IBPhysicsDPSLRevision NotesInquiry ProcessInquiry 3: Concluding and Evaluating in PhysicsEvaluating in Physics

Evaluating in Physics (DP IB Physics): Revision Note

Katie M

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Katie M

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DP Physics: SLDP Physics: HL

Evaluating in Physics

  • The evaluation is a critical reflection on your investigation's methodology

  • This is where you demonstrate your understanding of the scientific process by identifying the weaknesses and limitations of your own work

  • The goal is to assess the quality of your data and its impact on your conclusion, and to suggest meaningful, realistic improvements

Principles of evaluation

Evaluate your hypothesis

  • This is the final comment on your hypothesis, which should follow on from your conclusion

  • Even if your data supported your hypothesis, you should evaluate the strength of this support in light of the uncertainties and errors you have identified

  • For example:

    • The data supported the hypothesis that resistance is proportional to length

    • However, the fact that the y-intercept did not pass through the origin suggests a systematic error was present

    • This slightly weakens the confirmation of the theoretical model

Identify and discuss sources of error

  • This is the most important part of your evaluation

  • You must identify and discuss specific sources of error in your procedure, distinguishing between the two main types

    1. Systematic errors:

      • These are flaws in the experimental method or apparatus that cause the result to be consistently wrong in the same direction (e.g., always too high or always too low)

      • Example 1:

        • A zero error on a digital balance or ammeter that was not corrected

        • All readings will be consistently offset by the same amount

      • Example 2:

        • Not accounting for heat loss in a thermal physics experiment

        • This will always cause the measured temperature change to be smaller than the true value

    2. Random errors:

      • These are unpredictable variations in measurements that occur by chance

        • They cause results to be scattered around the true value

      • Example 1:

        • Fluctuations in your reaction time when starting and stopping a stopwatch to time oscillations

      • Example 2:

        • Parallax error when reading an analogue meter scale from different angles

      • Random errors can be minimised by taking multiple repeat trials and calculating an average

Evaluate methodological weaknesses, limitations and assumptions

  • Beyond errors, you should also discuss other aspects of your method that affect the quality of your conclusion

  • Weaknesses:

    • These are the aspects of your method that lead to significant systematic or random errors

    • For example:

      • Timing only a single swing of a pendulum is a key methodological weakness, as the period is very short, making the random error from human reaction time extremely significant

  • Limitations:

    • These are factors that limit the scope of your conclusion

    • They define the boundaries within which your conclusion is valid

    • For example:

      • This investigation was limited to a maximum pendulum length of 1.00 m

      • Therefore, the conclusion that T squared is proportional to L cannot be assumed to be valid for much longer pendulum systems

  • Assumptions:

    • These are simplifications made during your calculations that are not perfectly true

    • For example:

      • In the analysis of the pendulum, it was assumed that air resistance was negligible and that the string was massless.

      • In reality, these factors have a minor damping effect on the pendulum's motion

Explain realistic and relevant improvements

  • For every significant weakness or source of error you identify, you must suggest a specific, realistic improvement

  • The improvement must be relevant

    • It should directly address the weakness you identified

  • The improvement must be realistic

    • You should be able to carry it out in a typical school laboratory

    • For example, using a bomb calorimeter is not a realistic improvement

Worked Example

Research question:

  • "What is the value of the acceleration due to gravity, g, determined from the period and length of a simple pendulum?"

Weakness 1 (systematic error):

  • The length of the pendulum was measured to the bottom of the bob, not to its centre of mass.

  • Impact:

    • This caused the measured length L to be consistently longer than the true effective length

    • Since T is proportional to square root of L, this would lead to a consistently larger period for each length, and a calculated value for g that is systematically too high

  • Realistic Improvement:

    • The length should be measured to the geometric centre of the bob

    • For an even more accurate result, the bob's diameter could be measured with vernier callipers, and half of this value could be added to the measured length of the string

Weakness 2 (systematic/random error):

  • The period was determined by timing 20 oscillations with a manual stopwatch

  • Impact:

    • Human reaction time in starting and stopping the watch introduces random error, causing scatter in the measured times

    • This was visible in the error bars and the slight scatter of points around the line of best fit on the graph

  • Realistic Improvement:

    • The precision of the timing could be significantly improved by using a light gate placed at the bottom of the swing to automatically record the period, removing human reaction time error

Limitation:

  • The experiment relied on the small-angle approximation (θ < 10°)

  • Impact:

    • While a protractor was used to set an initial angle of 8°, it was difficult to ensure this was exact for every trial, and the amplitude may have changed during the swings

    • If the angle becomes too large, the period becomes amplitude-dependent, which would invalidate the theoretical model being tested

  • Realistic Improvement:

    • The initial release angle could be more rigorously controlled using a fixed release point

    • Video analysis could also be used to track the amplitude over the 20 swings to ensure it remains within the small-angle regime

Examiner Tips and Tricks

Be specific.

  • Never blame "human error".

  • Instead of saying "My measurements were wrong," identify a specific source of error, like "The parallax error when reading the position of the pointer on the metre ruler could have led to inconsistent length measurements."

Prioritise your evaluation.

  • Focus on the one or two most significant sources of error that had the biggest impact on your final result.

  • For a pendulum lab, discussing the measurement of the period or the effective length is always more important than the friction in the pivot.

Close the loop: Weakness → Impact → Improvement.

  • For every weakness you identify, you must explain its impact on your final result and then suggest a specific improvement to fix it.

Evaluate your own data.

  • Do not write a generic evaluation that could apply to any experiment.

  • Refer back to your own results, graphs, and observations.

  • For example, "The non-zero y-intercept on the R vs. L graph suggests a systematic error, such as contact resistance, was present."

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    Katie M

    Author: Katie M

    Expertise: Physics Content Creator

    Katie has always been passionate about the sciences, and completed a degree in Astrophysics at Sheffield University. She decided that she wanted to inspire other young people, so moved to Bristol to complete a PGCE in Secondary Science. She particularly loves creating fun and absorbing materials to help students achieve their exam potential.