The IB Physics IA criteria assess the quality of your scientific reasoning, not how advanced your topic appears. Under the course first assessed in 2025, the task is officially called the scientific investigation. It is marked out of 24, contributes 20% of the final Physics grade at SL and HL, and has a maximum overall word count of 3,000 words.
The mark scheme contains four equally weighted criteria: Research design, Data analysis, Conclusion, and Evaluation. Each is worth 6 marks. Your teacher marks the report before the IB externally moderates the school's marking.
IB Physics IA criteria at a glance
| Criterion | Marks | Main focus |
|---|---|---|
| Research design | 6 | Research question, scientific context, methodology, and reproducibility |
| Data analysis | 6 | Recording, processing, presentation, and uncertainty treatment |
| Conclusion | 6 | Answering the question and comparing results with accepted physics |
| Evaluation | 6 | Explaining limitations, their impact, and realistic improvements |
| Total | 24 | Overall quality of the scientific investigation |
The same criteria apply at SL and HL. Descriptors are organized into bands of 1-2, 3-4, and 5-6. Markers do not award one point for every item on an informal checklist; they select the descriptor that best represents the evidence across each criterion.
Criterion 1: Research design, 6 marks
Research design considers whether you created and communicated a suitable investigation. A strong design connects a focused research question to relevant physics and explains why the method will generate sufficient appropriate data.
| Mark band | Typical evidence |
|---|---|
| 1-2 | The question has little context, and the method cannot be reproduced reliably. |
| 3-4 | The question has broad context, with relevant methodological decisions and only some ambiguities. |
| 5-6 | The question has specific context, important decisions are explained, and the method is reproducible without guesswork. |
A strong research question normally identifies the independent and dependent variables, the physical system, measurable quantities, and the relationship or model being tested. “How does length affect a pendulum?” is measurable but underspecified. A better question is: “How does pendulum length from 0.20 m to 1.00 m affect the period of small-angle oscillations, and to what extent does the relationship agree with the accepted pendulum model?”
Background theory should explain the expected relationship rather than become a general textbook summary. Define equations, assumptions, and variables that directly influence your method or interpretation.
Top-band work also explains why the selected range, intervals, apparatus, repetitions, and control methods are appropriate. For each important control variable, state how it was controlled and why a change could affect the dependent variable.
There is no official rule requiring exactly five values or three repeats. Sufficiency depends on the expected pattern, instrument resolution, natural variation, and intended analysis. The guide to designing a science IA experiment can help you assess whether your plan will produce defensible evidence.
Include safety, ethical, and environmental considerations where genuinely relevant. A reproducible method should specify apparatus, settings, quantities, measurement definitions, and procedural steps without unnecessary narration.
Criterion 2: Data analysis, 6 marks
Data analysis assesses whether your recorded and processed evidence is relevant, accurate, clear, and precise. It also examines whether uncertainties have been treated appropriately.
| Mark band | Typical evidence |
|---|---|
| 1-2 | Recording or processing is unclear, with major errors and limited uncertainty treatment. |
| 3-4 | Communication is clear or precise but not consistently both, and some significant weaknesses remain. |
| 5-6 | Recording and processing are clear, precise, accurate, and sufficient to answer the question. |
“Clear” means the reader can follow the path from raw measurements to the final result. “Precise” means units, uncertainties, decimal places, graph labels, equations, and terminology are used consistently.
A strong analysis usually contains:
- raw-data tables with quantities, units, and measurement uncertainties;
- relevant qualitative observations;
- sample calculations that make processing traceable;
- processed results with appropriate significant figures;
- graphs with suitable scales, labels, fits, and meaningful error bars;
- interpretation of trends, anomalies, gradients, intercepts, or fitted parameters.
Uncertainty is not a decorative column added after the experiment. It should influence instrument selection, calculations, graphs, and the confidence of your conclusion. Appropriate treatment might involve instrument resolution, trial variation, propagated uncertainty, percentage uncertainty, or uncertainty in a fitted gradient.
Use the Physics IA data analysis guide and the explanation of absolute uncertainty in IB Physics for targeted support. Do not use a statistical technique simply because spreadsheet software provides it; every calculation should help answer the research question.
Criterion 3: Conclusion, 6 marks
The conclusion must answer the research question, remain consistent with the analysis, and compare the outcome with accepted scientific knowledge.
| Mark band | Typical evidence |
|---|---|
| 1-2 | A conclusion is stated but poorly supported, with superficial scientific comparison. |
| 3-4 | The conclusion is partly supported and includes some relevant comparison. |
| 5-6 | The conclusion is justified by the analysis, answers the question directly, and makes a traceable comparison with accepted physics. |
Begin with a quantitative answer. Refer to the result carrying your argument, such as a gradient, fitted constant, exponent, percentage difference, or correlation pattern, including uncertainty where relevant.
For a pendulum investigation, you might use the gradient of a graph of period squared against length to calculate an experimental value of gravitational field strength. Compare it with a cited accepted value and determine whether the values agree within uncertainty. Writing only that the graph “supports the theory” is insufficient.
The accepted scientific context may come from a textbook, course material, reliable database, or published source, but it must be traceable. Match the strength of your conclusion to the evidence. Noisy or limited data should produce a cautious claim rather than certainty.
Criterion 4: Evaluation, 6 marks
Evaluation examines whether you identify specific methodological weaknesses, explain their relative impact, and propose realistic improvements. The highest band requires prioritization and causal reasoning, not a long list of generic errors.
| Mark band | Typical evidence |
|---|---|
| 1-2 | Generic limitations and undeveloped improvements are stated. |
| 3-4 | Specific weaknesses and relevant improvements are described, but their effects are not fully explained. |
| 5-6 | Relative impacts are explained, and realistic improvements are developed and linked to each important limitation. |
Use the structure limitation, evidence, impact, improvement, expected benefit. Instead of writing “reaction time caused human error,” explain that manual timing introduced random variation comparable with the measured change, increasing scatter and weakening confidence in the gradient. Then propose a photogate, state where it would be positioned, and explain how automated timing would reduce that uncertainty.
Prioritize issues that could change the conclusion. Explain whether each issue increases random scatter, creates systematic bias, changes the gradient, shifts the intercept, or limits the range over which the conclusion is valid.
An extension is not a substitute for improving the original method. The IA evaluation guide provides a practical framework for developing criterion-relevant improvements.
Common misconceptions about the Physics IA mark scheme
Personal engagement and communication are no longer separate criteria. Resources using Personal engagement, Exploration, Analysis, Evaluation, and Communication describe the previous course. Clarity and independent decision-making still matter, but they are evidenced through the four current criteria.
A complicated topic does not automatically score highly. A simple mechanics investigation with justified decisions, careful uncertainty treatment, and critical evaluation can outperform an ambitious project producing unreliable data.
Perfect results are not required. Unexpected results can still support a high mark if you process them honestly, avoid removing anomalies without justification, and explain how they affect confidence in your conclusion.
Presentation has no separate mark allocation. Poor tables, graphs, or calculations can nevertheless prevent evidence from being understood in Research design or Data analysis. Decorative formatting cannot replace scientific content.
How to review your draft
Read your report four times, focusing on one criterion each time. For every top-band descriptor, identify the exact paragraph, table, graph, or calculation that provides evidence.
Ask:
- Research design: Have I justified how the method produces sufficient relevant data?
- Data analysis: Can every important result be traced to raw measurements?
- Conclusion: Does each major claim have quantitative support and scientific comparison?
- Evaluation: Have I prioritized limitations and linked each one to a workable improvement?
Use annotated Physics IA examples to examine the expected standard, but do not copy their wording. The Physics coursework guide and Physics IA Grader can help identify weak criteria before submission.
Conclusion
The IB Physics IA criteria reward a coherent scientific argument. Research design establishes a defensible method, Data analysis converts measurements into evidence, Conclusion answers the question, and Evaluation explains the investigation's limitations and improvements.
Explain decisions rather than merely stating them, and let uncertainty determine the strength of each claim. During final revision, use RevisionDojo's exemplars and rubric guidance, then apply the Coursework Grader or Jojo AI while keeping the submitted reasoning and writing your own.
Sources and referenced URLs
- Official IB Physics subject brief, first assessment 2025
- Official IB Physics curriculum update
- Official IB science professional development resources
- RevisionDojo Physics IA rubric explained
- RevisionDojo Physics IA tips
- Designing a science IA experiment
- Physics IA data analysis guide
- Absolute uncertainty guide
- IA evaluation guide
- Physics IA examples
- Physics coursework guide
- Physics IA Grader
- Coursework Grader