base is a strength because it works well to keep it stable'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 7

During design review, Jamal and Sofia test shelf storage. Design A has one shelf and holds 8 books. Design B has three shelves and holds 24 books. They say holding more books is a strength for storage. They use the same size books for both tests. Looking at the results, what does the data show about Design B?

  1. Design B holds more books because the data shows 24 books. (correct answer)
  2. Design B holds fewer books because the data shows 8 books.
  3. Design B holds more books because it is painted red.
  4. Design B holds 80 books because three shelves means 80.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two shelf designs for storage - Design A had one shelf, Design B had three shelves. The test data showed: Design A held 8 books; Design B held 24 books. Based on this data, Design B's strength is holding more books (data shows 24); Design A's weakness is holding fewer (data shows 8). Choice A is correct because it correctly identifies Design B's strength with evidence; it uses data showing Design B held 24 books to support holding more. Choice C represents irrelevant feature; this error typically occurs when students focus on non-functional features. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows 24 books - that means holding more is a strength because it works well for storage'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 8

At the science table, Amir and Yuki test two funnel designs. Design A has a wide opening and spilled 2 tablespoons. Design B has a narrow opening and spilled 5 tablespoons. They say less spilling means it works well. They compare both designs with the same pour. Based on the data, which design spilled less?

  1. Design B, because the data shows it spilled 2 tablespoons.
  2. Design A, because the data shows it spilled 2 tablespoons. (correct answer)
  3. Design B, because narrow openings always spill less.
  4. Both designs, because 2 and 5 are the same.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two funnel designs for pouring - Design A had wide opening, Design B had narrow opening. The test data showed: Design A spilled 2 tablespoons; Design B spilled 5 tablespoons. Based on this data, Design A's strength is less spilling (data shows 2); Design B's weakness is more spilling (data shows 5). Choice B is correct because it correctly identifies Design A's strength of spilling less with evidence; it uses data showing Design A spilled 2 tablespoons, which is less than 5. Choice A represents confusing designs; this error typically occurs when students confuse which design had which result. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows 2 tablespoons spilled - that means less spilling is a strength because it works well for pouring'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 9

Marcus and Yuki compare two containers using results. Design A (one box) had items get mixed (yes). Design B (box with dividers) had items stay separated (yes). They say evidence comes from the test results. Based on the data, what is a weakness of Design A?

  1. A weakness of Design A is dividers kept items apart, based on testing.
  2. A weakness of Design A is items mixed because the results say yes. (correct answer)
  3. A weakness of Design A is it is bigger, so it must mix.
  4. A weakness of Design A is items stayed separated, so it doesn't work.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two container designs for organizing supplies - A had one box, B had box with dividers. The test data showed: Design A (one box) had items get mixed (yes). Design B (box with dividers) had items stay separated (yes). Based on this data, Design A's weakness is single space that allowed mixing; Design B's strength is dividers that kept items separated. Choice B is correct because it correctly states what design doesn't do well and provides data support - it identifies that Design A's weakness is items mixed because the results say yes. Choice A represents wrong feature - this error typically occurs when students confuse which design had which feature, saying Design A had dividers when it was actually one box. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows items mixed - that means one box is a weakness because it doesn't work well to keep items organized'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 10

In the classroom, Carlos and Keisha test two base designs for stability. The results show Design A (narrow base) tipped over: yes. Design B (wide base) stayed standing: yes. They say tipping over means it doesn't work well. They compare using the same push each time. Based on the test results, what is a strength of Design B?

  1. A strength of Design B is the wide base because it stayed standing. (correct answer)
  2. A strength of Design B is the narrow base because it tipped over.
  3. A strength of Design B is it is shiny, so it works well.
  4. A strength of Design B is it tipped over because the data says yes.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two base designs for stability - Design A had narrow base, Design B had wide base. The test data showed: Design A tipped over (yes); Design B stayed standing (yes). Based on this data, Design B's strength is the wide base that prevented tipping (data shows stayed standing); Design A's weakness is narrow base that caused tipping (data shows tipped over). Choice A is correct because it correctly states what design does well and provides data support; it identifies Design B's strength as the wide base because data shows it stayed standing. Choice D represents reversed evaluation; this error typically occurs when students call good performance a weakness or vice versa. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows stayed standing - that means the wide base is a strength because it works well to keep stable'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 11

During science talk, Amir and Maya compare two reach platforms. The results say Design A is 3 inches high and helped reach 48 inches. Design B is 6 inches high and helped reach 51 inches. They use the same measuring tape for both tests. They say higher reach means it works better for reaching. Looking at the results, which design reached higher?

  1. Design A, because the results tell us it reached 51 inches.
  2. Design B, because the results tell us it reached 51 inches. (correct answer)
  3. Design A, because it is smaller and that is always better.
  4. Both designs, because they reached the same height in the data.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two platform designs for reaching - Design A was 3 inches high, Design B was 6 inches high. The test data showed: Design A reached 48 inches high; Design B reached 51 inches high. Based on this data, Design B's strength is providing more height (data shows 51 inches); Design A's weakness is providing less height (data shows 48 inches). Choice B is correct because it correctly identifies Design B's strength of reaching higher and provides data support; it uses data from both designs to compare performance, correctly stating Design B reached 51 inches. Choice C represents opinion without data; this error typically occurs when students give opinions instead of using data. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows 51 inches - that means the height is a strength because it works well to reach higher'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 12

Emma and Chen look at stability results together. Design A has a narrow base and tipped over (yes). Design B has a wide base and stayed standing (yes). They say a weakness is what doesn't work well, shown by the results. They connect the narrow base to tipping. From the testing, what weakness did Design A show?

  1. A weakness of Design A is tipping over because the results say yes. (correct answer)
  2. A weakness of Design A is staying standing because the results say yes.
  3. A weakness of Design A is being wide, so it takes up space.
  4. A weakness of Design A is it looks boring, not the data.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two base designs for stability - Design A had narrow base, Design B had wide base. The test data showed: Design A tipped over (yes); Design B stayed standing (yes). Based on this data, Design A's weakness is tipping over due to narrow base (data shows yes); Design B's strength is staying standing (data shows yes). Choice A is correct because it correctly states what design doesn't do well and provides data support; it identifies Design A's weakness as tipping over because data shows yes. Choice B represents reversed evaluation; this error typically occurs when students reverse good and poor performance. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows tipped over yes - that means tipping is a weakness because it doesn't work well for stability'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 13

During design review, Emma and Jamal read results: Tray A (flat) had 2 of 3 books fall; Tray B (edges) had 0 of 3 books fall. They say Tray B works well because the edges help hold books on. They write that Tray A doesn't work well because it has no edges and books can slide off. They compare both designs using the same test. Based on the test results, what is a strength of Design B?

  1. A strength of Design B is the edges because the data shows 0 books fell. (correct answer)
  2. A strength of Design B is being flat because the data shows 2 books fell.
  3. A strength of Design B is it looks nicer, so it must work well.
  4. A strength of Design B is 3 books fell because edges push books off.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two tray designs for carrying books - Design A had flat board, Design B had raised edges. The test data showed: Design A 2 of 3 books fell; Design B 0 of 3 books fell. Based on this data, Design B's strength is the raised edges that prevented books from falling (data shows 0 fell); Design A's weakness is lack of edges that allowed books to slide off (data shows 2 fell). Choice A is correct because it correctly states what design does well and provides data support; it correctly identifies that Design B's strength is the edges because data shows 0 books fell (all stayed on). Choice B represents wrong feature; this error typically occurs when students confuse which design had which results. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows 0 books fell - that means the edges are a strength because they work well to keep books on'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 14

Sofia and Chen look at results: Design A had 2 of 3 books fall; Design B had 0 of 3 fall. They write that edges help keep books on the tray. They also note Design A has no edges, so books slide off. Based on the data, what weakness did the testing show about Design A?

  1. A weakness of Design A is it has edges because the data shows 0 fell.
  2. A weakness of Design A is no edges because the data shows 2 fell. (correct answer)
  3. A weakness of Design A is it is blue, so it doesn't work.
  4. A weakness of Design A is the handle because the data shows 2 fell.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two tray designs for carrying books - A had no edges, B had edges. The test data showed: Design A had 2 of 3 books fall. Design B had 0 of 3 books fall. Based on this data, Design A's weakness is lack of edges that allowed books to slide off (data shows 2 fell); Design B's strength is the edges that prevented books from falling (data shows 0 fell). Choice B is correct because it correctly states what design doesn't do well and provides data support - it identifies that Design A's weakness is no edges because data shows 2 of 3 books fell off. Choice C represents aesthetic focus. This error typically occurs when students focus on non-functional features like color instead of using test data about performance. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows 2 books fell - that means no edges is a weakness because they don't work well to keep books on'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 15

Amir, Maya, and Marcus review results: Design A had 2 of 3 books fall; Design B had 0 of 3 fall. They say both designs carried 3 books, but one kept them on better. They use the data to compare. Based on the data, which design kept books on better?

  1. Based on data, Design A kept books on better because 2 of 3 fell.
  2. Based on data, Design B kept books on better because 0 of 3 fell. (correct answer)
  3. Based on data, both designs are the same because both used boards.
  4. Based on data, Design B kept books on better because it looks strong.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two tray designs for carrying books - A had no edges, B had edges. The test data showed: Design A had 2 of 3 books fall. Design B had 0 of 3 books fall. Based on this data, Design B kept books on better because 0 fell compared to Design A where 2 fell. Choice B is correct because it makes evidence-based comparison - uses data from both designs to compare performance, correctly identifying that Design B kept books on better because data shows 0 of 3 fell (versus 2 of 3 for Design A). Choice A represents reversed evaluation. This error typically occurs when students call good performance a weakness or vice versa, misreading that 2 falling is worse performance, not better. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows 0 books fell for B and 2 fell for A - that means B kept books on better'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 16

Keisha and Carlos review results: Design A reached 48 inches high using a 3-inch platform. Design B reached 51 inches high using a 6-inch platform. They say higher reach works well for high shelves. They use the data to compare. Based on the data, which design helped reach higher?

  1. Based on data, Design A helped reach higher because it reached 48 inches.
  2. Based on data, Design B helped reach higher because it reached 51 inches. (correct answer)
  3. Based on data, both helped the same because both are platforms.
  4. Based on data, Design B helped reach higher because it is a fun color.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two platform designs for reaching - A was 3 inches high, B was 6 inches high. The test data showed: Design A reached 48 inches high. Design B reached 51 inches high. Based on this data, Design B's strength is providing more height (data shows reached 51 inches); Design A's weakness is providing less height (data shows reached only 48 inches). Choice B is correct because it makes evidence-based comparison - uses data from both designs to compare performance, correctly identifying that Design B helped reach higher because data shows it reached 51 inches (versus 48 for Design A). Choice D represents aesthetic focus. This error typically occurs when students focus on non-functional features like color instead of using test measurements. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows B reached 51 inches and A reached 48 - that means B helped reach higher'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 17

Chen and Maya review results: Design A is one shelf and holds 8 books. Design B is three shelves and holds 24 books. They say more books held means it works well for storage. They use the numbers to compare. Based on the data, which design holds more books?

  1. Based on data, Design A holds more books because it holds 24 books.
  2. Based on data, Design B holds more books because it holds 24 books. (correct answer)
  3. Based on data, both hold the same because shelves are wood.
  4. Based on data, Design B holds more books because it looks bigger.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two shelf designs for holding books - A had one shelf, B had three shelves. The test data showed: Design A holds 8 books. Design B holds 24 books. Based on this data, Design B's strength is holding more books (data shows 24 books); Design A's weakness is holding fewer books (data shows only 8 books). Choice B is correct because it makes evidence-based comparison - uses data from both designs to compare performance, correctly identifying that Design B holds more books because data shows it holds 24 books (versus 8 for Design A). Choice D represents opinion without data. This error typically occurs when students give opinions based on appearance instead of using actual test numbers. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows B holds 24 books and A holds 8 - that means B holds more'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 18

Emma and Jamal review results: Design A had 2 of 3 books fall; Design B had 0 of 3 fall. They say Design B works well because the edges hold books in. Design A does not work well because it has no edges and books slid off. Based on the test results, what is a strength of Design B?

  1. A strength of Design B is its edges because the data shows 0 fell. (correct answer)
  2. A strength of Design B is it is prettier, so it works well.
  3. A strength of Design B is no edges because the data shows 2 fell.
  4. A strength of Design B is it held 3 books because 2 fell off.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two tray designs for carrying books - A had no edges, B had edges. The test data showed: Design A had 2 of 3 books fall. Design B had 0 of 3 books fall. Based on this data, Design B's strength is the edges that prevented books from falling (data shows 0 fell); Design A's weakness is lack of edges that allowed books to slide off (data shows 2 fell). Choice A is correct because it correctly states what design does well and provides data support - it identifies that Design B's strength is the edges because data shows 0 books fell (all stayed on). Choice B represents opinion without data. This error typically occurs when students give opinions instead of using data, thinking 'prettier' means it works better without looking at test results. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows 0 books fell - that means the edges are a strength because they work well to keep books on'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 19

Jamal and Sofia review results: Design A has a narrow base and it tipped over (yes). Design B has a wide base and it stayed standing (yes). They connect the base shape to what happened. Based on the data, what weakness did the testing show about Design A?

  1. A weakness of Design A is narrow base because the data shows it tipped over. (correct answer)
  2. A weakness of Design A is wide base because the data shows it stayed standing.
  3. A weakness of Design A is it is shiny, so it tipped over.
  4. A weakness of Design A is it tipped over, and that is a strength.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two platform designs for stability - A had narrow base, B had wide base. The test data showed: Design A tipped over (yes). Design B stayed standing (yes). Based on this data, Design A's weakness is narrow base that made it unstable (data shows it tipped over); Design B's strength is the wide base that kept it stable (data shows it stayed standing). Choice A is correct because it identifies weakness with evidence - correctly states what design feature doesn't work well and provides data support, identifying that Design A's weakness is narrow base because data shows it tipped over. Choice C represents aesthetic focus. This error typically occurs when students focus on non-functional features like shininess instead of using test data about actual performance. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows it tipped over - that means the narrow base is a weakness because it doesn't work well to keep it stable'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.

Question 20

Emma and Jamal review results: Design A had 2 of 3 books fall; Design B had 0 of 3 fall. They say Design B's strength is the edges because the data shows none fell. They say Design A's weakness is no edges because the results tell us 2 books fell. They compare fairly because both carried 3 books. Based on the test results, what is a strength of Design B?

  1. A strength of Design B is the edges because the data shows 0 books fell. (correct answer)
  2. A strength of Design B is being flat because the data shows 2 books fell.
  3. A strength of Design B is it looks nicer, so it works well.
  4. A strength of Design B is 2 books fell, so it holds books.
Explanation: This question tests the 1st grade skill of analyzing data from tests of two objects to compare the strengths and weaknesses of how each performs (K-2-ETS1-3: Analyze data to compare strengths and weaknesses). After testing two designs, we analyze (look carefully at) the data to find strengths and weaknesses. Strengths are what a design does well - where it performs successfully based on test results (fewer items fell, reached higher, held more, didn't tip, kept items separated, spilled less). Weaknesses are what a design doesn't do well - where it performs poorly based on test results (more items fell, didn't reach as high, held less, tipped over, items mixed together, spilled more). We identify strengths and weaknesses BY LOOKING AT THE DATA - not by guessing or opinions. The data (test results) gives us evidence about how each design performed, and we use that evidence to say what each design's strengths and weaknesses are. In this scenario, two tray designs for carrying books - A had flat board, B had raised edges. The test data showed: Design A had 2 of 3 books fall. Design B had 0 of 3 books fall. Based on this data, Design B's strength is the raised edges that prevented books from falling (data shows 0 fell); Design A's weakness is lack of edges that allowed books to slide off (data shows 2 fell). Choice A is correct because it correctly states what design does well and provides data support - it identifies that Design B's strength is the edges because data shows 0 books fell (all stayed on). Choice B represents wrong feature - this error typically occurs when students confuse which design had which results, calling Design B flat when it actually had edges. To help students analyze data for strengths and weaknesses: Create two-column chart (Strengths | Weaknesses) for each design; explicitly connect data to evaluation ('The data shows 0 books fell - that means the edges are a strength because they work well to keep books on'); practice strength/weakness language (strength = what works well, weakness = what doesn't work well); emphasize evidence ('How do we know? The data shows...'); look at specific results (numbers, yes/no, measurements) to identify performance; compare design features to their results. Watch for: students who give opinions without data, who state results without labeling as strength/weakness, who reverse good and poor performance, who focus on appearance instead of function, who confuse which design had which result, or who think strength/weakness is about whether they like it instead of whether data shows it works well. Key concept: Data tells us about performance → good performance = strength, poor performance = weakness → we base our evaluation on evidence from testing, not on opinions.