If you’re a high school student thinking about doing a research project, exploring quantitative STEM research can be a smart way to start. Instead of rushing to pick one topic, take some time to look at a range of ideas first. This helps you find something that truly matches your interests and the skills you want to build. 

Quantitative STEM research focuses on experimentation, analyzing data, and measurable results to answer questions. By exploring different ideas in this area, you can understand how data plays a role in science, technology, and everyday problem-solving. Whether you’re studying patterns in nature, analyzing environmental data, or designing a small experiment, this kind of research helps you think more logically and work more independently.

Why should I do quantitative STEM research in high school?

Doing quantitative STEM research in high school helps you build skills that go beyond the classroom. Completing an independent research project also shows that you can take initiative and manage long-term goals, which can make your academic profile stronger. Colleges and future employers often notice students who can work independently and apply classroom knowledge to real situations.

Research also helps you understand STEM concepts more deeply. You get experience in collecting and analyzing data, testing ideas, and learning from results. These are core parts of any scientific or technical field. Beyond school, doing research prepares you for future opportunities, whether it’s applying for a job, internship, or graduate program. 

With that, here are 20+ quantitative STEM research topics for high school students!

40 Quantitative STEM Research Topics for High School Students 

Environmental Science and Sustainability

1. For carbon sequestration, measure organic matter, pH, and microbial activity in sandy, clay, and loamy soils. Check for carbon storage over time and compare which soil type contains carbon most effectively.

2. Microplastic accumulation in freshwater organisms: Collect samples of small fish or invertebrates from local ponds. Analyze microplastic content using filtration and microscopy. Track bioaccumulation trends across the food chain and discuss potential ecological implications.

3. Measure the energy efficiency of solar panels at different angles, intensities, and temperatures. Identify optimal configurations for maximum efficiency.

4. Test water filtration systems with the filters you build: sand, charcoal, and cloth. Measure the efficiency of contaminant removal and evaluate which filter provides the cleanest result.

5. Analyze how urbanization affects local temperatures by comparing temperature and humidity values in urban and rural areas. Also see how green spaces contribute to the microclimate.

Physics and Engineering

6. Examine orbital mechanics. Build a small model by using pendulums to mimic planetary motion. You can calculate the force and compare it with existing theoretical predictions for review.

7. Investigate electrical resistance in a series vs. parallel circuit. First, measure values including current and voltage, then compare the calculated and observed resistance.

8. Heat capacity of liquids: Measure the capacity of liquids like water, oil, and alcohol under controlled conditions, compare the temperature changes, and calculate specific heat accordingly.

9. Study the strength of a magnetic field with coil turns and current: Build electromagnets with several coil counts. Measure using a Gauss meter. Test how the changes in current affect the intensity of the field and compare your results to theoretical predictions.

10. Test the period of a pendulum with varying mass and length: Record the time for multiple swings. Use simple harmonic motion equations to analyze the relationship between length, mass, and period.

Computer Science

11. Design a machine learning model to classify handwritten digits. Evaluate its accuracy and confusion matrices, and explore which techniques can improve performance.

12. Use network graphs to analyze the flow of traffic. Mark roads and intersections as nodes and edges. Calculate bottlenecks and suggest improvements.

13. Design a model to predict disease outbreaks by using environmental data. Collect historical data for temperature, humidity, and infections. Train the algorithms to forecast outbreaks, then compare those predictions to real events, and evaluate the strengths and weaknesses of your model. 

14. Study social media response during events to track sentiment trends. Use NLP to mark both positive and negative sentiment over a period of time.

15. Design a model for energy consumption in commercial buildings. Gather electricity data over a month, identify peak usage patterns, and then suggest energy-saving solutions by analyzing data.

16. Use motion tracking to analyze a sportsperson’s performance. Track athlete movements using video and sensor data. Calculate speed, acceleration, and efficiency.

17. Build a chatbot for any local application by using publicly available datasets. Test it for accuracy by logging domain-specific questions and verifying answers.

18. Use computer vision to count objects in images: Collect a dataset of natural or urban scenes. Train an algorithm for detection and evaluate its accuracy against real data.

19. Explore algorithmic bias: Take a dataset used in ML, run standard classifying tests, and compare the outcomes to identify bias.

Chemistry and Biochemistry

20. Analyze reaction rates with differing temperatures and concentrations. Use either a color change or a gas evolution reaction. Record the time taken for completion and determine the rate laws.

21. Test the solubility of salts using different solvents: Measure saturation points at different temperatures and review the differences observed.

22. Investigate the kinetics of enzymes by measuring reaction velocity at different substrate levels. Discuss how inhibitors affect reaction rates.

23. Compare multiple battery chemistries for lifespan. Test for lithium-ion, lead-acid, and nickel-metal hydride cells. Measure the voltage, capacity, and efficiency levels over repeated cycles. Analyze which combination performs best under given conditions.

24. Study molecular diffusion in liquids. For instance, track dye movement in water and glycerin. Calculate diffusion coefficients and compare results.

25. Investigate pH effects on bacterial growth. Grow cultures in media with different pH levels. Measure colony formation rates.

26. Design a model for chemical equilibria in solution reactions. Prepare reactions using different concentrations. Measure the equilibrium constants and compare the values to theoretical predictions.

27. Analyze how catalysts affect the rates of reaction. Use a common reaction like the decomposition of hydrogen peroxide. Measure time with and without catalysts and compare.

28. Test metals for varying corrosion rates in different solutions: Submerge the samples in salt, acid, and neutral solutions. Record weight loss over time. Compare results.

29. Investigate compounds for thermal decomposition. Heat the samples of organic or inorganic compounds. Measure weight change and gas evolution. Analyze results in the context of reactions.

30. Analyze how the heart rate fluctuates during exercise: Collect pulse or ECG data and quantify changes under different conditions.

Mathematics 

31. Monitor the growth of the population by using differential equations. Use logistic or exponential models. Compare predictions to records and evaluate model accuracy.

32. Use statistics to analyze voting patterns. Collect public election data, and apply correlation and regression to identify trends.

33. Study optimization problems in practical contexts: Minimize or maximize cost, distance, or resource allocation. Test solutions by designing algorithms.

34. Simulate the spread of disease using SIR or SEIR models. Set initial parameters based on historical outbreaks. Run the simulations and analyze how changes in parameters affect outcomes.

35. Model traffic congestion with queuing theory. Use arrival and service rates for intersections. Simulate wait times and suggest improvements to traffic flow.

36. Explore the role of probability in genetics. Model patterns of inheritance by using probability calculations. Compare predictions to records. 

37. Analyze patterns in environmental datasets: Use temperature, rainfall, or pollution data, identify correlations and trends using statistical methods.

38. Study bridges and beams to understand structural stress. Apply force and measure strain on a designed model. Compare experimental data to theoretical models and suggest improvements in design.

39. Use fractals to monitor the occurrence of natural phenomena: Investigate patterns in coastlines, clouds, or plants. Measure dimensions and compare with theoretical fractal dimensions.

40. Simulate global financial markets with quantitative models. Use either historical stock or commodity prices. Develop algorithms, compare model performance to real-world outcomes, and discuss limitations and potential improvements.

One other option—the Lumiere Research Scholar Program

If you’re interested in pursuing independent research, consider applying to one of the Lumiere Research Scholar Programs, selective online high school programs for students founded with researchers at Harvard and Oxford. Last year, we had over 4,000 students apply for 500 spots in the program! You can find the application form here, check out students’ reviews of the program here and here.

Also check out the Lumiere Research Inclusion Foundation, a non-profit research program for talented, low-income students. Last year, we had 150 students on full need-based financial aid!

Stephen is one of the founders of Lumiere and a Harvard College graduate. He founded Lumiere as a PhD student at Harvard Business School. Lumiere is a selective research program where students work 1-1 with a research mentor to develop an independent research paper.

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