Sofia and Marcus tested containers to keep small toys sorted. Design A is one box and the toys got mixed (yes). Design B has dividers and the toys stayed separated (yes). A helped hold toys, but mixing was a weakness. B was strong because dividers kept toys apart. They need to decide which container works better for organizing. Design B works better than Design A because the data shows toys stayed separated. The dividers stop mixing, so it solves the organization problem. Based on the data, how do they know Design B works better?
- Design B works better because the data shows toys stayed separated, so dividers stop mixing. (correct answer)
- Design B works better because it is new and fun to use.
- Design A works better because the toys got mixed up in one box.
- Design B works better because toys stayed separated.
Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, [problem: organizing supplies without mixing]. Test data showed: Design A [results: items got mixed (yes)]. Design B [results: items stayed separated (yes)]. The students concluded that Design [B] works better because [specific reasoning from stimulus: the data shows items stayed separated, proving the dividers prevent supplies from mixing]. Choice [A] is correct because it [identifies correct design based on data: chooses design with better performance; provides evidence: cites specific test results; explains reasoning: connects data to design feature to problem solution; makes complete argument: includes all three parts of evidence-based conclusion]. For example, [specific complete reasoning: 'Design B is better because test results show items stayed separated (evidence), proving the dividers (design feature) prevent supplies from getting mixed up (solves problem)']. Choice [B] represents [error type: opinion without evidence]. This error typically occurs when students [developmental explanation: don't use data to decide, pick design they prefer instead of one that performed better]. To help students make evidence-based conclusions: Use three-part frame: 'Design [X] works better because [data evidence] shows that [design feature] [solves problem successfully]'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('I like A better') and evidence-based conclusion ('A works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.