Top 10 Mistakes in Physics IA

The IB Physics Internal Assessment challenges students to apply theory, experimentation, and critical thinking in a single investigation. Understanding common mistakes and how to avoid them can significantly improve the clarity of the IA, helping students gain high marks. This post will outline the top 10 mistakes students make in the IB Physics IA. Read this post to learn what some common mistakes are and how to avoid them. 

Top 10 Mistakes in IB Physics

1. Poorly defined variables – Students often fail to clearly define independent, dependent, and control variables, or miss out on stating the units. Unclear independent and dependent variables can lead to a confusing or unfocused research question, while uncontrolled variables (e.g., temperature, friction, air resistance) can significantly reduce the reliability of the results. Students should clearly explain each control variable, why it should be controlled, and how it was controlled during the experiment. If a variable cannot be controlled, students should note this and, where possible, discuss its impact quantitatively. A good example of well-defined variables can be found here. 

    

2. Using poorly calibrated equipment  – A common mistake is using equipment with insufficient precision, such as low-resolution stopwatches or rulers with faded gradings, for experiments requiring high accuracy. Instrument uncertainty directly affects derived quantities and subsequent calculations. Ignoring calibration errors reduces credibility and can introduce systematic errors to the results.

    

3. Insufficient data points  – Many students collect too few data points or use a narrow range for the independent variable, resulting in weak trends and unreliable graphs. Repetitions of the experiment are crucial to ensure that the results are significant and the study is replicable. Students should aim to have a minimum of 3 trials per independent variable increment. A good example of a sufficient dataset can be found in this exemplar. 

    

4. Limited background information – Many Physics IAs include a brief, textbook-style theory that is not strongly linked to the investigation. This makes the work appear generic and limits the reader's understanding of the physics theory behind the investigation. To avoid this, students should ensure they conduct in-depth background research using scientific articles rather than non-credible websites. Students should include figures, images, and equations where necessary. A good example of an IA with a strong background can be found here. 

    

5. Incorrect uncertainty propagation – Students frequently misunderstand uncertainty propagation, confuse random and systematic errors, or omit uncertainties from graphs and calculations (e.g. missing error bars in graphs). Uncertainty analysis is essential for demonstrating the validity of the results, so a poor explanation of the uncertainties can limit the score obtained in the Analysis criterion. To gain a high score in this criterion, students should include absolute and percentage uncertainties, propagate errors correctly, and show sample calculations. Uncertainty bars should be added to graphs, and it should be explained how uncertainties affect the final results. A good example can be seen in this IA.

    

    

6. Unclear graphs – Graphs are often poorly labelled, lack units, or use incorrect scales. Some students calculate gradients incorrectly or fail to linearize the data when appropriate. Since physics heavily relies on graphical interpretation, this directly impacts the results if they are not clearly presented and understood by the examiner. To avoid this mistake, students should label the axes with quantities and units, include uncertainty bars, and use appropriate lines of best fit (e.g. linear, quadratic, etc.). A good example can be found here.

    

7. Not using numerical values in the conclusion – The conclusion is meant to tie the loose ends of the investigation together and give the reader a summary of the experimental findings. The most common mistake made by students is that they only describe the general experimental trends without using any numerical data from the experiment. Students are encouraged to use their experimental data to support their conclusions. A good example can be seen in this IA. 

    

8. Incomplete evaluation: Most students include some kind of evaluation of their work; however, it is often incomplete. Students may discuss the limitations of the experiment in depth, but may not give as much importance to the strengths. To get a high mark in the Evaluation criterion, students should ensure they discuss both the experimental strengths and limitations. When discussing the limitations, make sure to classify them as random, systematic or human errors. Additionally, describe how the errors affected the experimental results and state some improvements that can be made in future to prevent these errors from happening if the experiment were to be repeated. A strong evaluation can be seen here and here.

    

9. Inconsistent use of significant figures – Many students change the number of significant figures throughout calculations and when reporting results (e.g. rounding to 3 significant figures in data tables but using 5 significant figures in the graph). Students should ensure they keep the number of significant figures consistent throughout the IA. 

    

10. No comparison between experimental and theoretical values – Students often focus only on their own experiment and fail to connect it to literature from the broader scientific community. Students should ensure they provide a comparison of their results to the results from at least one published scientific paper. A good example of this can be seen here.