The Complete IB Physics Internal Assessment Guide (2025 Syllabus)

Stressing about how to achieve a Grade 7 in your upcoming IB Physics Internal Assessment? Don't worry! In this guide, I’ll tell you exactly what is needed, covering topic selection, research, and mark maximisation in each criterion.

Topic Selection

Contrary to what some may tell you, extreme amounts of ingenuity and overzealous creativity in choosing a topic WON’T earn you high marks in your Physics IA.

In fact, choosing a topic beyond your ability, means, or equipment, may sacrifice many marks in your data analysis, conclusion and evaluation (combined 18/24 of your marks). What the IB is looking for is an effective methodology to achieve your aim, and a detailed analysis of your results, both of which will be discussed later.

When looking for a topic, I recommend searching for prescribed practicals at university/college level physics courses, other high scoring Physics IAs (available at IB Solved), or interesting experiments you’ve seen conducted online.

This has multiple advantages – first, it lets you know that the experiment can be done with high school/undergraduate level materials. Second, it can provide a guide into constructing an effective methodology.

Another crucial factor to keep in mind when selecting a topic is the type of variables involved. Good-performing IAs almost always use continuous numerical independent and dependent variables. These are variables that can take on an infinite range of values within a given interval (for example, time, temperature, mass, length etc.)

AVOID, if possible, using categorical or discrete independent variables which are more limited in their range (e.g., colours, types, or counts).

Using continuous variables allows for more detailed data collection and more advanced data analysis techniques, such as linear regression, curve fitting, or calculating rates of change—tools that make your interpretation and evaluation of results much stronger. This directly contributes to higher marks in your data analysis, conclusion, and evaluation sections.

Main Takeaway – DON'T be too original in your topic selection. Go for something tried and tested.

Criterion A: Research Design (6 marks)

The entirety of the IA hinges on good research design so takes your time here to come up with a well-thought-out and robust your overall plan. Spend time researching to understand exactly what you want to investigate and how you’re going to collect meaningful data on it.

To attain full marks in this area, I recommend writing a small abstract at the beginning of your IA (the first thing the marker reads), detailing the independent and dependent variable, a brief overview of methodology, and your results.

Whilst it may feel strange writing your results on the first page, a scientific report isn’t a mystery novel! Your marker isn’t waiting to be surprised by the results at the end, they prefer to have everything laid out to them in the beginning, so they can follow your report easily. An abstract should be no longer than one paragraph of 3-4 lines.

Next is your introduction. This is the place to lay out any personal engagement details, along with the line of thought that led you to choose this topic.

At the end of your introduction, you should state your fully focused RESEARCH QUESTION. According to the IB:

“A research question with context should contain reference to the dependent and independent variables … include a concise description of the system in which the research question is embedded, and include background theory of direct relevance.”

A research question is usually best given in the format: “What is the relationship between (independent variable) and (dependent variable).” Followed by relevant contextualization for some of the key details for your experiment, which might include the independent variable range or the data collection method.

Following the introduction is your background information. This is where you build from the ground up – identify all physics laws, forces, equations, and theories of relevance to your IA. You may reference external sources for material that goes beyond your IA. At the end of this should be your hypothesis, which should logically follow from your background research.

Next, the central part of research design, your methodology section. Essential elements in methodology include:

• An apparatus list, with specific lengths, masses, or dimensions of equipment

• A precise methodology, which details everything you’ve done in your IA

• A photo of your experimental set up

• A labelled scientific diagram of your experimental set up

• An identification of variables, including the dependent, independent, and controlled variables

• A controlled variables table, which lists the variable, why it needs to be controlled, and how you’re controlling it.

YOUR METHOD SHOULD be detailed enough that someone else could replicate your experiment without needing to ask you questions. Make sure to clearly outline what you're doing, how you’re doing it, and why you’re doing it that way.

Your choice of data collection techniques also matters. You need to justify why those methods are appropriate for answering your question. Are you using measurements that are accurate and reliable? Have you considered how many trials are needed to account for variability?

Students should also consider constraints — like equipment limitations, ethical concerns, or environmental variables — and how they shaped the design. This kind of reflection helps demonstrate that your approach wasn’t just slapped together but carefully constructed.

This section is closely related to Tools 1 & 2 (Experimental Techniques & Technology), as well as Inquiry Process 1 (Exploring and Designing).

Main Takeaway – Essential elements within Research Design include an abstract, introduction, research question, background information, hypothesis, and methodology.

Criterion B: Data Analysis (6 marks)

This is perhaps the most important element of your IA. It is essential to have enough data to perform an effective analysis – you should have at the very least three trials (ideally five or more) for each increment of the independent variable, with at least five different increments (ideally seven or more) of your independent variable.

Of course, you DON'T have to show all these as usually it would take up far too much space in your IA. Instead show 1-2 sample results and analysis at different increments and clearly state that this process was repeated for other results.

Whilst the marking scheme indicates a need for both qualitative and quantitative analysis, a Physics IA should be more weighted towards quantitative analysis, with qualitative discussion limited to explaining any adjustments needing to be made to your analysis, or unexpected results.

The quantitative analysis should be at the heart of the IA and the investigation up until this point should be directed towards a plot comparing the independent variable (usually on the x-axis) and the dependent variable (usually on the y-axis). This will give you a clear idea of the relationship between these variables which should allow you to answer to your research question.

Depending on the investigation it can often be useful to plot this relationship in different ways to get a deeper understanding of the trends in the data, show your abilities in data manipulation and allow for a more in-depth answer to your research question.

Also, make sure to keep in mind the accuracy to which data must be recorded. This is usually determined by the configuration of your equipment. You must also consider human error – if you quote the result of a stopwatch to the closest millisecond with no error, you will almost certainly be penalised marks. This is where uncertainty analysis comes in.

A thorough uncertainty analysis can be the difference between a 4 and a 6 in this criterion. Almost every source of uncertainty should be discussed, even if they turn out to be negligible in your calculations (which you are free to write in your report). Examiners will be pleased if you’ve kept this in mind, as it indicates precise thought about each and every aspect of your experiment.

It is especially useful to keep in mind the propagation of uncertainties, and their rules for significant figures in uncertainties, which can be found at the beginning of any IB Physics textbook. Again, if there is not enough room to show all propagation calculations, show a sample calculation and indicate that the same method was used for other areas.

Uncertainties should always be indicated on graphs as error bars, even if they are negligible (write “uncertainties are indicated on graph but are negligible”), and lines of best and worst fit should be drawn.

Throughout this section it is also vital to keep the communication direct. All processes including recordings, data processing and graphing should be described clearly and precisely. Make sure to explain what you're doing for each step, how you’re doing it, and why doing it that way allows you to best answer your research question.

This section is closely related to Tools 2 & 3 (Technology & Mathematics) as well as Inquiry Process 2 (Collecting and Processing Data).

Main Takeaway – Your data analysis should have sufficient data, relevant graphical representations, and a thorough consideration and discussion of the origins and propagation of all uncertainties.

Criterion C: Conclusion (6 marks)

This section is where everything in your IA comes together. The data analysis has allowed you to see what your results tell you about the research question and here is your opportunity to give a direct answer. You should directly refer to the data you’ve collected and the analysis you’ve conducted to back this answer up.

This answer doesn’t need to be simple and can have nuance, but it should be directly related to the research question you have focused the IA on.

To achieve full marks here, your conclusion must be justified—that means it should flow logically and clearly from the data analysis you presented in the previous section.

You are NOT just stating what happened

You are explaining what it means in the scientific context.

You should explain all trends, relationships, and uncertainty ranges in your processed data and give interpretations of what this mean. Your conclusion should be fully consistent with your graphs, calculations, and error analysis.

It’s also important to ground your conclusion in the accepted scientific context. This means comparing your findings with those in published scientific literature, textbooks, or trustworthy online sources. This shows the examiner that you understand where your findings fit within broader physics principles. Make sure all sources are clearly cited, and all variables are clearly described.

In doing this, you should also be comparing the conclusion to the hypothesis and stating whether your data aligns with what you had predicted.

This section is closely related to Tool 1 (Experimental Techniques) as well as Inquiry Process 3 (Concluding and Evaluating).

Main Takeaway – Your conclusion must be justified with reference to your analysis, aligned with accepted scientific context and compared to your hypothesis.

Criterion D: Evaluation (6 marks)

Your evaluation mark is closely related to your conclusion mark. If you have discussed the origins and propagation of uncertainties throughout the analysis of results, you will already be scoring highly in this area.

To finish and secure maximum marks, your evaluation should identify the strengths and limitations of your method. reiterate the sources of error and distinguish between random error and systematic error, with an acknowledgement of how each may be eliminated or minimised through methodological adaptation or increased trials. 

Be honest and specific …

DON’T just say “human error.”

INSTEAD, identify where uncertainties arose (e.g., delay in starting/stopping a stopwatch), their likely impact on your results, and how you might reduce them in future experiments.

Also discuss how these errors would have affected the result, particularly for systematic error where you should always identify whether they would have INCREASED OR DECREASED any final calculated values or which way they would have shifted trendlines.

Where possible, suggest realistic improvements.

AVOID generic suggestions like “use better equipment.”

INSTEAD, specify what equipment and how it would improve your results (e.g., using a motion sensor instead of a stopwatch to reduce the delay between the event and the time recording). Also reflect on whether your method tested the relationship in the most effective way possible. Could an alternative setup have offered more reliable results, or a wider range of data?

More advanced students may want to discuss the distribution of error, and whether it follows an approximately normal distribution or if it is skewed towards the centre or to either tail, however this would be an optional extension rather than a necessity.

You should also discuss the validity of your experiment, which is determined by how well you controlled your variables. In other words, you need to show that any changes in your dependent variable were solely caused by changes in the independent variable, solidifying the causal link between the two.

A discussion of accuracy should also be included; however, this should be much shorter than the discussion of validity.

Following this, you should discuss any possible changes or extensions to your methodology. These should not be too ambitious (using a high-powered microscope to measure the distance travelled by a projectile), but be informed by what you found problematic or difficult in conducting your IA.

Most importantly...

DON'T pretend that everything was perfect the first time around

It certainly wasn’t for me, and rarely ever is. Rather, discuss the difficulties you had and what you would do to overcome them in the future. These are often related to your sources of error and should therefore be separated into improvements targeting random or systematic sources of error.

This section is closely related to Tool 1 (Experimental Techniques) as well as Inquiry Process 3 (Concluding and Evaluating).

Main Takeaway – Once again, be conscious of errors and uncertainties, explore the validity and accuracy of your results, and target realistic improvements related to your sources of random and systematic error.

And that's it! From here, you should be well-equipped to begin your Physics Internal Assessment. But if you're still scratching your head, wondering if there are any examples you can follow to achieve a high mark, make sure to check out our perfect 24/24 IB Physics IA Example.

Or even better, click below to work with one of our expert IB Physics tutors who can guide you personally through the complete process of achieving top marks in your own Physics IA!

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