Evaluate a Model or Explanation
Sample Question:
Does the data support the claim that the force applied is directly proportional to acceleration?
What’s Being Tested: Can you determine whether data validates a physical relationship or model?
Knowledge & Skills Required:
- Recognizing physical relationships (like Newton’s Second Law)
- Reading graphs or tables with multiple variables (e.g., force vs. acceleration)
What’s Needed to Answer Correctly:
- Ability to interpret direction and proportionality in data
- Distinguish between exact, approximate, or no match
Correct Approach:
- Look at how one variable changes as the other increases
- Determine if the pattern is linear, inverse, or inconsistent
- Decide if the data supports, partially supports, or contradicts the model
Assess Whether a Result Supports or Contradicts a Pattern
Sample Question:
Does Trial 4 contradict the trend observed in Trials 1–3?
What’s Being Tested: Can you identify anomalies or consistent outcomes in a pattern?
Knowledge & Skills Required:
- Ability to spot outliers in numerical or visual data
- Knowing what “contradiction” means in a data context (e.g., significant deviation)
What’s Needed to Answer Correctly:
- Understand that slight variation may be normal, but major reversal signals contradiction
- Avoid labeling something as contradictory unless it clearly breaks the trend
Correct Approach:
- Analyze whether Trial 4’s result fits the established pattern (e.g., increasing or linear)
- Judge how far it deviates from expected behavior
- Select “contradicts” only if the result goes against the trend
Predict Outcomes Using a Model
Sample Question:
If the same experiment were conducted on the Moon (with less gravity), how would the object’s acceleration change?
What’s Being Tested: Can you apply the given model or pattern to a hypothetical situation?
Knowledge & Skills Required:
- Understanding how a model links variables (e.g., acceleration depends on net force and mass)
- Using logic to apply the same relationship to a new context
What’s Needed to Answer Correctly:
- Identify what changes in the new scenario and how that affects the outcome
- Use consistent application of the model without outside physics knowledge
Correct Approach:
- Refer to the variable relationships shown in the passage
- Replace one variable with its new value or condition (e.g., lower g)
- Predict the new result using the same logic shown in the original model
Predict the Behavior of a Similar Object or Setup
Sample Question:
If a ball twice as heavy as in Trial 1 were used, what time would it likely take to reach the ground under the same conditions?
What’s Being Tested: Can you apply observed patterns to a new object or condition?
Knowledge & Skills Required:
- Recognizing what variables do or don’t affect outcomes based on data
- Interpreting experimental constants and how new inputs fit
What’s Needed to Answer Correctly:
- Understand from the experiment whether mass affects time (e.g., in free fall, it may not)
- Predict only using trends shown in the passage
Correct Approach:
- Find similar trials with varying mass and note the effect (or lack thereof)
- Use that pattern to estimate what will happen for the new object
- Eliminate answers that contradict the experimental trend
Choose the Best Explanation for an Observed Result
Sample Question:
What best explains why the object in Trial 5 traveled farther than expected?
What’s Being Tested: Can you identify the most plausible reason for an unexpected observation?
Knowledge & Skills Required:
- Connecting possible causes to effects (e.g., reduced friction → more distance)
- Understanding how setup differences can cause surprising outcomes
What’s Needed to Answer Correctly:
- Look for possible setup changes or conditions mentioned that could explain it
- Eliminate choices that aren’t consistent with the experiment’s context
Correct Approach:
- Revisit the description of Trial 5 for unique factors (e.g., surface, incline)
- Match the unusual result to a logical cause
- Choose the explanation that directly connects to the outcome and is consistent with physics logic
Judge the Validity of a Conclusion
Sample Question:
Do the results support the student’s conclusion that mass does not affect acceleration on a frictionless ramp?
What’s Being Tested: Can you critically evaluate a claim using the provided data?
Knowledge & Skills Required:
- Distinguishing what the data actually shows vs. what is claimed
- Understanding how to validate a conclusion with evidence
What’s Needed to Answer Correctly:
- Avoid accepting the claim at face value
- Compare multiple trials with different mass but same ramp, surface, or incline
Correct Approach:
- Find trials where only mass varies
- Check if acceleration stayed constant (or changed)
- Choose whether the data fully supports, partially supports, or contradicts the claim
Resolve a Discrepancy Without Disproving the Model
Sample Question:
The object in Trial 3 slowed down instead of speeding up. Which of the following explanations is consistent with the model and the observed data?
What’s Being Tested: Can you explain anomalous data as a special case, not a full rejection of the model?
Knowledge & Skills Required:
- Understanding external influences (e.g., friction, faulty sensors)
- Recognizing the difference between flawed model vs. flawed execution
What’s Needed to Answer Correctly:
- Isolate a plausible reason that affects only that trial
- Ensure the explanation fits both the model and the result
Correct Approach:
- Review conditions in Trial 3 for anything different (e.g., new ramp material)
- Pick the explanation that keeps the original model intact but explains the exception
- Eliminate choices that require abandoning the model