Physics

1. What makes Physics distinct?

A Physics EE must:

• focus on a clearly defined physical system, relationship or model

• investigate measurable physical variables or theoretical predictions

• use established physical principles such as mechanics, thermodynamics, electromagnetism or waves

• collect or analyse reliable data from experiments, simulations or secondary sources

• apply mathematical reasoning to explain results or trends

• use methods appropriate for controlled physical investigation

• evaluate precision, uncertainty and the validity of models

Your essay should feel physical, not chemical, mathematical or engineering based.

2. What counts as a suitable Physics topic?

A strong topic is:

• narrow and grounded in a specific physical law or relationship

• supported by variables that can be measured with available equipment

• framed using established physical theory

• feasible within school laboratory conditions

• able to generate clear quantitative data or legitimate simulations

Examples of suitable topic types

• motion and forces in simple mechanical systems

• harmonic or oscillatory behaviour

• electrical or magnetic field interactions

• energy transfer or thermal properties

• optics or wave phenomena

• modelling of physical systems using simulations

Examples of unsuitable topic types

• projects requiring equipment that is too advanced or unsafe

• theoretical topics with no clear way to generate or analyse data

• questions belonging to Engineering or Computer Science rather than Physics

• broad investigations with too many uncontrolled variables

• topics relying purely on qualitative observations

Physics requires quantifiable variables, mathematical reasoning and controlled investigation.

3. Using data in Physics

Your essay must draw upon physical data, such as:

• measurements of time, distance, force, voltage, current, temperature or frequency

• experimental results collected using appropriate sensors or apparatus

• data from simulations based on physical models

• reliable secondary datasets from published scientific research

Avoid

• data collected with imprecise or inappropriate tools

• values taken from unverified websites

• simulations that are used without understanding their algorithms

• datasets that do not allow mathematical interpretation

Evidence must be interpreted through physical principles and mathematical relationships.

4. Research methods appropriate for Physics

Your methods may include:

• controlled laboratory experiments isolating one variable

• kinematic or dynamic measurements

• thermal or electrical investigations

• use of sensors, data loggers or motion tracking tools

• modelling systems using spreadsheets, coding or simulations

• analysing published physical datasets

The method must suit the physical system or model you are investigating.

5. Expectations for analysis

Physics analysis should:

• process data using appropriate mathematical techniques

• include uncertainty analysis and propagation where relevant

• link results to physical laws or theoretical predictions

• explain discrepancies using accepted physical reasoning

• use graphs, equations and models purposefully

• remain tightly focused on the physical relationship defined in the research question

Analysis must move beyond description and show genuine physical understanding.

6. Evaluation in Physics

Evaluation may include:

• precision, calibration and limitations of equipment

• effects of systematic and random errors

• validity of assumptions in physical models

• sensitivity of results to changing variables

• extent to which data supports or contradicts theory

• practical limitations affecting the investigation’s reliability

A strong Physics EE explains what the findings mean and how confidently they can be interpreted.

7. Common pitfalls in Physics EEs

Avoid these issues, as they frequently lead to weak outcomes:

• topics that require unrealistic accuracy or specialised equipment

• insufficient data for meaningful mathematical analysis

• overly theoretical questions with no viable data source

• projects that drift into Engineering or pure Mathematics

• failure to analyse uncertainties

• experiments dominated by error rather than signal

• questions that are too broad to model or measure effectively

8. Model research questions

Here are high quality examples of Physics research questions:

1. How accurately can the simple harmonic motion model predict the behaviour of a loaded spring system?

2. To what extent does wire length influence the fundamental frequency of a stretched string?

3. How does changing blade angle affect the power output of a small scale wind turbine in controlled airflow?

4. How does surface texture influence the coefficient of friction between two solid materials?

5. To what extent can the inverse square law predict the intensity of light emitted from an LED source?

Each question is narrow, measurable and grounded in physical theory.