Score a 7 in Your IA
Most students lose marks not because their experiment is weak — but because they don’t understand how examiners actually think.
What Most Students Get Wrong
The IB Physics IA is not about performing a complex experiment. It is about demonstrating clear scientific thinking, strong data analysis, and critical evaluation.
A simple experiment with excellent analysis will always outperform a complex experiment with weak reasoning.
IA Criteria Breakdown (2025)
Research Design
This criterion evaluates how well you design your investigation — from the research question to the methodology. It is not just about what you do, but how clearly and logically your experiment is structured.
Your RQ must clearly define the relationship you are investigating.
- Clearly identifies independent (IV) and dependent variable (DV)
- Includes relevant conditions (e.g. constant temperature, fixed length)
- Specific and measurable (not vague)
✅ Strong: How does temperature (20–80°C) affect the resistance of a copper wire under constant current conditions?
Examiners expect clear identification and control of variables.
- Independent variable: what you change
- Dependent variable: what you measure
- Controlled variables: what you keep constant (with justification)
Your method must be detailed enough that another student can repeat the experiment exactly.
- Step-by-step procedure
- Measurement techniques clearly described
- Equipment listed with precision (e.g. ±0.01 s stopwatch)
- Control of variables explained, not just stated
Theory should be integrated into your design — not written as a separate textbook section.
- Relevant equations included and explained
- Prediction of expected relationship (e.g. linear, inverse)
- Link between theory and experiment clearly established
If your method is unclear or variables are poorly controlled, your IA is capped at mid-level marks — no matter how good your data is.
Data Analysis
This is the most important section of your IA. It evaluates how well you transform raw data into meaningful conclusions using physics. Most students lose marks here because they present data without interpreting it.
You must clearly show how your data is collected and how it is transformed.
- Organized raw data tables with correct units
- Processed data (averages, calculations, derived values)
- Consistent significant figures
Uncertainty must be included throughout your analysis — not added at the end.
- Absolute and percentage uncertainties
- Propagation of uncertainty in calculations
- Uncertainty reflected in final results
✅ Strong approach: Showing how uncertainty affects calculated values
Graphs are not just visuals — they are tools to extract relationships.
- Correct axis labels with units
- Appropriate scale and linearization (if needed)
- Error bars included
- Best-fit line or curve
This is where most students lose marks — describing is not enough.
- Explain trends using physics concepts
- Use numerical values (e.g. gradient, slope)
- Compare with theoretical expectations
✅ Strong: “The linear relationship suggests direct proportionality between force and acceleration, consistent with F = ma”
Listing data and plotting graphs is not analysis. Marks are awarded for explaining what the data means using physics.
Conclusion
The conclusion answers your research question using evidence from your data and links it directly to physics theory. This is not a summary — it is a justified scientific argument.
Start with a clear, explicit answer based on your results.
- State the relationship (e.g. proportional, inverse)
- Refer to your final graph or trend
- Avoid vague statements
High-scoring conclusions always include quantitative support.
- Include values such as gradients, slopes, or constants
- Quote uncertainties where relevant
- Reference specific data points
✅ Strong: “The gradient of 2.01 ± 0.05 confirms a direct proportionality between force and acceleration, consistent with F = ma”
Your conclusion must connect your findings to established physics principles.
- Reference relevant equations
- Explain how your results support or deviate from theory
- Use correct physics terminology
Briefly evaluate how trustworthy your results are.
- Comment on uncertainty size
- Discuss consistency of data
- State whether results are reliable
If your conclusion does not include numerical evidence, it cannot reach the top mark band — even if your experiment was correct.
Evaluation
The evaluation assesses your ability to think critically about your investigation. It is not about listing errors — it is about explaining how limitations affect your results and how they can be realistically improved.
Focus on specific, relevant limitations in your experiment.
- Measurement limitations (e.g. stopwatch reaction time)
- Environmental factors (e.g. temperature fluctuations)
- Apparatus constraints (e.g. resolution of instruments)
✅ Strong: “Manual timing introduces a reaction time uncertainty (~0.2 s), which affects the accuracy of period measurements”
Explain how each limitation influences your data and conclusions.
- Does it increase or decrease measured values?
- Does it affect precision or accuracy?
- Does it introduce systematic or random error?
✅ Strong: “Reaction time causes an overestimation of time measurements, leading to a higher calculated period”
Improvements must directly address the identified limitation.
- Use automated sensors instead of manual timing
- Increase number of trials to reduce random error
- Use higher precision instruments
✅ Strong: “Use a motion sensor to eliminate human reaction time and improve timing precision”
Top-band responses show a clear chain of reasoning:
Listing errors without explaining their impact will limit your score. Evaluation is about demonstrating scientific thinking, not identifying problems.
High-Scoring IA Questions
How does the length of a pendulum (0.2–1.0 m) affect its period under small-angle conditions (θ < 10°)?
✔ Allows linearization (T² ∝ L) | ✔ Strong theoretical link
How does temperature (20–80°C) affect the resistance of a copper wire under constant current conditions?
✔ Clear trend | ✔ Good uncertainty discussion | ✔ Real-world relevance
How does launch angle (10°–70°) affect the horizontal range of a projectile at constant initial velocity?
✔ Non-linear relationship | ✔ Strong analysis opportunity
- Clearly defined independent and dependent variables
- Includes measurement range (critical for IA)
- Based on IB syllabus concepts
- Allows strong data analysis (not just observation)
Your question should always follow: How does [IV] affect [DV] under controlled conditions?
How to Score a 7
- Choose a simple but analyzable experiment
- Focus on data quality
- Explain every step clearly
- Think like an examiner
Half your marks come from conclusion and evaluation — not the experiment.
Need IA Guidance?
Academic Integrity at Newtonine
Newtonine does not write Internal Assessments for students.
Instead, we provide structured mentorship — helping you refine your research question, improve your analysis, and develop the critical thinking required to produce your own high-quality IA.
- Topic selection and refinement
- Methodology feedback
- Data analysis guidance
- Evaluation improvement
This approach aligns with IB academic honesty guidelines and ensures that your work is authentic, ethical, and fully yours.