non experimental research topics for stem students quantitative

Best 151+ Quantitative Research Topics for STEM Students

In today’s rapidly evolving world, STEM (Science, Technology, Engineering, and Mathematics) fields have gained immense significance. For STEM students, engaging in quantitative research is a pivotal aspect of their academic journey. Quantitative research involves the systematic collection and interpretation of numerical data to address research questions or test hypotheses. Choosing the right research topic is essential to ensure a successful and meaningful research endeavor. 

In this blog, we will explore 151+ quantitative research topics for STEM students. Whether you are an aspiring scientist, engineer, or mathematician, this comprehensive list will inspire your research journey. But we understand that the journey through STEM education and research can be challenging at times. That’s why we’re here to support you every step of the way with our Engineering Assignment Help service. 

What is Quantitative Research in STEM?

Table of Contents

Quantitative research is a scientific approach that relies on numerical data and statistical analysis to draw conclusions and make predictions. In STEM fields, quantitative research encompasses a wide range of methodologies, including experiments, surveys, and data analysis. The key characteristics of quantitative research in STEM include:

• Data Collection: Systematic gathering of numerical data through experiments, observations, or surveys.
• Statistical Analysis: Application of statistical techniques to analyze data and draw meaningful conclusions.
• Hypothesis Testing: Testing hypotheses and theories using quantitative data.
• Replicability: The ability to replicate experiments and obtain consistent results.
• Generalizability: Drawing conclusions that can be applied to larger populations or phenomena.

Importance of Quantitative Research Topics for STEM Students

Quantitative research plays a pivotal role in STEM education and research for several reasons:

1. Empirical Evidence

It provides empirical evidence to support or refute scientific theories and hypotheses.

2. Data-Driven Decision-Making

STEM professionals use quantitative research to make informed decisions, from designing experiments to developing new technologies.

3. Innovation

It fuels innovation by providing data-driven insights that lead to the creation of new products, processes, and technologies.

4. Problem Solving

STEM students learn critical problem-solving skills through quantitative research, which are invaluable in their future careers.

5. Interdisciplinary Applications 

Quantitative research transcends STEM disciplines, facilitating collaboration and the tackling of complex, real-world problems.

Also Read: Google Scholar Research Topics

Quantitative Research Topics for STEM Students

Now, let’s explore important quantitative research topics for STEM students:

Biology and Life Sciences

Here are some quantitative research topics in biology and life science:

1. The impact of climate change on biodiversity.

2. Analyzing the genetic basis of disease susceptibility.

3. Studying the effectiveness of vaccines in preventing infectious diseases.

4. Investigating the ecological consequences of invasive species.

5. Examining the role of genetics in aging.

6. Analyzing the effects of pollution on aquatic ecosystems.

7. Studying the evolution of antibiotic resistance.

8. Investigating the relationship between diet and lifespan.

9. Analyzing the impact of deforestation on wildlife.

10. Studying the genetics of cancer development.

11. Investigating the effectiveness of various plant fertilizers.

12. Analyzing the impact of microplastics on marine life.

13. Studying the genetics of human behavior.

14. Investigating the effects of pollution on plant growth.

15. Analyzing the microbiome’s role in human health.

16. Studying the impact of climate change on crop yields.

17. Investigating the genetics of rare diseases.

Let’s get started with some quantitative research topics for stem students in chemistry:

1. Studying the properties of superconductors at different temperatures.

2. Analyzing the efficiency of various catalysts in chemical reactions.

3. Investigating the synthesis of novel polymers with unique properties.

4. Studying the kinetics of chemical reactions.

5. Analyzing the environmental impact of chemical waste disposal.

6. Investigating the properties of nanomaterials for drug delivery.

7. Studying the behavior of nanoparticles in different solvents.

8. Analyzing the use of renewable energy sources in chemical processes.

9. Investigating the chemistry of atmospheric pollutants.

10. Studying the properties of graphene for electronic applications.

11. Analyzing the use of enzymes in industrial processes.

12. Investigating the chemistry of alternative fuels.

13. Studying the synthesis of pharmaceutical compounds.

14. Analyzing the properties of materials for battery technology.

15. Investigating the chemistry of natural products for drug discovery.

16. Analyzing the effects of chemical additives on food preservation.

17. Investigating the chemistry of carbon capture and utilization technologies.

Here are some quantitative research topics in physics for stem students:

1. Investigating the behavior of subatomic particles in high-energy collisions.

2. Analyzing the properties of dark matter and dark energy.

3. Studying the quantum properties of entangled particles.

4. Investigating the dynamics of black holes and their gravitational effects.

5. Analyzing the behavior of light in different mediums.

6. Studying the properties of superfluids at low temperatures.

7. Investigating the physics of renewable energy sources like solar cells.

8. Analyzing the properties of materials at extreme temperatures and pressures.

9. Studying the behavior of electromagnetic waves in various applications.

10. Investigating the physics of quantum computing.

11. Analyzing the properties of magnetic materials for data storage.

12. Studying the behavior of particles in plasma for fusion energy research.

13. Investigating the physics of nanoscale materials and devices.

14. Analyzing the properties of materials for use in semiconductors.

15. Studying the principles of thermodynamics in energy efficiency.

16. Investigating the physics of gravitational waves.

17. Analyzing the properties of materials for use in quantum technologies.

Engineering

Let’s explore some quantitative research topics for stem students in engineering: 

1. Investigating the efficiency of renewable energy systems in urban environments.

2. Analyzing the impact of 3D printing on manufacturing processes.

3. Studying the structural integrity of materials in aerospace engineering.

4. Investigating the use of artificial intelligence in autonomous vehicles.

5. Analyzing the efficiency of water treatment processes in civil engineering.

6. Studying the impact of robotics in healthcare.

7. Investigating the optimization of supply chain logistics using quantitative methods.

8. Analyzing the energy efficiency of smart buildings.

9. Studying the effects of vibration on structural engineering.

10. Investigating the use of drones in agricultural practices.

11. Analyzing the impact of machine learning in predictive maintenance.

12. Studying the optimization of transportation networks.

13. Investigating the use of nanomaterials in electronic devices.

14. Analyzing the efficiency of renewable energy storage systems.

15. Studying the impact of AI-driven design in architecture.

16. Investigating the optimization of manufacturing processes using Industry 4.0 technologies.

17. Analyzing the use of robotics in underwater exploration.

Environmental Science

Here are some top quantitative research topics in environmental science for students:

1. Investigating the effects of air pollution on respiratory health.

2. Analyzing the impact of deforestation on climate change.

3. Studying the biodiversity of coral reefs and their conservation.

4. Investigating the use of remote sensing in monitoring deforestation.

5. Analyzing the effects of plastic pollution on marine ecosystems.

6. Studying the impact of climate change on glacier retreat.

7. Investigating the use of wetlands for water quality improvement.

8. Analyzing the effects of urbanization on local microclimates.

9. Studying the impact of oil spills on aquatic ecosystems.

10. Investigating the use of renewable energy in mitigating greenhouse gas emissions.

11. Analyzing the effects of soil erosion on agricultural productivity.

12. Studying the impact of invasive species on native ecosystems.

13. Investigating the use of bioremediation for soil cleanup.

14. Analyzing the effects of climate change on migratory bird patterns.

15. Studying the impact of land use changes on water resources.

16. Investigating the use of green infrastructure for urban stormwater management.

17. Analyzing the effects of noise pollution on wildlife behavior.

Computer Science

Let’s get started with some simple quantitative research topics for stem students:

1. Investigating the efficiency of machine learning algorithms for image recognition.

2. Analyzing the security of blockchain technology in financial transactions.

3. Studying the impact of quantum computing on cryptography.

4. Investigating the use of natural language processing in chatbots and virtual assistants.

5. Analyzing the effectiveness of cybersecurity measures in protecting sensitive data.

6. Studying the impact of algorithmic trading in financial markets.

7. Investigating the use of deep learning in autonomous robotics.

8. Analyzing the efficiency of data compression algorithms for large datasets.

9. Studying the impact of virtual reality in medical simulations.

10. Investigating the use of artificial intelligence in personalized medicine.

11. Analyzing the effectiveness of recommendation systems in e-commerce.

12. Studying the impact of cloud computing on data storage and processing.

13. Investigating the use of neural networks in predicting disease outbreaks.

14. Analyzing the efficiency of data mining techniques in customer behavior analysis.

15. Studying the impact of social media algorithms on user behavior.

16. Investigating the use of machine learning in natural language translation.

17. Analyzing the effectiveness of sentiment analysis in social media monitoring.

Mathematics

Let’s explore the quantitative research topics in mathematics for students:

1. Investigating the properties of prime numbers and their distribution.

2. Analyzing the behavior of chaotic systems using differential equations.

3. Studying the optimization of algorithms for solving complex mathematical problems.

4. Investigating the use of graph theory in network analysis.

5. Analyzing the properties of fractals in natural phenomena.

6. Studying the application of probability theory in risk assessment.

7. Investigating the use of numerical methods in solving partial differential equations.

8. Analyzing the properties of mathematical models for population dynamics.

9. Studying the optimization of algorithms for data compression.

10. Investigating the use of topology in data analysis.

11. Analyzing the behavior of mathematical models in financial markets.

12. Studying the application of game theory in strategic decision-making.

13. Investigating the use of mathematical modeling in epidemiology.

14. Analyzing the properties of algebraic structures in coding theory.

15. Studying the optimization of algorithms for image processing.

16. Investigating the use of number theory in cryptography.

17. Analyzing the behavior of mathematical models in climate prediction.

Earth Sciences

Here are some quantitative research topics for stem students in earth science:

1. Investigating the impact of volcanic eruptions on climate patterns.

2. Analyzing the behavior of earthquakes along tectonic plate boundaries.

3. Studying the geomorphology of river systems and erosion.

4. Investigating the use of remote sensing in monitoring wildfires.

5. Analyzing the effects of glacier melt on sea-level rise.

6. Studying the impact of ocean currents on weather patterns.

7. Investigating the use of geothermal energy in renewable power generation.

8. Analyzing the behavior of tsunamis and their destructive potential.

9. Studying the impact of soil erosion on agricultural productivity.

10. Investigating the use of geological data in mineral resource exploration.

11. Analyzing the effects of climate change on coastal erosion.

12. Studying the geomagnetic field and its role in navigation.

13. Investigating the use of radar technology in weather forecasting.

14. Analyzing the behavior of landslides and their triggers.

15. Studying the impact of groundwater depletion on aquifer systems.

16. Investigating the use of GIS (Geographic Information Systems) in land-use planning.

17. Analyzing the effects of urbanization on heat island formation.

Health Sciences and Medicine

Here are some quantitative research topics for stem students in health science and medicine:

1. Investigating the effectiveness of telemedicine in improving healthcare access.

2. Analyzing the impact of personalized medicine in cancer treatment.

3. Studying the epidemiology of infectious diseases and their spread.

4. Investigating the use of wearable devices in monitoring patient health.

5. Analyzing the effects of nutrition and exercise on metabolic health.

6. Studying the impact of genetics in predicting disease susceptibility.

7. Investigating the use of artificial intelligence in medical diagnosis.

8. Analyzing the behavior of pharmaceutical drugs in clinical trials.

9. Studying the effectiveness of mental health interventions in schools.

10. Investigating the use of gene editing technologies in treating genetic disorders.

11. Analyzing the properties of medical imaging techniques for early disease detection.

12. Studying the impact of vaccination campaigns on public health.

13. Investigating the use of regenerative medicine in tissue repair.

14. Analyzing the behavior of pathogens in antimicrobial resistance.

15. Studying the epidemiology of chronic diseases like diabetes and heart disease.

16. Investigating the use of bioinformatics in genomics research.

17. Analyzing the effects of environmental factors on health outcomes.

Quantitative research is the backbone of STEM fields, providing the tools and methodologies needed to explore, understand, and innovate in the world of science and technology . As STEM students, embracing quantitative research not only enhances your analytical skills but also equips you to address complex real-world challenges. With the extensive list of 155+ quantitative research topics for stem students provided in this blog, you have a starting point for your own STEM research journey. Whether you’re interested in biology, chemistry, physics, engineering, or any other STEM discipline, there’s a wealth of quantitative research topics waiting to be explored. So, roll up your sleeves, grab your lab coat or laptop, and embark on your quest for knowledge and discovery in the exciting world of STEM.

I hope you enjoyed this blog post about quantitative research topics for stem students.

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189+ Good Quantitative Research Topics For STEM Students

Quantitative research is an essential part of STEM (Science, Technology, Engineering, and Mathematics) fields. It involves collecting and analyzing numerical data to answer research questions and test hypotheses. 

In 2023, STEM students have a wealth of exciting research opportunities in various disciplines. Whether you’re an undergraduate or graduate student, here are quantitative research topics to consider for your next project.

If you are looking for the best list of quantitative research topics for stem students, then you can check the given list in each field. It offers STEM students numerous opportunities to explore and contribute to their respective fields in 2023 and beyond. 

Whether you’re interested in astrophysics, biology, engineering, mathematics, or any other STEM field.

Also Read: Most Exciting Qualitative Research Topics For Students

What Is Quantitative Research

Table of Contents

Quantitative research is a type of research that focuses on the organized collection, analysis, and evaluation of numerical data to answer research questions, test theories, and find trends or connections between factors. It is an organized, objective way to do study that uses measurable data and scientific methods to come to results.

Quantitative research is often used in many areas, such as the natural sciences, social sciences, economics, psychology, education, and market research. It gives useful information about patterns, trends, cause-and-effect relationships, and how often things happen. Quantitative tools are used by researchers to answer questions like “How many?” and “How often?” “Is there a significant difference?” or “What is the relationship between the variables?”

In comparison to quantitative research, qualitative research uses non-numerical data like conversations, notes, and open-ended surveys to understand and explore the ideas, experiences, and points of view of people or groups. Researchers often choose between quantitative and qualitative methods based on their research goals, questions, and the type of thing they are studying.

How To Choose Quantitative Research Topics For STEM

Here’s a step-by-step guide on how to choose quantitative research topics for STEM:

Step 1:- Identify Your Interests and Passions

Start by reflecting on your personal interests within STEM. What areas or subjects in STEM excite you the most? Choosing a topic you’re passionate about will keep you motivated throughout the research process.

Step 2:- Review Coursework and Textbooks

Look through your coursework, textbooks, and class notes. Identify concepts, theories, or areas that you found particularly intriguing or challenging. These can be a source of potential research topics.

Step 3:- Consult with Professors and Advisors

Discuss your research interests with professors, academic advisors, or mentors. They can provide valuable insights, suggest relevant topics, and guide you toward areas with research opportunities.

Step 4:- Read Recent Literature

Explore recent research articles, journals, and publications in STEM fields. This will help you identify current trends, gaps in knowledge, and areas where further research is needed.

Step 5:- Narrow Down Your Focus

Once you have a broad area of interest, narrow it down to a specific research focus. Consider questions like:

• What specific problem or phenomenon do you want to investigate?
• Are there unanswered questions or controversies in this area?
• What impact could your research have on the field or society?

Step 6:- Consider Resources and Access

Assess the resources available to you, including access to laboratories, equipment, databases, and funding. Ensure that your chosen topic aligns with the resources you have or can access.

Step 7:- Think About Practicality

Consider the feasibility of conducting research on your chosen topic. Are the data readily available, or will you need to collect data yourself? Can you complete the research within your available time frame?

Step 8:- Define Your Research Question

Formulate a clear and specific research question or hypothesis. Your research question should guide your entire study and provide a focus for your data collection and analysis.

Step 9:- Conduct a Literature Review

Dive deeper into the existing literature related to your chosen topic. This will help you understand the current state of research, identify gaps, and refine your research question.

Step 10:- Consider the Impact

Think about the potential impact of your research. How does your topic contribute to the advancement of knowledge in your field? Does it have practical applications or implications for society?

Step 11:- Brainstorm Research Methods

Determine the quantitative research methods and data collection techniques you plan to use. Consider whether you’ll conduct experiments, surveys, data analysis, simulations, or use existing datasets.

Step 12:- Seek Feedback

Share your research topic and ideas with peers, advisors, or mentors. They can provide valuable feedback and help you refine your research focus.

Step 13:- Assess Ethical Considerations

Consider ethical implications related to your research, especially if it involves human subjects, sensitive data, or potential environmental impacts. Ensure that your research adheres to ethical guidelines.

Step 14:- Finalize Your Research Topic

Once you’ve gone through these steps, finalize your research topic. Write a clear and concise research proposal that outlines your research question, objectives, methods, and expected outcomes.

Step 15:- Stay Open to Adjustments

Be open to adjusting your research topic as you progress. Sometimes, new insights or challenges may lead you to refine or adapt your research focus.

Following are the most interesting quantitative research topics for stem students. These are given below.

Quantitative Research Topics In Physics and Astronomy

• Quantum Computing Algorithms : Investigate new algorithms for quantum computers and their potential applications.
• Dark Matter Detection Methods : Explore innovative approaches to detect dark matter particles.
• Quantum Teleportation : Study the principles and applications of quantum teleportation.
• Exoplanet Characterization : Analyze data from telescopes to characterize exoplanets.
• Nuclear Fusion Modeling : Create mathematical models for nuclear fusion reactions.
• Superconductivity at High Temperatures : Research the properties and applications of high-temperature superconductors.
• Gravitational Wave Analysis : Analyze gravitational wave data to study astrophysical phenomena.
• Black Hole Thermodynamics : Investigate the thermodynamics of black holes and their entropy.

Quantitative Research Topics In Biology and Life Sciences

• Genome-Wide Association Studies (GWAS) : Conduct GWAS to identify genetic factors associated with diseases.
• Pharmacokinetics and Pharmacodynamics : Study drug interactions in the human body.
• Ecological Modeling : Model ecosystems to understand population dynamics.
• Protein Folding : Research the kinetics and thermodynamics of protein folding.
• Cancer Epidemiology : Analyze cancer incidence and risk factors in specific populations.
• Neuroimaging Analysis : Develop algorithms for analyzing brain imaging data.
• Evolutionary Genetics : Investigate evolutionary patterns using genetic data.
• Stem Cell Differentiation : Study the factors influencing stem cell differentiation.

Engineering and Technology Quantitative Research Topics

• Renewable Energy Efficiency : Optimize the efficiency of solar panels or wind turbines.
• Aerodynamics of Drones : Analyze the aerodynamics of drone designs.
• Autonomous Vehicle Safety : Evaluate safety measures for autonomous vehicles.
• Machine Learning in Robotics : Implement machine learning algorithms for robot control.
• Blockchain Scalability : Research methods to scale blockchain technology.
• Quantum Computing Hardware : Design and test quantum computing hardware components.
• IoT Security : Develop security protocols for the Internet of Things (IoT).
• 3D Printing Materials Analysis : Study the mechanical properties of 3D-printed materials.

Quantitative Research Topics In Mathematics and Statistics

Following are the best Quantitative Research Topics For STEM Students in mathematics and statistics.

• Prime Number Distribution : Investigate the distribution of prime numbers.
• Graph Theory Algorithms : Develop algorithms for solving graph theory problems.
• Statistical Analysis of Financial Markets : Analyze financial data and market trends.
• Number Theory Research : Explore unsolved problems in number theory.
• Bayesian Machine Learning : Apply Bayesian methods to machine learning models.
• Random Matrix Theory : Study the properties of random matrices in mathematics and physics.
• Topological Data Analysis : Use topology to analyze complex data sets.
• Quantum Algorithms for Optimization : Research quantum algorithms for optimization problems.

Experimental Quantitative Research Topics In Science and Earth Sciences

• Climate Change Modeling : Develop climate models to predict future trends.
• Biodiversity Conservation Analysis : Analyze data to support biodiversity conservation efforts.
• Geographic Information Systems (GIS) : Apply GIS techniques to solve environmental problems.
• Oceanography and Remote Sensing : Use satellite data for oceanographic research.
• Air Quality Monitoring : Develop sensors and models for air quality assessment.
• Hydrological Modeling : Study the movement and distribution of water resources.
• Volcanic Activity Prediction : Predict volcanic eruptions using quantitative methods.
• Seismology Data Analysis : Analyze seismic data to understand earthquake patterns.

Chemistry and Materials Science Quantitative Research Topics

• Nanomaterial Synthesis and Characterization : Research the synthesis and properties of nanomaterials.
• Chemoinformatics : Analyze chemical data for drug discovery and materials science.
• Quantum Chemistry Simulations : Perform quantum simulations of chemical reactions.
• Materials for Renewable Energy : Investigate materials for energy storage and conversion.
• Catalysis Kinetics : Study the kinetics of chemical reactions catalyzed by materials.
• Polymer Chemistry : Research the properties and applications of polymers.
• Analytical Chemistry Techniques : Develop new analytical techniques for chemical analysis.
• Sustainable Chemistry : Explore green chemistry approaches for sustainable materials.

Computer Science and Information Technology Topics

• Natural Language Processing (NLP) : Work on NLP algorithms for language understanding.
• Cybersecurity Analytics : Analyze cybersecurity threats and vulnerabilities.
• Big Data Analytics : Apply quantitative methods to analyze large data sets.
• Machine Learning Fairness : Investigate bias and fairness issues in machine learning models.
• Human-Computer Interaction (HCI) : Study user behavior and interaction patterns.
• Software Performance Optimization : Optimize software applications for performance.
• Distributed Systems Analysis : Analyze the performance of distributed computing systems.
• Bioinformatics Data Mining : Develop algorithms for mining biological data.

Good Quantitative Research Topics Students In Medicine and Healthcare

• Clinical Trial Data Analysis : Analyze clinical trial data to evaluate treatment effectiveness.
• Epidemiological Modeling : Model disease spread and intervention strategies.
• Healthcare Data Analytics : Analyze healthcare data for patient outcomes and cost reduction.
• Medical Imaging Algorithms : Develop algorithms for medical image analysis.
• Genomic Medicine : Apply genomics to personalized medicine approaches.
• Telemedicine Effectiveness : Study the effectiveness of telemedicine in healthcare delivery.
• Health Informatics : Analyze electronic health records for insights into patient care.

Agriculture and Food Sciences Topics

• Precision Agriculture : Use quantitative methods for optimizing crop production.
• Food Safety Analysis : Analyze food safety data and quality control.
• Aquaculture Sustainability : Research sustainable practices in aquaculture.
• Crop Disease Modeling : Model the spread of diseases in agricultural crops.
• Climate-Resilient Agriculture : Develop strategies for agriculture in changing climates.
• Food Supply Chain Optimization : Optimize food supply chain logistics.
• Soil Health Assessment : Analyze soil data for sustainable land management.

Social Sciences with Quantitative Approaches

• Educational Data Mining : Analyze educational data for improving learning outcomes.
• Sociodemographic Surveys : Study social trends and demographics using surveys.
• Psychometrics : Develop and validate psychological measurement instruments.
• Political Polling Analysis : Analyze political polling data and election trends.
• Economic Modeling : Develop economic models for policy analysis.
• Urban Planning Analytics : Analyze data for urban planning and infrastructure.
• Climate Policy Evaluation : Evaluate the impact of climate policies on society.

Environmental Engineering Quantitative Research Topics

• Water Quality Assessment : Analyze water quality data for environmental monitoring.
• Waste Management Optimization : Optimize waste collection and recycling programs.
• Environmental Impact Assessments : Evaluate the environmental impact of projects.
• Air Pollution Modeling : Model the dispersion of air pollutants in urban areas.
• Sustainable Building Design : Apply quantitative methods to sustainable architecture.

Quantitative Research Topics Robotics and Automation

• Robotic Swarm Behavior : Study the behavior of robot swarms in different tasks.
• Autonomous Drone Navigation : Develop algorithms for autonomous drone navigation.
• Humanoid Robot Control : Implement control algorithms for humanoid robots.
• Robotic Grasping and Manipulation : Study robotic manipulation techniques.
• Reinforcement Learning for Robotics : Apply reinforcement learning to robotic control.

Quantitative Research Topics Materials Engineering

• Additive Manufacturing Process Optimization : Optimize 3D printing processes.
• Smart Materials for Aerospace : Research smart materials for aerospace applications.
• Nanostructured Materials for Energy Storage : Investigate energy storage materials.
• Corrosion Prevention : Develop corrosion-resistant materials and coatings.

Nuclear Engineering Quantitative Research Topics

• Nuclear Reactor Safety Analysis : Study safety aspects of nuclear reactor designs.
• Nuclear Fuel Cycle Analysis : Analyze the nuclear fuel cycle for efficiency.
• Radiation Shielding Materials : Research materials for radiation protection.

Quantitative Research Topics In Biomedical Engineering

• Medical Device Design and Testing : Develop and test medical devices.
• Biomechanics Analysis : Analyze biomechanics in sports or rehabilitation.
• Biomaterials for Medical Implants : Investigate materials for medical implants.

Good Quantitative Research Topics Chemical Engineering

• Chemical Process Optimization : Optimize chemical manufacturing processes.
• Industrial Pollution Control : Develop strategies for pollution control in industries.
• Chemical Reaction Kinetics : Study the kinetics of chemical reactions in industries.

Best Quantitative Research Topics In Renewable Energy

• Energy Storage Systems : Research and optimize energy storage solutions.
• Solar Cell Efficiency : Improve the efficiency of photovoltaic cells.
• Wind Turbine Performance Analysis : Analyze and optimize wind turbine designs.

Brilliant Quantitative Research Topics In Astronomy and Space Sciences

• Astrophysical Simulations : Simulate astrophysical phenomena using numerical methods.
• Spacecraft Trajectory Optimization : Optimize spacecraft trajectories for missions.
• Exoplanet Detection Algorithms : Develop algorithms for exoplanet detection.

Quantitative Research Topics In Psychology and Cognitive Science

• Cognitive Psychology Experiments : Conduct quantitative experiments in cognitive psychology.
• Emotion Recognition Algorithms : Develop algorithms for emotion recognition in AI.
• Neuropsychological Assessments : Create quantitative assessments for brain function.

Geology and Geological Engineering Quantitative Research Topics

• Geological Data Analysis : Analyze geological data for mineral exploration.
• Geological Hazard Prediction : Predict geological hazards using quantitative models.

Top Quantitative Research Topics In Forensic Science

• Forensic Data Analysis : Analyze forensic evidence using quantitative methods.
• Crime Pattern Analysis : Study crime patterns and trends in urban areas.

Great Quantitative Research Topics In Cybersecurity

• Network Intrusion Detection : Develop quantitative methods for intrusion detection.
• Cryptocurrency Analysis : Analyze blockchain data and cryptocurrency trends.

Mathematical Biology Quantitative Research Topics

• Epidemiological Modeling : Model disease spread and control in populations.
• Population Genetics : Analyze genetic data to understand population dynamics.

Quantitative Research Topics In Chemical Analysis

• Analytical Chemistry Methods : Develop quantitative methods for chemical analysis.
• Spectroscopy Analysis : Analyze spectroscopic data for chemical identification.

Mathematics Education Quantitative Research Topics

• Mathematics Curriculum Analysis : Analyze curriculum effectiveness in mathematics education.
• Mathematics Assessment Development : Develop quantitative assessments for mathematics skills.

Quantitative Research Topics In Social Research

• Social Network Analysis : Analyze social network structures and dynamics.
• Survey Research : Conduct quantitative surveys on social issues and trends.

Quantitative Research Topics In Computational Neuroscience

• Neural Network Modeling : Model neural networks and brain functions computationally.
• Brain Connectivity Analysis : Analyze functional and structural brain connectivity.

Best Topics In Transportation Engineering

• Traffic Flow Modeling : Model and optimize traffic flow in urban areas.
• Public Transportation Efficiency : Analyze the efficiency of public transportation systems.

Good Quantitative Research Topics In Energy Economics

• Energy Policy Analysis : Evaluate the economic impact of energy policies.
• Renewable Energy Cost-Benefit Analysis : Assess the economic viability of renewable energy projects.

Quantum Information Science

• Quantum Cryptography Protocols : Develop and analyze quantum cryptography protocols.
• Quantum Key Distribution : Study the security of quantum key distribution systems.

Human Genetics

• Genome Editing Ethics : Investigate ethical issues in genome editing technologies.
• Population Genomics : Analyze genomic data for population genetics research.

Marine Biology

• Coral Reef Health Assessment : Quantitatively assess the health of coral reefs.
• Marine Ecosystem Modeling : Model marine ecosystems and biodiversity.

Data Science and Machine Learning

• Machine Learning Explainability : Develop methods for explaining machine learning models.
• Data Privacy in Machine Learning : Study privacy issues in machine learning applications.
• Deep Learning for Image Analysis : Develop deep learning models for image recognition.

Environmental Engineering

Robotics and automation, materials engineering, nuclear engineering, biomedical engineering, chemical engineering, renewable energy, astronomy and space sciences, psychology and cognitive science, geology and geological engineering, forensic science, cybersecurity, mathematical biology, chemical analysis, mathematics education, quantitative social research, computational neuroscience, quantitative research topics in transportation engineering, quantitative research topics in energy economics, topics in quantum information science, amazing quantitative research topics in human genetics, quantitative research topics in marine biology, what is a common goal of qualitative and quantitative research.

A common goal of both qualitative and quantitative research is to generate knowledge and gain a deeper understanding of a particular phenomenon or topic. However, they approach this goal in different ways:

1. Understanding a Phenomenon

Both types of research aim to understand and explain a specific phenomenon, whether it’s a social issue, a natural process, a human behavior, or a complex event.

2. Testing Hypotheses

Both qualitative and quantitative research can involve hypothesis testing. While qualitative research may not use statistical hypothesis tests in the same way as quantitative research, it often tests hypotheses or research questions by examining patterns and themes in the data.

3. Contributing to Knowledge

Researchers in both approaches seek to contribute to the body of knowledge in their respective fields. They aim to answer important questions, address gaps in existing knowledge, and provide insights that can inform theory, practice, or policy.

4. Informing Decision-Making

Research findings from both qualitative and quantitative studies can be used to inform decision-making in various domains, whether it’s in academia, government, industry, healthcare, or social services.

5. Enhancing Understanding

Both approaches strive to enhance our understanding of complex phenomena by systematically collecting and analyzing data. They aim to provide evidence-based explanations and insights.

6. Application

Research findings from both qualitative and quantitative studies can be applied to practical situations. For example, the results of a quantitative study on the effectiveness of a new drug can inform medical treatment decisions, while qualitative research on customer preferences can guide marketing strategies.

7. Contributing to Theory

In academia, both types of research contribute to the development and refinement of theories in various disciplines. Quantitative research may provide empirical evidence to support or challenge existing theories, while qualitative research may generate new theoretical frameworks or perspectives.

Conclusion – Quantitative Research Topics For STEM Students

So, selecting a quantitative research topic for STEM students is a pivotal decision that can shape the trajectory of your academic and professional journey. The process involves a thoughtful exploration of your interests, a thorough review of the existing literature, consideration of available resources, and the formulation of a clear and specific research question.

Your chosen topic should resonate with your passions, align with your academic or career goals, and offer the potential to contribute to the body of knowledge in your STEM field. Whether you’re delving into physics, biology, engineering, mathematics, or any other STEM discipline, the right research topic can spark curiosity, drive innovation, and lead to valuable insights.

Moreover, quantitative research in STEM not only expands the boundaries of human knowledge but also has the power to address real-world challenges, improve technology, and enhance our understanding of the natural world. It is a journey that demands dedication, intellectual rigor, and an unwavering commitment to scientific inquiry.

What is quantitative research in STEM?

Quantitative research in this context is designed to improve our understanding of the science system’s workings, structural dependencies and dynamics.

What are good examples of quantitative research?

Surveys and questionnaires serve as common examples of quantitative research. They involve collecting data from many respondents and analyzing the results to identify trends, patterns

What are the 4 C’s in STEM?

They became known as the “Four Cs” — critical thinking, communication, collaboration, and creativity.

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240+ Experimental Quantitative Research Topics For STEM Students In 2024 (Updated)

STEM stands for Science, Technology, Engineering, and Math, but these are not the only subjects we learn in school. STEM is like a treasure chest of skills that help students become great problem solvers, ready to tackle the real world’s challenges.

In this blog, we are exploring the world of Research Topics for STEM Students. We will explain what STEM really means and why it is so important for students. We will also give you the lowdown on how to pick a fascinating research topic. We will explain a list of 240+ Experimental Quantitative Research Topics For STEM Students.

And when it comes to writing a research title, we will guide you step by step. So, stay with us as we unlock the exciting world of STEM research – it is not just about grades; it is about growing smarter, more confident, and happier along the way.

What Is STEM?

Table of Contents

STEM is Science, Technology, Engineering, and Mathematics. It is a way of talking about things like learning, jobs, and activities related to these four important subjects. Science is about understanding the world around us, technology is about using tools and machines to solve problems, engineering is about designing and building things, and mathematics is about numbers and solving problems with them. STEM helps us explore, discover, and create cool stuff that makes our world better and more exciting.

Why STEM Research Is Important?

STEM research is important because it helps us learn new things about the world and solve problems. When scientists, engineers, and mathematicians study these subjects, they can discover cures for diseases, create new technology that makes life easier, and build things that help us live better. It is like a big puzzle where we put together pieces of knowledge to make our world safer, healthier, and more fun.

• STEM research leads to discoveries and solutions.
• It helps find cures for diseases.
• STEM technology makes life easier.
• Engineers build things that improve our lives.
• Mathematics helps us understand and solve complex problems. There are various Mathematic formulas that students should know.

How to Choose a Topic for STEM Research Paper

Here are some steps to choose a topic for STEM Research Paper:

Step 1: Identify Your Interests

Think about what you like and what excites you in science, technology, engineering, or math. It could be something you learned in school, saw in the news, or experienced in your daily life. Choosing a topic you’re passionate about makes the research process more enjoyable.

Step 2: Research Existing Topics

Look up different STEM research areas online, in books, or at your library. See what scientists and experts are studying. This can give you ideas and help you understand what’s already known in your chosen field.

Step 3: Consider Real-World Problems

Think about the problems you see around you. Are there issues in your community or the world that STEM can help solve? Choosing a topic that addresses a real-world problem can make your research impactful.

Step 4: Talk to Teachers and Mentors

Discuss your interests with your teachers, professors, or mentors. They can offer guidance and suggest topics that align with your skills and goals. They may also provide resources and support for your research.

Step 5: Narrow Down Your Topic

Once you have some ideas, narrow them down to a specific research question or project. Make sure it’s not too broad or too narrow. You want a topic that you can explore in depth within the scope of your research paper.

240+ Experimental Quantitative Research Topics For STEM Students In 2023

Here, we will discuss 240+ Experimental Quantitative Research Topics For STEM Students: 

Qualitative Research Topics for STEM Students:

Qualitative research focuses on exploring and understanding phenomena through non-numerical data and subjective experiences. Here are 10 qualitative research topics for STEM students:

• Exploring the experiences of female STEM students in overcoming gender bias in academia.
• Understanding the perceptions of teachers regarding the integration of technology in STEM education.
• Investigating the motivations and challenges of STEM educators in underprivileged schools.
• Exploring the attitudes and beliefs of parents towards STEM education for their children.
• Analyzing the impact of collaborative learning on student engagement in STEM subjects.
• Investigating the experiences of STEM professionals in bridging the gap between academia and industry.
• Understanding the cultural factors influencing STEM career choices among minority students.
• Exploring the role of mentorship in the career development of STEM graduates.
• Analyzing the perceptions of students towards the ethics of emerging STEM technologies like AI and CRISPR. You may check the best AI tools like Top 10 AI Chatbots in 2024: Efficient ChatGPT Alternatives or Rise Of Generative AI: Transforming The Way Businesses Create Content .
• Investigating the emotional well-being and stress levels of STEM students during their academic journey.

Easy Experimental Research Topics for STEM Students:

These experimental research topics are relatively straightforward and suitable for STEM students who are new to research:

• Measuring the effect of different light wavelengths on plant growth.
• Investigating the relationship between exercise and heart rate in various age groups.
• Testing the effectiveness of different insulating materials in conserving heat.
• Examining the impact of pH levels on the rate of chemical reactions.
• Studying the behavior of magnets in different temperature conditions.
• Investigating the effect of different concentrations of a substance on bacterial growth.
• Testing the efficiency of various sunscreen brands in blocking UV radiation.
• Measuring the impact of music genres on concentration and productivity.
• Examining the correlation between the angle of a ramp and the speed of a rolling object.
• Investigating the relationship between the number of blades on a wind turbine and energy output.

Research Topics for STEM Students in the Philippines:

These research topics are tailored for STEM students in the Philippines:

• Assessing the impact of climate change on the biodiversity of coral reefs in the Philippines.
• Studying the potential of indigenous plants in the Philippines for medicinal purposes.
• Investigating the feasibility of harnessing renewable energy sources like solar and wind in rural Filipino communities.
• Analyzing the water quality and pollution levels in major rivers and lakes in the Philippines.
• Exploring sustainable agricultural practices for small-scale farmers in the Philippines.
• Assessing the prevalence and impact of dengue fever outbreaks in urban areas of the Philippines.
• Investigating the challenges and opportunities of STEM education in remote Filipino islands.
• Studying the impact of typhoons and natural disasters on infrastructure resilience in the Philippines.
• Analyzing the genetic diversity of endemic species in the Philippine rainforests.
• Assessing the effectiveness of disaster preparedness programs in Philippine communities.

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Good Research Topics for STEM Students:

These research topics are considered good because they offer interesting avenues for investigation and learning:

• Developing a low-cost and efficient water purification system for rural communities.
• Investigating the potential use of CRISPR-Cas9 for gene therapy in genetic disorders.
• Studying the applications of blockchain technology in securing medical records.
• Analyzing the impact of 3D printing on customized prosthetics for amputees.
• Exploring the use of artificial intelligence in predicting and preventing forest fires.
• Investigating the effects of microplastic pollution on aquatic ecosystems.
• Analyzing the use of drones in monitoring and managing crops.
• Studying the potential of quantum computing in solving complex optimization problems.
• Investigating the development of biodegradable materials for sustainable packaging.
• Exploring the ethical implications of gene editing in humans.

Unique Research Topics for STEM Students:

Unique research topics can provide STEM students with the opportunity to explore unconventional and innovative ideas. Here are 10 unique research topics for STEM students:

• Investigating the use of bioluminescent organisms for sustainable lighting solutions.
• Studying the potential of using spider silk proteins for advanced materials in engineering.
• Exploring the application of quantum entanglement for secure communication in the field of cryptography.
• Analyzing the feasibility of harnessing geothermal energy from underwater volcanoes.
• Investigating the use of CRISPR-Cas12 for rapid and cost-effective disease diagnostics.
• Studying the interaction between artificial intelligence and human creativity in art and music generation.
• Exploring the development of edible packaging materials to reduce plastic waste.
• Investigating the impact of microgravity on cellular behavior and tissue regeneration in space.
• Analyzing the potential of using sound waves to detect and combat invasive species in aquatic ecosystems.
• Studying the use of biotechnology in reviving extinct species, such as the woolly mammoth.

Experimental Research Topics for STEM Students in the Philippines

Research topics for STEM students in the Philippines can address specific regional challenges and opportunities. Here are 10 experimental research topics for STEM students in the Philippines:

• Assessing the effectiveness of locally sourced materials for disaster-resilient housing construction in typhoon-prone areas.
• Investigating the utilization of indigenous plants for natural remedies in Filipino traditional medicine.
• Studying the impact of volcanic soil on crop growth and agriculture in volcanic regions of the Philippines.
• Analyzing the water quality and purification methods in remote island communities.
• Exploring the feasibility of using bamboo as a sustainable construction material in the Philippines.
• Investigating the potential of using solar stills for freshwater production in water-scarce regions.
• Studying the effects of climate change on the migration patterns of bird species in the Philippines.
• Analyzing the growth and sustainability of coral reefs in marine protected areas.
• Investigating the utilization of coconut waste for biofuel production.
• Studying the biodiversity and conservation efforts in the Tubbataha Reefs Natural Park.

Capstone Research Topics for STEM Students in the Philippines:

Capstone research projects are often more comprehensive and can address real-world issues. Here are 10 capstone research topics for STEM students in the Philippines:

• Designing a low-cost and sustainable sanitation system for informal settlements in urban Manila.
• Developing a mobile app for monitoring and reporting natural disasters in the Philippines.
• Assessing the impact of climate change on the availability and quality of drinking water in Philippine cities.
• Designing an efficient traffic management system to address congestion in major Filipino cities.
• Analyzing the health implications of air pollution in densely populated urban areas of the Philippines.
• Developing a renewable energy microgrid for off-grid communities in the archipelago.
• Assessing the feasibility of using unmanned aerial vehicles (drones) for agricultural monitoring in rural Philippines.
• Designing a low-cost and sustainable aquaponics system for urban agriculture.
• Investigating the potential of vertical farming to address food security in densely populated urban areas.
• Developing a disaster-resilient housing prototype suitable for typhoon-prone regions.

Experimental Quantitative Research Topics for STEM Students:

Experimental quantitative research involves the collection and analysis of numerical data to conclude. Here are 10 Experimental Quantitative Research Topics For STEM Students interested in experimental quantitative research:

• Examining the impact of different fertilizers on crop yield in agriculture.
• Investigating the relationship between exercise and heart rate among different age groups.
• Analyzing the effect of varying light intensities on photosynthesis in plants.
• Studying the efficiency of various insulation materials in reducing building heat loss.
• Investigating the relationship between pH levels and the rate of corrosion in metals.
• Analyzing the impact of different concentrations of pollutants on aquatic ecosystems.
• Examining the effectiveness of different antibiotics on bacterial growth.
• Trying to figure out how temperature affects how thick liquids are.
• Finding out if there is a link between the amount of pollution in the air and lung illnesses in cities.
• Analyzing the efficiency of solar panels in converting sunlight into electricity under varying conditions.

Descriptive Research Topics for STEM Students

Descriptive research aims to provide a detailed account or description of a phenomenon. Here are 10 topics for STEM students interested in descriptive research:

• Describing the physical characteristics and behavior of a newly discovered species of marine life.
• Documenting the geological features and formations of a particular region.
• Creating a detailed inventory of plant species in a specific ecosystem.
• Describing the properties and behavior of a new synthetic polymer.
• Documenting the daily weather patterns and climate trends in a particular area.
• Providing a comprehensive analysis of the energy consumption patterns in a city.
• Describing the structural components and functions of a newly developed medical device.
• Documenting the characteristics and usage of traditional construction materials in a region.
• Providing a detailed account of the microbiome in a specific environmental niche.
• Describing the life cycle and behavior of a rare insect species.

Research Topics for STEM Students in the Pandemic:

The COVID-19 pandemic has raised many research opportunities for STEM students. Here are 10 research topics related to pandemics:

• Analyzing the effectiveness of various personal protective equipment (PPE) in preventing the spread of respiratory viruses.
• Studying the impact of lockdown measures on air quality and pollution levels in urban areas.
• Investigating the psychological effects of quarantine and social isolation on mental health.
• Analyzing the genomic variation of the SARS-CoV-2 virus and its implications for vaccine development.
• Studying the efficacy of different disinfection methods on various surfaces.
• Investigating the role of contact tracing apps in tracking & controlling the spread of infectious diseases.
• Analyzing the economic impact of the pandemic on different industries and sectors.
• Studying the effectiveness of remote learning in STEM education during lockdowns.
• Investigating the social disparities in healthcare access during a pandemic.
• Analyzing the ethical considerations surrounding vaccine distribution and prioritization.

Research Topics for STEM Students Middle School

Research topics for middle school STEM students should be engaging and suitable for their age group. Here are 10 research topics:

• Investigating the growth patterns of different types of mold on various food items.
• Studying the negative effects of music on plant growth and development.
• Analyzing the relationship between the shape of a paper airplane and its flight distance.
• Investigating the properties of different materials in making effective insulators for hot and cold beverages.
• Studying the effect of salt on the buoyancy of different objects in water.
• Analyzing the behavior of magnets when exposed to different temperatures.
• Investigating the factors that affect the rate of ice melting in different environments.
• Studying the impact of color on the absorption of heat by various surfaces.
• Analyzing the growth of crystals in different types of solutions.
• Investigating the effectiveness of different natural repellents against common pests like mosquitoes.

Technology Research Topics for STEM Students

Technology is at the forefront of STEM fields. Here are 10 research topics for STEM students interested in technology:

• Developing and optimizing algorithms for autonomous drone navigation in complex environments.
• Exploring the use of blockchain technology for enhancing the security and transparency of supply chains.
• Investigating the applications of virtual reality (VR) and augmented reality (AR) in medical training and surgery simulations.
• Studying the potential of 3D printing for creating personalized prosthetics and orthopedic implants.
• Analyzing the ethical and privacy implications of facial recognition technology in public spaces.
• Investigating the development of quantum computing algorithms for solving complex optimization problems.
• Explaining the use of machine learning and AI in predicting and mitigating the impact of natural disasters.
• Studying the advancement of brain-computer interfaces for assisting individuals with
• disabilities.
• Analyzing the role of wearable technology in monitoring and improving personal health and wellness.
• Investigating the use of robotics in disaster response and search and rescue operations.

Scientific Research Topics for STEM Students

Scientific research encompasses a wide range of topics. Here are 10 research topics for STEM students focusing on scientific exploration:

• Investigating the behavior of subatomic particles in high-energy particle accelerators.
• Studying the ecological impact of invasive species on native ecosystems.
• Analyzing the genetics of antibiotic resistance in bacteria and its implications for healthcare.
• Exploring the physics of gravitational waves and their detection through advanced interferometry.
• Investigating the neurobiology of memory formation and retention in the human brain.
• Studying the biodiversity and adaptation of extremophiles in harsh environments.
• Analyzing the chemistry of deep-sea hydrothermal vents and their potential for life beyond Earth.
• Exploring the properties of superconductors and their applications in technology.
• Investigating the mechanisms of stem cell differentiation for regenerative medicine.
• Studying the dynamics of climate change and its impact on global ecosystems.

Interesting Research Topics for STEM Students:

Engaging and intriguing research topics can foster a passion for STEM. Here are 10 interesting research topics for STEM students:

• Exploring the science behind the formation of auroras and their cultural significance.
• Investigating the mysteries of dark matter and dark energy in the universe.
• Studying the psychology of decision-making in high-pressure situations, such as sports or
• emergencies.
• Analyzing the impact of social media on interpersonal relationships and mental health.
• Exploring the potential for using genetic modification to create disease-resistant crops.
• Investigating the cognitive processes involved in solving complex puzzles and riddles.
• Studying the history and evolution of cryptography and encryption methods.
• Analyzing the physics of time travel and its theoretical possibilities.
• Exploring the role of Artificial Intelligence in creating art and music.
• Investigating the science of happiness and well-being, including factors contributing to life satisfaction.

Practical Research Topics for STEM Students

Practical research often leads to real-world solutions. Here are 10 practical research topics for STEM students:

• Developing an affordable and sustainable water purification system for rural communities.
• Designing a low-cost, energy-efficient home heating and cooling system.
• Investigating strategies for reducing food waste in the supply chain and households.
• Studying the effectiveness of eco-friendly pest control methods in agriculture.
• Analyzing the impact of renewable energy integration on the stability of power grids.
• Developing a smartphone app for early detection of common medical conditions.
• Investigating the feasibility of vertical farming for urban food production.
• Designing a system for recycling and upcycling electronic waste.
• Studying the environmental benefits of green roofs and their potential for urban heat island mitigation.
• Analyzing the efficiency of alternative transportation methods in reducing carbon emissions.

Experimental Research Topics for STEM Students About Plants

Plants offer a rich field for experimental research. Here are 10 experimental research topics about plants for STEM students:

• Investigating the effect of different light wavelengths on plant growth and photosynthesis.
• Studying the impact of various fertilizers and nutrient solutions on crop yield.
• Analyzing the response of plants to different types and concentrations of plant hormones.
• Investigating the role of mycorrhizal in enhancing nutrient uptake in plants.
• Studying the effects of drought stress and water scarcity on plant physiology and adaptation mechanisms.
• Analyzing the influence of soil pH on plant nutrient availability and growth.
• Investigating the chemical signaling and defense mechanisms of plants against herbivores.
• Studying the impact of environmental pollutants on plant health and genetic diversity.
• Analyzing the role of plant secondary metabolites in pharmaceutical and agricultural applications.
• Investigating the interactions between plants and beneficial microorganisms in the rhizosphere.

Qualitative Research Topics for STEM Students in the Philippines

Qualitative research in the Philippines can address local issues and cultural contexts. Here are 10 qualitative research topics for STEM students in the Philippines:

• Exploring indigenous knowledge and practices in sustainable agriculture in Filipino communities.
• Studying the perceptions and experiences of Filipino fishermen in coping with climate change impacts .
• Analyzing the cultural significance and traditional uses of medicinal plants in indigenous Filipino communities.
• Investigating the barriers and facilitators of STEM education access in remote Philippine islands.
• Exploring the role of traditional Filipino architecture in natural disaster resilience.
• Studying the impact of indigenous farming methods on soil conservation and fertility.
• Analyzing the cultural and environmental significance of mangroves in coastal Filipino regions.
• Investigating the knowledge and practices of Filipino healers in treating common ailments.
• Exploring the cultural heritage and conservation efforts of the Ifugao rice terraces.
• Studying the perceptions and practices of Filipino communities in preserving marine biodiversity.

Science Research Topics for STEM Students

Science offers a diverse range of research avenues. Here are 10 science research topics for STEM students:

• Investigating the potential of gene editing techniques like CRISPR-Cas9 in curing genetic diseases.
• Studying the ecological impacts of species reintroduction programs on local ecosystems.
• Analyzing the effects of microplastic pollution on aquatic food webs and ecosystems.
• Investigating the link between air pollution and respiratory health in urban populations.
• Studying the role of epigenetics in the inheritance of acquired traits in organisms.
• Analyzing the physiology and adaptations of extremophiles in extreme environments on Earth.
• Investigating the genetics of longevity and factors influencing human lifespan.
• Studying the behavioral ecology and communication strategies of social insects.
• Analyzing the effects of deforestation on global climate patterns and biodiversity loss.
• Investigating the potential of synthetic biology in creating bioengineered organisms for beneficial applications.

Correlational Research Topics for STEM Students

Correlational research focuses on relationships between variables. Here are 10 correlational research topics for STEM students:

• Analyzing the correlation between dietary habits and the incidence of chronic diseases.
• Studying the relationship between exercise frequency and mental health outcomes.
• Investigating the correlation between socioeconomic status and access to quality healthcare.
• Analyzing the link between social media usage and self-esteem in adolescents.
• Studying the correlation between academic performance and sleep duration among students.
• Investigating the relationship between environmental factors and the prevalence of allergies.
• Analyzing the correlation between technology use and attention span in children.
• Studying how environmental factors are related to the frequency of allergies.
• Investigating the link between parental involvement in education and student achievement.
• Analyzing the correlation between temperature fluctuations and wildlife migration patterns.

Quantitative Research Topics for STEM Students in the Philippines

Quantitative research in the Philippines can address specific regional issues. Here are 10 quantitative research topics for STEM students in the Philippines

• Analyzing the impact of typhoons on coastal erosion rates in the Philippines.
• Studying the quantitative effects of land use change on watershed hydrology in Filipino regions.
• Investigating the quantitative relationship between deforestation and habitat loss for endangered species.
• Analyzing the quantitative patterns of marine biodiversity in Philippine coral reef ecosystems.
• Studying the quantitative assessment of water quality in major Philippine rivers and lakes.
• Investigating the quantitative analysis of renewable energy potential in specific Philippine provinces.
• Analyzing the quantitative impacts of agricultural practices on soil health and fertility.
• Studying the quantitative effectiveness of mangrove restoration in coastal protection in the Philippines.
• Investigating the quantitative evaluation of indigenous agricultural practices for sustainability .
• Analyzing the quantitative patterns of air pollution and its health impacts in urban Filipino areas.

Environmental Science Research Topics for STEM Students In the USA

• Measuring the effect of deforestation on carbon dioxide levels.
• Quantifying the rate of soil erosion under different farming practices.
• Statistical analysis of air pollution levels in urban vs. rural areas.
• Quantifying the impact of plastic pollution on marine life.
• Measuring the efficiency of water purification techniques.
• Statistical comparison of renewable vs. non-renewable energy sources.
• Quantifying the rate of melting glaciers due to global warming.
• Investigating the effect of climate change on species migration patterns.
• Quantitative analysis of the impact of urbanization on local ecosystems.
• Measuring the impact of pesticide use on soil microorganisms.
• Investigating the relationship between water quality and human health.
• Quantifying the impact of conservation efforts on endangered species.
• Statistical analysis of waste generation and recycling rates.
• Measuring the effectiveness of different methods for reducing carbon emissions.
• Quantifying the rate of ocean acidification over time.
• Investigating the effects of oil spills on marine biodiversity.
• Measuring the energy efficiency of different agricultural practices.
• Quantitative study of the relationship between water scarcity and agriculture.
• Investigating the effect of temperature rise on coral reef ecosystems.
• Quantifying the relationship between forest cover and local weather patterns.

Physics Research Topics for STEM Students 

• Measuring the speed of sound in different media.
• Quantifying the energy loss in elastic vs. inelastic collisions.
• Statistical analysis of projectile motion under varying wind conditions.
• The effect of temperature on the resistance of conductors.
• Measuring the impact force in different types of collisions.
• Effects of varying mass on the pendulum oscillation frequency.
• Quantifying the relationship between force, mass, and acceleration.
• Statistical analysis of wave interference patterns in light.
• Measuring the effects of gravitational force on falling objects.
• Analysis of friction’s impact on energy efficiency in different materials.
• Statistical study of voltage drop across different types of resistors.
• Measuring magnetic field strength in different materials.
• The quantitative relationship between electric current and magnetic field generation.
• Effects of varying pressure on gas volume: Boyle’s Law in action.
• Measuring the thermal conductivity of different metals.
• Quantifying energy transfer in different types of heat exchangers.
• The effect of altitude on atmospheric pressure.
• Statistical analysis of the efficiency of different photovoltaic cells.
• Measuring energy conservation in simple harmonic motion.
• Investigating the Doppler effect with different sound frequencies.

Mathematics Research Topics for STEM Students In The USA

• Statistical analysis of correlation coefficients in large data sets.
• Quantifying the probability distribution of random variables in simulations.
• Statistical modeling of population growth trends over time.
• Analyzing the efficiency of different algorithms in solving large datasets.
• A quantitative comparison of different statistical methods for outlier detection.
• Measuring the accuracy of predictive modeling in weather forecasting.
• Application of Monte Carlo methods to model real-world systems.
• Statistical analysis of market trends using regression models.
• Quantitative analysis of game theory in strategic decision making.
• Investigating the effectiveness of machine learning algorithms in pattern recognition.
• Quantifying the chaos theory in weather systems.
• Statistical analysis of the distribution of prime numbers.
• Measuring the complexity of fractal patterns in nature.
• Comparing the efficiency of numerical methods in solving differential equations.
• Quantitative study of optimization algorithms in resource allocation.
• Statistical comparison of geometric vs. arithmetic sequences in population models.
• Quantifying the impact of missing data on statistical model accuracy.
• Measuring the convergence rates of iterative methods in linear algebra.
• Quantitative comparison of algorithms in cryptography.
• Investigating the relationship between network theory and social media dynamics.

Things That Must Keep In Mind While Writing Quantitative Research Title 

Here are a few things that must be kept in mind while writing a quantitative research:

1. Be Clear and Precise

Make sure your research title is clear and says exactly what your study is about. People should easily understand the topic and goals of your research by reading the title.

2. Use Important Words

Include words that are crucial to your research, like the main subjects, who you’re studying, and how you’re doing your research. This helps others find your work and understand what it’s about.

3. Avoid Confusing Words

Stay away from words that might confuse people. Your title should be easy to grasp, even if someone isn’t an expert in your field.

4. Show Your Research Approach

Tell readers what kind of research you did, like experiments or surveys. This gives them a hint about how you conducted your study.

5. Match Your Title with Your Research Questions

Make sure your title matches the questions you’re trying to answer in your research. It should give a sneak peek into what your study is all about and keep you on the right track as you work on it.

Also Read: Exploring Quantitative Biology: A Guide to Research Topics

STEM students, addressing what STEM is and why research matters in this field. It offered an extensive list of research topics , including experimental, qualitative, and regional options, catering to various academic levels and interests. Whether you’re a middle school student or pursuing advanced studies, these topics offer a wealth of ideas. The key takeaway is to choose a topic that resonates with your passion and aligns with your goals, ensuring a successful journey in STEM research. Choose the best Experimental Quantitative Research Topics For STEM students today!

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55 Brilliant Research Topics For STEM Students

Primarily, STEM is an acronym for Science, Technology, Engineering, and Mathematics. It’s a study program that weaves all four disciplines for cross-disciplinary knowledge to solve scientific problems. STEM touches across a broad array of subjects as STEM students are required to gain mastery of four disciplines.

As a project-based discipline, STEM has different stages of learning. The program operates like other disciplines, and as such, STEM students embrace knowledge depending on their level. Since it’s a discipline centered around innovation, students undertake projects regularly. As a STEM student, your project could either be to build or write on a subject. Your first plan of action is choosing a topic if it’s written. After selecting a topic, you’ll need to determine how long a thesis statement should be .

Given that topic is essential to writing any project, this article focuses on research topics for STEM students. So, if you’re writing a STEM research paper or write my research paper , below are some of the best research topics for STEM students.

List of Research Topics For STEM Students

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Several research topics can be formulated in this field. They cut across STEM science, engineering, technology, and math. Here is a list of good research topics for STEM students.

• The effectiveness of online learning over physical learning
• The rise of metabolic diseases and their relationship to increased consumption
• How immunotherapy can improve prognosis in Covid-19 progression

For your quantitative research in STEM, you’ll need to learn how to cite a thesis MLA for the topic you’re choosing. Below are some of the best quantitative research topics for STEM students.

• A study of the effect of digital technology on millennials
• A futuristic study of a world ruled by robotics
• A critical evaluation of the future demand in artificial intelligence

There are several practical research topics for STEM students. However, if you’re looking for qualitative research topics for STEM students, here are topics to explore.

• An exploration into how microbial factories result in the cause shortage in raw metals
• An experimental study on the possibility of older-aged men passing genetic abnormalities to children
• A critical evaluation of how genetics could be used to help humans live healthier and longer.

Experimental research in STEM is a scientific research methodology that uses two sets of variables. They are dependent and independent variables that are studied under experimental research. Experimental research topics in STEM look into areas of science that use data to derive results.

Below are easy experimental research topics for STEM students.

• A study of nuclear fusion and fission
• An evaluation of the major drawbacks of Biotechnology in the pharmaceutical industry
• A study of single-cell organisms and how they’re capable of becoming an intermediary host for diseases causing bacteria

Unlike experimental research, non-experimental research lacks the interference of an independent variable. Non-experimental research instead measures variables as they naturally occur. Below are some non-experimental quantitative research topics for STEM students.

• Impacts of alcohol addiction on the psychological life of humans
• The popularity of depression and schizophrenia amongst the pediatric population
• The impact of breastfeeding on the child’s health and development

STEM learning and knowledge grow in stages. The older students get, the more stringent requirements are for their STEM research topic. There are several capstone topics for research for STEM students .

Below are some simple quantitative research topics for stem students.

• How population impacts energy-saving strategies
• The application of an Excel table processor capabilities for cost calculation
•  A study of the essence of science as a sphere of human activity

Correlations research is research where the researcher measures two continuous variables. This is done with little or no attempt to control extraneous variables but to assess the relationship. Here are some sample research topics for STEM students to look into bearing in mind how to cite a thesis APA style for your project.

• Can pancreatic gland transplantation cure diabetes?
• A study of improved living conditions and obesity
• An evaluation of the digital currency as a valid form of payment and its impact on banking and economy

There are several science research topics for STEM students. Below are some possible quantitative research topics for STEM students.

• A study of protease inhibitor and how it operates
• A study of how men’s exercise impacts DNA traits passed to children
• A study of the future of commercial space flight

If you’re looking for a simple research topic, below are easy research topics for STEM students.

• How can the problem of Space junk be solved?
• Can meteorites change our view of the universe?
• Can private space flight companies change the future of space exploration?

For your top 10 research topics for STEM students, here are interesting topics for STEM students to consider.

• A comparative study of social media addiction and adverse depression
• The human effect of the illegal use of formalin in milk and food preservation
• An evaluation of the human impact on the biosphere and its results
• A study of how fungus affects plant growth
• A comparative study of antiviral drugs and vaccine
• A study of the ways technology has improved medicine and life science
• The effectiveness of Vitamin D among older adults for disease prevention
• What is the possibility of life on other planets?
• Effects of Hubble Space Telescope on the universe
• A study of important trends in medicinal chemistry research

Below are possible research topics for STEM students about plants:

• How do magnetic fields impact plant growth?
• Do the different colors of light impact the rate of photosynthesis?
• How can fertilizer extend plant life during a drought?

Below are some examples of quantitative research topics for STEM students in grade 11.

• A study of how plants conduct electricity
• How does water salinity affect plant growth?
• A study of soil pH levels on plants

Here are some of the best qualitative research topics for STEM students in grade 12.

• An evaluation of artificial gravity and how it impacts seed germination
• An exploration of the steps taken to develop the Covid-19 vaccine
• Personalized medicine and the wave of the future

Here are topics to consider for your STEM-related research topics for high school students.

• A study of stem cell treatment
• How can molecular biological research of rare genetic disorders help understand cancer?
• How Covid-19 affects people with digestive problems

Below are some survey topics for qualitative research for stem students.

• How does Covid-19 impact immune-compromised people?
• Soil temperature and how it affects root growth
• Burned soil and how it affects seed germination

Here are some descriptive research topics for STEM students in senior high.

• The scientific information concept and its role in conducting scientific research
• The role of mathematical statistics in scientific research
• A study of the natural resources contained in oceans

Final Words About Research Topics For STEM Students

STEM topics cover areas in various scientific fields, mathematics, engineering, and technology. While it can be tasking, reducing the task starts with choosing a favorable topic. If you require external assistance in writing your STEM research, you can seek professional help from our experts.

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110+ Best Quantitative Research Topics for STEM Students

Explore engaging quantitative research topics for STEM students. This guide covers the basics, popular areas, and tips for success to help you make an impact.

Quantitative research uses data and numbers to uncover insights. Whether you’re into computer science, engineering, or natural sciences, it’s a powerful tool for discovery.

Ready to get started? Let’s dive in!

Table of Contents

Quantitative Research Topics for STEM Students PDF

Understanding quantitative research.

Quantitative research uses numerical data and statistical methods to find patterns and draw conclusions.

Key Characteristics

• Objectivity: Minimizes personal bias.
• Numerical Data: Focuses on measurable data.
• Generalizability: Makes broad conclusions from samples.
• Structured Design: Follows a set research plan.
• Statistical Analysis: Uses statistics to analyze data.

Quantitative vs. Qualitative Research

• Quantitative: Deals with numbers and statistical analysis.
• Qualitative: Explores non-numerical data like text and images.

The Research Process

• Identify the Problem: Define the research question.
• Formulate Hypotheses: Create testable statements.
• Collect Data: Use surveys, experiments, or observations.
• Analyze Data: Apply statistical methods.
• Interpret Findings: Draw conclusions based on results.

These basics help in designing and conducting effective quantitative research.

Popular Quantitative Research Methods

Check out popular quantitative research methods:-

• Description: Collect data via questionnaires or interviews.
• Use: Measure attitudes, opinions, or behaviors.
• Example: Assessing student satisfaction with online learning.

Experiments

• Description: Manipulate variables to see effects.
• Use: Determine cause-and-effect relationships.
• Example: Testing a new drug’s effectiveness.

Correlational Studies

• Description: Examine relationships between variables.
• Use: Identify patterns and trends.
• Example: Linking air pollution to respiratory issues.

Causal-Comparative Research

• Description: Compare groups without random assignment.
• Use: Explore cause-and-effect when experiments aren’t possible.
• Example: Comparing student performance across socioeconomic backgrounds.

Observational Studies

• Description: Observe and record behavior in natural settings.
• Use: Study behaviors not suitable for experiments.
• Example: Observing animal behavior in the wild.

Content Analysis

• Description: Analyze text or visual content for data.
• Use: Study media or document content.
• Example: Analyzing trends in scientific papers.

Longitudinal Studies

• Description: Collect data from the same group over time.
• Use: Track changes and developments.
• Example: Monitoring plant growth under various conditions.

These methods help researchers choose the best approach for their questions.

Quantitative Research Topics for STEM Students

Check out quantitative research topics for STEM students:-

• Friction : Compare friction on different surfaces.
• Light Diffraction : Measure light patterns through slits.
• Heat Engines : Test efficiency with different fluids.
• Magnetism : Study magnetic field strength in wires.
• Quantum : Analyze electron patterns in a slit experiment.
• Sound Absorption : Test materials for sound absorption.
• Gravity : Study forces in planetary motion.
• Fluid Flow : Measure flow rates in different conditions.
• Radioactivity : Compare decay rates of isotopes.
• Metal Expansion : Measure how metals expand when heated.
• Reaction Rates : Study catalysts’ effect on reaction speed.
• Gas Solubility : Test gas dissolving in liquids at different temps.
• Battery Efficiency : Compare power in different battery types.
• Reaction Yield : Measure product yield in reactions.
• Buffer Solutions : Test buffers’ ability to resist pH changes.
• Organic Reactions : Study reaction speed in organic compounds.
• Equilibrium : Analyze shifts in chemical equilibrium.
• Adsorption : Test adsorption on solid surfaces.
• Heat Changes : Measure energy in chemical reactions.
• Polymer Size : Compare sizes of different polymers.
• Gene Linkage : Study gene inheritance patterns.
• Antibiotics : Test bacteria growth with antibiotics.
• Invasive Species : Measure impact on native species.
• BMI vs Heart Rate : Compare BMI with heart rates.
• Blood Glucose : Measure blood sugar before/after meals.
• Photosynthesis : Test plant growth under various light.
• Reaction Times : Compare responses to visual and sound stimuli.
• Cell Growth : Measure cell growth under different nutrients.
• Vaccine Response : Test antibody production after vaccines.
• Animal Behavior : Study stress effects on animal behavior.

Environmental Science

• Soil Pollution : Measure heavy metals in soil.
• Glacier Melt : Track glacier melting rates.
• Energy Use : Compare renewable energy in homes.
• Composting : Test compost methods for waste reduction.
• Water Oxygen : Measure oxygen in water bodies.
• Air Pollution : Compare urban and rural air quality.
• Species Richness : Measure species diversity in forests.
• Carbon Storage : Compare carbon storage in trees.
• Soil Erosion : Measure soil loss in farms.
• Solar Panels : Test solar efficiency in different weather.

Engineering

• Material Strength : Test building materials’ strength.
• Power Loss : Measure power loss in transmission lines.
• Gear Efficiency : Compare efficiency of gear types.
• Road Surfaces : Study effects of road materials on fuel use.
• Software Bugs : Count bugs in different coding languages.
• Chemical Reactors : Test reactor yields at various temps.
• Airfoil Lift : Measure lift in different wing designs.
• Prosthetics : Compare materials used in prosthetics.
• Water Treatment : Test effectiveness of water treatment.
• Robot Accuracy : Measure precision in robotic arms.

Mathematics

• Probability : Analyze outcome probabilities in experiments.
• Cooling Rates : Measure cooling rates using calculus.
• Cryptography : Study algebra in encryption methods.
• Shape Geometry : Calculate area and perimeter of shapes.
• Population Models : Model population growth rates.
• Prime Numbers : Analyze prime number distribution.
• Graphics : Test matrix operations in computer graphics.
• Combinations : Study combinations in optimization problems.
• Game Strategy : Analyze game strategies mathematically.
• Resource Allocation : Optimize resources in production.

Computer Science

• Data Patterns : Analyze data clusters in large datasets.
• AI Accuracy : Test machine learning models’ precision.
• Cyber-Attacks : Measure attack frequency on networks.
• Algorithm Performance : Compare sorting algorithm speeds.
• User Interface : Test user satisfaction in different designs.
• Object Detection : Measure accuracy in computer vision.
• Sentiment Analysis : Test algorithms in sentiment detection.
• Blockchain Speed : Measure transaction speeds in blockchain.
• Encryption : Test security of different encryption methods.
• Big Data : Analyze performance in big data systems.

Medicine and Health

• Disease Spread : Study disease spread in dense populations.
• Drug Dosage : Measure drug effectiveness at different doses.
• Vaccine Impact : Test vaccine success rates.
• Diet Impact : Measure diet effects on cholesterol.
• Imaging Accuracy : Compare diagnostic imaging methods.
• Heart Rate : Study heart rate variability in stress.
• Cancer Treatment : Compare effectiveness of cancer treatments.
• Surgery Recovery : Measure recovery time in joint surgeries.
• Mental Health : Study anxiety and depression rates.
• Gene Expression : Analyze gene activity in disorders.

Astronomy and Space Science

• Star Brightness : Measure star brightness and distance.
• Impact Craters : Study craters and asteroid sizes.
• Universe Expansion : Analyze cosmic background radiation.
• Space Propulsion : Test deep space propulsion systems.
• Binary Stars : Study orbits in binary star systems.
• Exoplanet Detection : Measure planet detection accuracy.
• Dark Matter : Analyze dark matter in galaxies.
• Solar Radiation : Track solar radiation changes.
• Solar Flares : Study effects of solar flares on satellites.
• Space Chemistry : Measure chemicals in space clouds.

These topics are now more concise while still providing a clear focus for quantitative research.

Tips for Choosing a Research Topic

After brainstorming research topics, refine your ideas with these steps:

Narrow Your Topic

• Define specific research questions.
• Determine the scope and depth of your study.
• Identify key variables to measure.

Literature Review

• Explore existing research to find gaps.
• Review how previous studies were done.
• Identify relevant theories to support your work.

Feasibility Assessment

• Check if you have access to necessary data.
• Evaluate time and resource requirements.
• Secure any needed approvals or permissions.

Following these steps will help turn a broad idea into a focused research project.

Conducting Quantitative Research

Check out the best tips for coducting quantitative research:-

Data Collection Methods

Surveys: use questionnaires or interviews..

• Pros: Efficient for large data.
• Cons: Risk of bias, less detail.

Experiments: Change variables to see effects.

• Pros: Shows cause-and-effect.
• Cons: Time-consuming, costly, ethical issues.

Observations: Record behavior systematically.

• Pros: Natural data, captures unexpected behavior.
• Cons: Observer bias, time-consuming.

Data Analysis Techniques

• Use: Stats analysis, hypothesis testing.
• Use: Data manipulation, visualization, machine learning.

Research Ethics and Data Privacy

• Informed Consent: Ensure participants agree voluntarily.
• Data Privacy: Protect confidentiality.
• Data Integrity: Maintain accuracy and avoid misconduct.

Writing a Research Paper

• Clear Writing: Use concise academic language.
• Structure: Follow standard format (intro, methods, results, discussion).
• Data Visualization: Use graphs and charts.
• Citation Style: Follow APA or MLA.
• Proofreading: Check for clarity and grammar.

These steps help ensure rigorous, ethical research and clear communication.

Ethical Considerations in Quantitative Research

Ethical conduct is essential in research for protecting participants, ensuring integrity, and building trust.

Importance of Ethical Research

• Protects Participants: Avoids harm and privacy issues.
• Ensures Integrity: Keeps findings reliable.
• Builds Trust: Gains public confidence.

Informed Consent

• Clear Info: Explain the study clearly.
• Voluntary: Participation should be free of pressure.
• Right to Withdraw: Participants can leave anytime.

Data Privacy

• Confidentiality: Keep identities and data secure.
• Anonymity: Use data without personal identifiers when possible.
• Security: Protect data from unauthorized access.

Research Integrity

• Honesty: Report findings accurately.
• Avoid Plagiarism: Credit sources properly.
• Manage Data: Keep records organized and complete.

Adhering to these principles ensures ethical and trustworthy research.

Challenges and Opportunities in Quantitative Research

Quantitative research has its challenges but can be highly effective with the right approach.

• Data Quality: Ensure accuracy and handle errors.
• Sample Size: Find the right balance—avoid too small or too large.
• Causality: Correlation doesn’t equal causation.
• Generalizability: Ensure findings apply broadly.

Big Data and Advanced Analytics

• Vast Datasets: Discover new patterns.
• Advanced Analytics: Use AI and machine learning for insights.
• Predictive Modeling: Forecast trends and guide decisions.

Interdisciplinary Collaboration

• Diverse Perspectives: Gain fresh insights.
• Complementary Expertise: Combine strengths from different fields.
• Real-World Impact: Increase practical applications.

By tackling these challenges and leveraging new tools, researchers can achieve meaningful results.

Overcoming Challenges in Quantitative Research

Quantitative research can face challenges, but these strategies can help:

Data Quality

• Clean Data: Fix errors and inconsistencies.
• Handle Missing Data: Use statistical methods for imputation.
• Validate Data: Cross-check with other sources.

Sample Size

• Power Analysis: Determine the right sample size.
• Sampling Techniques: Use probability methods.
• Combine Data: Aggregate data from various sources.
• Randomization: Randomly assign participants.
• Control Factors: Manage confounding variables.
• Longitudinal Studies: Track changes over time.

Generalizability

• Representative Sample: Reflect the target population.
• Replicate Studies: Test across different settings.
• Strong Framework: Base findings on solid theory.

Big Data and Analytics

• Manage Data: Efficiently store and access data.
• Mine Data: Extract valuable insights.
• Apply Machine Learning: Discover patterns and make predictions.

Using these strategies can help address challenges and improve research outcomes.

Real-world Examples of Successful Quantitative Research Projects

Quantitative research drives progress in many fields. Here are some examples:

Medicine and Healthcare

• Clinical Trials: Test new treatments.
• Epidemiological Studies: Find disease risk factors.
• Health Economics: Assess healthcare costs and benefits.

Business and Economics

• Market Research: Study consumer behavior.
• Financial Modeling: Forecast market trends.
• Operations Research: Improve supply chains.

Social Sciences

• Education Research: Evaluate teaching methods .
• Political Science: Analyze voting and public opinion.
• Sociology: Examine social trends.

Natural Sciences

• Physics: Test scientific theories.
• Chemistry: Study chemical reactions.
• Biology: Research genetic patterns.
• Product Testing: Check product performance.
• Structural Analysis: Assess building strength.
• Process Optimization: Enhance manufacturing efficiency.

These examples highlight the diverse applications and impact of quantitative research.

Collaborate with Other Researchers

Collaboration is crucial in research. Here’s how to do it effectively:

Finding Collaborators

• Shared Interests: Look for those with similar research topics.
• Different Skills: Seek out varied expertise.
• Institutional Links: Partner within or outside your institution.
• Online Networks: Use research sites and social media.

Building Collaborations

• Communicate Clearly: Keep discussions open and honest.
• Set Goals: Define objectives and expectations.
• Define Roles: Outline each person’s responsibilities.
• Handle Conflicts: Plan for resolving disagreements.
• Build Trust: Foster respectful relationships.

Challenges to Address

• Manage Time: Balance joint and solo work.
• Clarify Ownership: Agree on who owns the research.
• Respect Differences: Manage cultural and background differences.
• Authorship Rules: Decide on publication credit.

Tools to Use

• Collaboration Software: Use Google Drive, Slack , or Teams.
• Project Management: Organize with Trello or Asana.
• Video Calls: Meet via Zoom or Skype.

Effective collaboration leads to productive research.

Quantitative Research Topics for STEM Students in the Philippines

Check out quantitative research topics for STEM students in the Philippines

Agriculture and Food Science

• Climate Impact on Rice : Study how climate change affects rice yields.
• Organic vs. Soil Health : Compare soil health in organic and conventional farming.
• Extension Programs : Evaluate agricultural extension program effectiveness.
• Aquaculture Benefits : Assess economic benefits of aquaculture.
• Sustainable Farming : Develop sustainable crop management methods.
• Organic Pest Control : Test organic pest control methods.
• Water Efficiency : Study water usage in farming.
• Fertilizer Effects : Compare soil health with different fertilizers.
• Food Security : Improve food security strategies.
• Agri-Tech : Explore technology in farming.

Information and Communications Technology (ICT)

• Digital Skills and Jobs : Study how digital skills affect jobs.
• Internet and Education : Analyze internet access and education.
• E-Learning Impact : Evaluate e-learning platforms.
• Digital Divide : Examine the digital divide’s effect on rural areas.
• Cybersecurity Education : Increase cybersecurity awareness.
• Social Media and Studies : Study social media’s impact on learning.
• Tech Access and Jobs : Compare tech access and job prospects.
• Learning Apps : Assess mobile learning apps.
• E-Governance : Investigate benefits of e-governance.
• Digital Training : Evaluate digital skills training.
• Deforestation and Wildlife : Study deforestation’s effect on wildlife.
• Pollution and Health : Analyze air pollution and health issues.
• Renewable Energy : Evaluate renewable energy’s effect on emissions.
• Climate and Erosion : Study climate change and coastal erosion.
• Biodiversity : Develop strategies to conserve biodiversity.
• Water Pollution : Investigate water pollution sources.
• Soil Erosion : Study land use and soil erosion.
• Plastic Waste : Analyze plastic waste impact on marine life.
• Renewable Adoption : Assess renewable energy adoption.
• Climate Adaptation : Explore climate adaptation strategies.
• Local Materials : Test local materials in earthquakes.
• Housing Efficiency : Evaluate energy efficiency in housing.
• Infrastructure Impact : Assess infrastructure’s effect on poverty.
• Energy Costs : Analyze costs of renewable energy projects.
• Building Materials : Research sustainable materials.
• Water Tech : Develop water conservation technologies.
• Smart Grids : Investigate smart grid benefits.
• Transportation Solutions : Explore urban transportation improvements.
• Disaster-Resistant Structures : Design structures for disasters.
• Green Certifications : Study green building certifications.

Medical and Health Sciences

• Disease Prevalence : Study non-communicable disease rates.
• Maternal Health : Evaluate programs reducing maternal deaths.
• Malnutrition Impact : Investigate malnutrition’s effect on growth.
• Healthcare Access : Analyze access based on socioeconomic status.
• Vaccination Impact : Assess vaccination’s role in disease prevention.
• Mental Health : Improve mental health awareness.
• Chronic Disease : Study chronic disease management.
• Health Tech : Explore healthcare technology.
• Nutrition Programs : Evaluate nutritional intervention effects.
• Health Education : Study health education program effectiveness.

Quantitative research is crucial in STEM fields, offering a structured way to study complex phenomena. By choosing a focused topic, using rigorous methods, and analyzing data effectively, students can make impactful contributions.

Success in quantitative research comes from curiosity, perseverance, and a drive to discover new knowledge. Embrace challenges as chances for growth and innovation.

Combining theory with practical application, your research can push the boundaries of knowledge and benefit society.

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60+ Best Quantitative Research Topics for STEM Students: Dive into Data

Embark on a captivating journey through the cosmos of knowledge with our curated guide on Quantitative Research Topics for STEM Students. Explore innovative ideas in science, technology, engineering, and mathematics, designed to ignite curiosity and shape the future.

Unleash the power of quantitative research and dive into uncharted territories that go beyond academics, fostering innovation and discovery.

Hey, you future scientists, tech wizards, engineering maestros, and math superheroes – gather ’round! We’re about to dive headfirst into the rad world of quantitative research topics, tailor-made for the rockstars of STEM.

In the crazy universe of science, technology, engineering, and math (STEM), quantitative research isn’t just a nerdy term—it’s your VIP pass to an interstellar adventure. Picture this: you’re strapping into a rocket ship, zooming through the cosmos, and decoding the universe’s coolest secrets, all while juggling numbers like a cosmic DJ.

But here’s the real scoop: finding the ultimate research topic is like picking the juiciest star in the galaxy. It’s about stumbling upon something so mind-blowing that you can’t resist plunging into the data. It’s about choosing questions that make your STEM-loving heart do the cha-cha.

In this guide, we’re not just your sidekicks; we’re your partners in crime through the vast jungle of quantitative research topics. Whether you’re a rookie gearing up for your first lab escapade or a seasoned explorer hunting for a new thrill, think of this article as your treasure map, guiding you to the coolest STEM discoveries.

From the teeny wonders of biology to the brain-bending puzzles of physics, the cutting-edge vibes of engineering, and the downright gorgeous dance of mathematics – we’ve got your back.

So, buckle up, fellow STEM enthusiasts! We’re setting sail on a cosmic adventure through the groovy galaxy of quantitative research topics. Get ready to unravel the secrets of science and tech, one sizzling digit at a time.

Stick around for a ride that’s part data, part disco, and all STEM swagger!

Table of Contents

Benefits of Choosing Quantitative Research

Embarking on the quantitative research journey is like stepping into a treasure trove of benefits across a spectrum of fields. Let’s dive into the exciting advantages that make choosing quantitative research a game-changer:

Numbers That Speak Louder

Quantitative research deals in cold, hard numbers. This means your data isn’t just informative; it’s objective, measurable, and has a voice of its own.

Statistical Swagger

Crunching numbers isn’t just for show. With quantitative research, statistical tools add a touch of pizzazz, boosting the validity of your findings and turning your study into a credible performance.

For the Masses

Quantitative research loves a crowd. Larger sample sizes mean your discoveries aren’t just for the lucky few – they’re for everyone. It’s the science of sharing the knowledge wealth.

Data Showdown

Ready for a duel between variables? Quantitative research sets the stage for epic battles, letting you compare, contrast, and uncover cause-and-effect relationships in the data arena.

Structured and Ready to Roll

Think of quantitative research like a well-organized party. It follows a structured plan, making replication a breeze. Because who doesn’t love a party that’s easy to recreate?

Data Efficiency Dance

Efficiency is the name of the game. Surveys, experiments, and structured observations make data collection a dance – choreographed, smooth, and oh-so-efficient.

Data Clarity FTW

No decoding needed here. Quantitative research delivers crystal-clear results. It’s like reading a good book without the need for interpretation – straightforward and to the point.

Spotting Trends Like a Pro

Ever wish you had a crystal ball for trends? Quantitative analysis is the next best thing. It’s like having a trend-spotting superpower, revealing patterns that might have otherwise stayed hidden.

Bias Be Gone

Quantitative research takes bias out of the equation. Systematic data collection and statistical wizardry reduce researcher bias, leaving you with results that are as unbiased as a judge at a talent show.

Key Components of a Quantitative Research Study

Launching into a quantitative research study is like embarking on a thrilling quest, and guess what? You’re the hero of this research adventure! Let’s unravel the exciting components that make your study a blockbuster:

Quest-Starter: Research Question or Hypothesis

It’s your “once upon a time.” Kick off your research journey with a bang by crafting a captivating research question or hypothesis. This is the spark that ignites your curiosity.

Backstory Bonanza: Literature Review

Think of it as your research Netflix binge. Dive into existing literature for the backstory. It’s not just research – it’s drama, plot twists, and the foundation for your epic tale.

Blueprint Brilliance: Research Design

Time to draw up the plans for your study castle. Choose your research design – is it a grand experiment or a cunning observational scheme? Your design is the architectural genius behind your research.

Casting Call: Population and Sample

Who’s in your star-studded lineup? Define your dream cast – your target population – and then handpick a sample that’s ready for the research red carpet.

Gear Up: Data Collection Methods

Choose your research tools wisely – surveys, experiments, or maybe a bit of detective work. Your methods are like the gadgets in a spy movie, helping you collect the data treasures.

The Numbers Game: Variables and Measures

What’s in the spotlight? Identify your main characters – independent and dependent variables. Then, sprinkle in some measures to add flair and precision to your study.

Magic Analysis Wand: Data Analysis Techniques

Enter the wizardry zone! Pick your magic wand – statistical methods, tests, or software – and watch as it unravels the mysteries hidden in your data.

Ethical Superhero Cape: Ethical Considerations

Every hero needs a moral compass. Clearly outline how you’ll be the ethical superhero of your study, protecting the well-being and secrets of your participants.

Grand Finale: Results and Findings

It’s showtime! Showcase your results like the grand finale of a fireworks display. Tables, charts, and statistical dazzle – let your findings steal the spotlight.

Wrap-Up Party: Conclusion and Implications

Bring out the confetti! Summarize your findings, discuss their VIP status in the research world, and hint at the afterparty – how your results shape the future.

Behind-the-Scenes Blooper Reel: Limitations and Future Research

No Hollywood film is perfect. Share the bloopers – the limitations of your study – and hint at the sequel with ideas for future research. It’s all part of the cinematic journey.

Roll Credits: References

Give a shout-out to the supporting cast! Cite your sources – it’s the credits that add credibility to your blockbuster.

Bonus Scene: Appendix

Think of it as the post-credits scene. Tuck in any extra goodies – surveys, questionnaires, or behind-the-scenes material – for those eager to dive deeper into your research universe.

By weaving these storylines together, your quantitative research study becomes a cinematic masterpiece, leaving a lasting impact on the grand stage of academia. Happy researching, hero!

Quantitative Research Topics for STEM Students

Check out the best quantitative research topics for STEM students:-

• Investigating the Effects of Different Soil pH Levels on Plant Growth.
• Analyzing the Impact of Pesticide Exposure on Bee Populations.
• Studying the Genetic Variability in Endangered Species.
• Quantifying the Relationship Between Temperature and Microbial Growth in Water.
• Analyzing the Effects of Ocean Acidification on Coral Reefs.
• Investigating the Correlation Between Pollinator Diversity and Crop Yield.
• Studying the Role of Gut Microbiota in Human Health and Disease.
• Quantifying the Impact of Antibiotics on Soil Microbial Communities.
• Analyzing the Effects of Light Pollution on Nocturnal Animal Behavior.
• Investigating the Relationship Between Altitude and Plant Adaptations in Mountain Ecosystems.
• Measuring the Speed of Light Using Interferometry Techniques.
• Investigating the Quantum Properties of Photons in Quantum Computing.
• Analyzing the Factors Affecting Magnetic Field Strength in Electromagnets.
• Studying the Behavior of Superfluids at Ultra-Low Temperatures.
• Quantifying the Efficiency of Energy Transfer in Photovoltaic Cells.
• Analyzing the Properties of Quantum Dots for Future Display Technologies.
• Investigating the Behavior of Particles in High-Energy Particle Accelerators.
• Studying the Effects of Gravitational Waves on Space-Time.
• Quantifying the Frictional Forces on Objects at Different Surfaces.
• Analyzing the Characteristics of Dark Matter and Dark Energy in the Universe.

Engineering

• Optimizing the Design of Wind Turbine Blades for Maximum Efficiency.
• Investigating the Use of Smart Materials in Structural Engineering.
• Analyzing the Impact of 3D Printing on Prototyping in Product Design.
• Studying the Behavior of Composite Materials Under Extreme Temperatures.
• Evaluating the Efficiency of Water Treatment Plants in Removing Contaminants.
• Investigating the Aerodynamics of Drones for Improved Flight Control.
• Quantifying the Effects of Traffic Flow on Roadway Maintenance.
• Analyzing the Impact of Vibration Damping in Building Structures.
• Studying the Mechanical Properties of Biodegradable Polymers in Medical Devices.
• Investigating the Use of Artificial Intelligence in Autonomous Robotic Systems.

Mathematics

• Exploring Chaos Theory and Its Applications in Nonlinear Systems.
• Modeling the Spread of Infectious Diseases in Population Dynamics.
• Analyzing Data Mining Techniques for Predictive Analytics in Business.
• Studying the Mathematics of Cryptography Algorithms for Data Security.
• Quantifying the Patterns in Stock Market Price Movements Using Time Series Analysis.
• Investigating the Applications of Fractal Geometry in Computer Graphics.
• Analyzing the Behavior of Differential Equations in Climate Modeling.
• Studying the Optimization of Supply Chain Networks Using Linear Programming.
• Investigating the Mathematical Concepts Behind Machine Learning Algorithms.
• Quantifying the Patterns of Prime Numbers in Number Theory.
• Investigating the Chemical Mechanisms Behind Enzyme Catalysis.
• Analyzing the Thermodynamic Properties of Chemical Reactions.
• Studying the Kinetics of Chemical Reactions in Different Solvents.
• Quantifying the Concentration of Pollutants in Urban Air Quality.
• Evaluating the Effectiveness of Antioxidants in Food Preservation.
• Investigating the Electrochemical Properties of Batteries for Energy Storage.
• Studying the Behavior of Nanomaterials in Drug Delivery Systems.
• Analyzing the Chemical Composition of Exoplanet Atmospheres Using Spectroscopy.
• Quantifying Heavy Metal Contamination in Soil and Water Sources.
• Investigating the Correlation Between Chemical Exposure and Human Health.

Computer Science

• Analyzing Machine Learning Algorithms for Natural Language Processing.
• Investigating Quantum Computing Algorithms for Cryptography Applications.
• Studying the Efficiency of Data Compression Methods for Big Data Storage.
• Quantifying Cybersecurity Threats and Vulnerabilities in IoT Devices.
• Evaluating the Impact of Cloud Computing on Distributed Systems.
• Investigating the Use of Artificial Intelligence in Autonomous Vehicles.
• Analyzing the Behavior of Neural Networks in Deep Learning Applications.
• Studying the Performance of Blockchain Technology in Supply Chain Management.
• Quantifying User Behavior in Social Media Analytics.
• Investigating Quantum Machine Learning for Enhanced Data Processing.

These additional project ideas provide a diverse range of opportunities for STEM students to engage in quantitative research and explore various aspects of their respective fields. Each project offers a unique avenue for discovery and contribution to the world of science and technology.

What is an example of a quantitative research?

Quantitative research is a powerful investigative approach, wielding numbers to shed light on intricate relationships and phenomena. Let’s dive into an example of quantitative research to understand its workings:

Research Question

What is the correlation between the time students devote to studying and their academic grades?

Students who invest more time in studying are likely to achieve higher grades.

Research Design

Imagine a researcher embarking on a journey within a high school. They distribute surveys to students, inquiring about their weekly study hours and their corresponding grades in core subjects.

Data Analysis

Equipped with statistical tools, our researcher scrutinizes the collected data. Lo and behold, a significant positive correlation emerges—students who dedicate more time to studying generally earn higher grades.

With data as their guide, the researcher concludes that indeed, a relationship exists between study time and academic grades. The more time students commit to their studies, the brighter their academic stars tend to shine.

This example merely scratches the surface of quantitative research’s potential. It can delve into an extensive array of subjects and investigate complex hypotheses. Here are a few more examples:

• Assessing a New Drug’s Effectiveness: Quantifying the impact of a  novel medication  in treating a specific illness.
• Socioeconomic Status and Crime Rates: Investigating the connection between economic conditions and criminal activity.
• Analyzing the Influence of an Advertising Campaign on Sales: Measuring the effectiveness of a marketing blitz on product purchases.
• Factors Shaping Customer Satisfaction: Using data to pinpoint the elements contributing to customer contentment.
• Government Policies and Employment Rates: Evaluating the repercussions of new governmental regulations on job opportunities.

Quantitative research serves as a potent beacon, illuminating the complexities of our world through data-driven inquiry. Researchers harness its might to collect, analyze, and draw valuable conclusions about a vast spectrum of phenomena. It’s a vital tool for unraveling the intricacies of our universe. 

As we bid adieu to our whirlwind tour of quantitative research topics tailor-made for the STEM dreamers, it’s time to soak in the vast horizons that science, technology, engineering, and mathematics paint for us.

We’ve danced through the intricate tango of poverty and crime, peeked into the transformative realm of cutting-edge technologies, and unraveled the captivating puzzles of quantitative research. But these aren’t just topics; they’re open invitations to dive headfirst into the uncharted seas of knowledge.

To you, the STEM trailblazers, these research ideas aren’t mere academic pursuits. They’re portals to curiosity, engines of innovation, and blueprints for shaping the future of our world. They’re the sparks that illuminate the trail leading to discovery.

As you set sail on your research odyssey, remember that quantitative research isn’t just about unlocking answers—it’s about nurturing that profound sense of wonder, igniting innovation, and weaving your unique thread into the fabric of human understanding.

Whether you’re stargazing, decoding the intricate language of genes, engineering marvels, or tackling global challenges head-on, realize that your STEM and quantitative research journey is a perpetual adventure.

May your questions be audacious, your data razor-sharp, and your discoveries earth-shattering. Keep that innate curiosity alive, keep exploring, and let the spirit of STEM be your North Star, guiding you towards a future that’s not just brighter but brilliantly enlightened.

And with that, fellow adventurers, go forth, embrace the unknown, and let your journey in STEM be the epic tale that reshapes the narrative of tomorrow!

Frequently Asked Questions

How can i ensure the ethical conduct of my quantitative research project.

To ensure ethical conduct, obtain informed consent from participants, maintain data confidentiality, and adhere to ethical guidelines established by your institution and professional associations.

Are there any software tools recommended for data analysis in STEM research?

Yes, there are several widely used software tools for data analysis in STEM research, including R, Python, MATLAB, and SPSS. The choice of software depends on your specific research needs and familiarity with the tools.

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199+ Quantitative Research Topics For STEM Students to Try Now

Discover engaging Quantitative Research Topics for STEM Students – Explore the world of science, tech, engineering, and math with simplified, fascinating ideas.

Have you ever wondered how science, tech, and math shape our world? You’re not alone! STEM (Science, Technology, Engineering, and Math) is like a treasure chest of discoveries. And the best part? You can be part of it!

Our blog is your path to the exciting world of STEM. We aim to make it interesting, enjoyable, and simple to comprehend. No tricky words, no fancy talk – just simple and exciting stuff.

In this blog, we’ve collected the best quantitative research topics for stem students. Scientists use these numbers to answer questions, and it’s cool!

Do you enjoy learning? We’re here to spark your curiosity and hold your interest.

From exploring nature to solving tech puzzles and uncovering the universe’s secrets, we’ve got it all. Think of it as an adventure, with each topic leading to great discoveries.

So, get ready to dive into STEM.  Let’s learn and explore together, one topic at a time. Your STEM journey starts now!

What Is Quantitative Research? 

Quantitative research involves gathering and studying numerical data. It tries to measure things, count them, or put them into classes that can be counted. For example, a researcher might ask 100 people their age and gender. They would count how many men and women are present and work out the average age.

Quantitative research gives us numbers that help us see patterns, test theories, and predict things. The goal is to be accurate and get precise, measurable results that can be summarized numerically. This type of research aims to remove personal biases.

Tips To Choose Quantitative Research Topics For STEM Students

First, let’s find how to quantitative research topics for STEM students, and then we will move on to the project ideas.

Choose a Topic That Interests You

Picking a research topic you’re genuinely curious or passionate about makes the research process so much more engaging and rewarding. Choosing something that excites you motivates you to push through the hard work.

Look for Gaps in Existing Research

Review academic journals and existing research to find gaps where further study is needed. Look for topics where findings are contradictory or inconclusive. New research could help resolve differences or offer additional insights. Exploring open questions interests the research community.

Consider Real-World Applications

Consider how quantitative research could inform products, services, policies, and processes to improve them. Research with practical implications beyond academia tends to be impactful and worthwhile.

Ensure Quantitative Methods Apply

Not all topics lend themselves well to quantitative analysis. Assess whether statistical numerical methods will work for your research question. If not, qualitative methods may be better.

Find a Unique Angle

Avoid research topics that have already been extensively studied from every angle. Look for a creative, novel way to approach the topic that hasn’t been done before. This will ensure your work is original.

Talk to Knowledgeable People

Discuss ideas with professors, peers, and academics knowledgeable about your field. They might identify poorly researched topics or suggest exciting questions for further inquiry.

Review Coursework

Look back at class assignments, readings, lectures, and textbooks. Note down any topics that stood out as warranting deeper investigation. Build off classwork.

Choose a Manageable Scope

Ensure your topic is focused enough to tackle within the time and resources you have. Overly, broad topics become unmanageable. Define a clear, concise research question.

It is time to uncover the best quantitative research topics for STEM students.

199+ Best Quantitative Research Topics For STEM Students

These are the top most interesting Quantitative Research Topics For STEM Students.

You’ll receive better grades as a result of that.

Biology Quantitative Research Topics For STEM Students

• How do different fertilizers affect how plants grow?
• Does temperature change how fast enzymes work?
• What is the variety of life like in a particular ecosystem over time?
• What genetics underlie a rare disease?
• Is there a link between diet and chronic illness?
• Do some antibiotics work better on bacteria?
• How does pollution impact water life in cities?
• Is there a connection between stress and the immune system?
• How do different fungi grow?
• Do night and day animals behave differently?

Chemistry Quantitative Research Topics For STEM Students

• What affects how fast chemical reactions occur?
• What’s in household cleaners?
• How do catalysts change hydrogen peroxide breakdown?
• How do polymers act in different environments?
• Can different salts dissolve in water?
• What are pH levels like in natural waters?
• Does temperature affect gas density?
• How do acids and bases neutralize?
• How does cooking change food chemicals?
• Do antioxidants help preserve food?

Physics Quantitative Research Topics For STEM Students

• How does light’s angle change reflection?
• What affects a pendulum’s swing?
• How do magnets work in different materials?
• What makes solar cells efficient?
• How do objects move in gravity?
• What affects the speed of sound?
• Does air resistance affect falling objects?
• How do particle states differ?
• Are superconductors different at low temperatures?
• Does heat change electrical conductivity?

Computer Science Quantitative Research Topics For STEM Students

• Do programming languages affect efficiency?
• What security holes exist in operating systems?
• What algorithms sort data best?
• How can network routing be optimized?
• How well do encryption methods secure data?
• Can machine learning ID images?
• Does parallel processing speed computing?
• How do data structures affect memory?
• What makes a good app interface?
• Can cybersecurity tools spot threats?

Environmental Science Quantitative Research Topics For STEM Students

• Does deforestation change the local climate?
• Can recycling reduce waste?
• How does urban growth impact wildlife?
• Is there a link between pollution and illness?
• Do renewable energies cut emissions?
• How does water quality differ between cities and rural areas?
• Are oceans and coral bleaching connected?
• How does climate change impact plants?
• How well do wastewater treatments work?
• How do invasive species affect ecosystems?

Mathematics Quantitative Research Topics For STEM Students

• Are there patterns in prime numbers?
• What are the properties of fractals?
• How are lottery numbers distributed?
• How does math relate to the real world?
• Can math model disease spread?
• How well do integration methods work?
• How do calculus sequences and series behave?
• What are geometrical shape properties?
• How does graph theory apply to social networks?
• Can statistics analyze voting patterns?

Engineering Quantitative Research Topics For STEM Students

• How efficient are renewable energies?
• What building materials are sturdiest?
• What aircraft designs are most aerodynamic?
• How stable are different bridge types?
• Can materials help purify water?
• What irrigation systems work best in agriculture?
• How do cities’ transit systems compare?
• What cooling systems work best for electronics?
• What car safety features work best?
• What construction methods are most sustainable?

Health Sciences Quantitative Research Topics For STEM Students

• Is exercise linked to heart health?
• How do diets affect weight loss?
• Do sleep patterns affect thinking?
• How well do vaccines work?
• Do genes influence disease risk?
• Which physical therapies work best?
• Is there a link between air quality and respiratory health?
• How does stress management affect mental health?
• Does telemedicine improve outcomes?
• Can wearables effectively monitor vital signs?

Geology Quantitative Research Topics For STEM Students

• What Geological Factors Cause Earthquakes?
• How do rocks erode?
• How does volcanism impact ecosystems?
• What’s the history of a region?
• Does climate change affect glaciers?
• How has sea level changed over time?
• What minerals are in different soils?
• How do caves form?
• How does geology affect groundwater?
• How does geology relate to resource extraction?

Materials Science Quantitative Research Topics For STEM Students

• How do semiconductors conduct electricity?
• What coatings are most durable?
• Which insulators resist heat flow?
• What magnetic properties are helpful in electronics?
• How does radiation affect spacecraft materials?
• How do materials change under stress?
• What alloys resist corrosion?
• What can nanomaterials do?
• How do polymers behave in different environments?
• What properties have 3D printed materials?

Astronomy Quantitative Research Topics For STEM Students

• What are the properties of exoplanets?
• How do solar system bodies interact?
• How do stars evolve and affect galaxies?
• What does cosmic microwave radiation reveal about the early universe?
• What are black holes’ properties and gravitational effects?
• How fast is the universe expanding?
• What is dark matter?
• What have telescopes revealed about the universe?
• What are the planets’ geological features?
• Could there be life on Mars or Europa?

Robotics Quantitative Research Topics For STEM Students

• What locomotion mechanisms work best in robots?
• How can swarm robotics enable collaboration?
• How is AI being developed for autonomous robots?
• How are robotic arms designed and controlled?
• How are robots used in disaster response?
• Are robot-assisted surgeries effective?
• What are the ethics of AI robots?
• How do autonomous vehicles behave?
• How are robots used in space?
• Could humans and robots productively collaborate?

Social Sciences Quantitative Research Topics For STEM Students

• How does social media affect relationships?
• What parenting styles influence child development?
• Is there a link between socioeconomics and education?
• How does culture influence behavior?
• What psychology underlies online consumerism?
• Can interventions reduce addiction?
• What is the impact of immigration policies?
• How do people cope after crises?
• Can social programs reduce poverty?
• How do gender and identity affect workplaces?

Economics Quantitative Research Topics For STEM Students

• How does inflation relate to economic growth?
• How do fiscal policies affect income inequality?
• What tax systems generate the most revenue?
• What are the economic effects of trade deals?
• What drives e-commerce purchases?
• Do environmental policies improve economic outcomes?
• How do interest rates affect investment?
• What are the economic impacts of healthcare reforms?
• How does technology affect labor markets?
• What is the global impact of financial crises?

Agriculture Quantitative Research Topics For STEM Students

• What irrigation methods work best?
• How does climate change impact crop yields?
• Can organic farming improve soil health?
• What genetic traits confer pest/disease resistance?
• What environmental effects do farming techniques have?
• How do growing conditions alter nutritional value?
• Can data analytics and precision agriculture improve yields?
• Are small farms economically sustainable?
• How do supply chain issues impact food security?
• Could vertical farming work in cities?

Quantitative Research Topic Ideas For STEM Students In The Philippines:

• Typhoon Training and Resilience
• Air Quality in Manila
• Online Learning and Math Scores
• Solar Power in Rural Villages
• Food and School Performance
• Local Plants for Medicine
• Water Quality in Rivers
• Mangroves and Coastal Protection
• Dengue Fever in Cities
• Waste Management in Cities

Experimental Quantitative Research Topics For STEM Students

• Testing Bridge Designs
• Wind Turbine Prototype Efficiency
• Battery Storage Capacity
• Water Filtration Methods
• Crop Growth With Organic Fertilizers
• Material Strength Under Stress
• Rocket Engine Performance
• Artificial Intelligence Image Recognition
• Electric Car Energy Use
• Greenhouse Gas Reduction Strategies

30 Quantitative Research Topic Ideas For STEM Students

• Investigating the properties and applications of novel materials created through 3D printing.
• Studying the effectiveness of virtual reality simulations for medical training programs.
• Analyzing the feasibility and methods for mineral extraction from asteroids.
• Developing machine learning algorithms to improve navigation in self-driving cars.
• Testing the use of drone systems for disaster response and relief operations.
• Implementing augmented reality to enhance manufacturing and assembly processes.
• Evaluating efficiency and optimal positioning for offshore wind farms.
• Comparing methods and materials for recycling different types of plastics.
• Examining the unique properties of graphene for uses in electronics and composites.
• Assessing the risks and solutions for commercial space travel programs.
• Designing and deploying rainwater harvesting systems in urban environments.
• Creating biodegradable packaging materials from sustainable sources.
• Building neural networks to predict stock market trends and patterns.
• Using aquaponics systems for urban farming in limited spaces.
• Leveraging AI algorithms for early detection of diseases like cancer.
• Developing applications to take advantage of quantum computing breakthroughs.
• Analyzing Martian soil for viability in growing crops for future colonies.
• Optimizing traffic flow patterns on highways to reduce congestion.
• Evaluating energy use and optimization in smartphones and devices.
• Converting ocean wave energy into usable electricity.
• Printing 3D biocompatible tissues and organs for transplants.
• Improving cybersecurity through new encryption and authentication techniques.
• Using solar power to operate desalination systems for clean water access.
• Editing plant genes with CRISPR to improve crop yields.
• Building fully electric aircraft for regional commercial flights.
• Using tiny microrobots for targeted drug delivery and therapies.
• Developing robotic exoskeletons to improve mobility for disabled individuals.
• Implementing blockchain technology to securely track global supply chains.
• Designing floating wind turbines for offshore energy generation.
• Creating a hyperloop system for high-speed terrestrial transportation.

Final Thoughts,

In conclusion, quantitative research is valuable for STEM students. It lets them test ideas using statistics, experiments, and measurable data. This allows students to move beyond theory and into evidence-based findings. With quantitative methods, students can verify ideas and expand their knowledge. 

Mastering these methods prepares STEM students to innovate and lead in the future. However, they must use quantitative research ethically and objectively. If used properly, it can lead to discoveries that advance STEM fields. Quantitative research gives STEM students concrete insights to deepen their scientific understanding. 

The numeric precision of quantitative data enables final conclusions to be drawn. By learning quantitative skills, STEM students position themselves at the forefront of creation. Yet, they must analyze results in a balanced way. Overall, quantitative research is a strong tool that can unlock breakthroughs when utilized judiciously.

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200 Quantitative Research Title for Stem Students

Are you a STEM (Science, Technology, Engineering, and Mathematics) student looking for inspiration for your next research project? You’re in the right place! Quantitative research involves gathering numerical data to answer specific questions, and it’s a fundamental part of STEM fields. To help you get started on your research journey, we’ve compiled a list of 200 quantitative research title for stem students. These titles span various STEM disciplines, from biology to computer science. Whether you’re an undergraduate or graduate student, these titles can serve as a springboard for your research ideas.

Biology and Life Sciences

• The Impact of pH Levels on Microbial Growth
• Examining the Impact of Temperature on Enzyme Activity.
• Investigating the Relationship Between Genetics and Obesity
• Exploring the Diversity of Microorganisms in Soil Samples
• Quantifying the Impact of Pesticides on Aquatic Ecosystems
• Studying the Effect of Light Exposure on Plant Growth
• Analyzing the Efficiency of Antibiotics on Bacterial Infections
• Investigating the Relationship Between Blood Type and Disease Susceptibility
• Evaluating the Effects of Different Diets on Lifespan in Fruit Flies
• Evaluating the Influence of Air Pollution on Respiratory Health.
• Determining the Kinetics of Chemical Reactions
• Investigating the Conductivity of Various Ionic Solutions
• Analyzing the Effects of Temperature on Gas Solubility
• Studying the Corrosion Rate of Metals in Different Environments
• Quantifying the Concentration of Heavy Metals in Water Sources
• Evaluating the Efficiency of Photocatalytic Materials in Water Purification
• Examining the Thermodynamics of Electrochemical Cells
• Investigating the Effect of pH on Acid-Base Titrations
• Analyzing the Composition of Natural and Synthetic Polymers
• Assessing the Chemical Properties of Nanoparticles
• Measuring the Speed of Light Using Interferometry
• Studying the Behavior of Electromagnetic Waves in Different Media
• Investigating the Relationship Between Mass and Gravitational Force
• Analyzing the Efficiency of Solar Cells in Energy Conversion
• Examining Quantum Entanglement in Photon Pairs
• Quantifying the Heat Transfer in Different Materials
• Evaluating the Efficiency of Wind Turbines in Energy Production
• Studying the Elasticity of Materials Through Stress-Strain Analysis
• Analyzing the Effects of Magnetic Fields on Particle Motion
• Investigating the Behavior of Superconductors at Low Temperatures

Mathematics

• Exploring Patterns in Prime Numbers
• Analyzing the Distribution of Random Variables
• Investigating the Properties of Fractals in Geometry
• Evaluating the Efficiency of Optimization Algorithms
• Studying the Dynamics of Differential Equations
• Quantifying the Growth of Cryptocurrency Markets
• Analyzing Network Theory and its Applications
• Investigating the Complexity of Sorting Algorithms
• Assessing the Predictive Power of Machine Learning Models
• Examining the Distribution of Prime Factors in Large Numbers

Computer Science

• Evaluating the Performance of Encryption Algorithms
• Analyzing the Efficiency of Data Compression Techniques
• Investigating Cybersecurity Threats in IoT Devices
• Quantifying the Impact of Code Refactoring on Software Quality
• Studying the Behavior of Neural Networks in Image Recognition
• Analyzing the Effectiveness of Natural Language Processing Models
• Investigating the Relationship Between Software Bugs and Development Methods
• Evaluating the Efficiency of Blockchain Consensus Mechanisms
• Assessing the Privacy Implications of Social Media Data Mining
• Studying the Dynamics of Online Social Networks

Engineering

• Analyzing the Structural Integrity of Bridges Under Load
• Investigating the Efficiency of Renewable Energy Systems
• Quantifying the Performance of Water Filtration Systems
• Evaluating the Durability of 3D-Printed Materials
• Studying the Aerodynamics of Drone Design
• Analyzing the Impact of Noise Pollution on Urban Environments
• Investigating the Efficiency of Heat Exchangers in HVAC Systems
• Assessing the Safety of Autonomous Vehicles in Real-world Scenarios
• Exploring the Applications of Artificial Intelligence in Robotics
• Investigating Material Behavior in Extreme Conditions.

Environmental Science

• Assessing the Effect of Climate Change on Wildlife Migration.
• Analyzing the Effect of Deforestation on Carbon Sequestration
• Investigating the Relationship Between Air Quality and Human Health
• Quantifying the Rate of Soil Erosion in Different Landscapes
• Analyzing the Impacts of Ocean Acidification on Coral Reefs.
• Assessing the Efficiency of Waste-to-Energy Conversion Technologies
• Analyzing the Impact of Urbanization on Local Microclimates
• Investigating the Effect of Oil Spills on Aquatic Ecosystems
• Assessing the Effectiveness of Endangered Species Conservation Initiatives.
• Studying the Dynamics of Ecological Communities

Astronomy and Space Sciences

• Measuring the Orbits of Exoplanets Using Transit Photometry
• Investigating the Formation of Stars in Nebulae
• Analyzing the Characteristics of Black Holes
• Exploring the Characteristics of Cosmic Microwave Background Radiation.
• Quantifying the Distribution of Dark Matter in Galaxies
• Assessing the Effects of Space Weather on Satellite Communications
• Evaluating the Potential for Asteroid Mining
• Investigating the Habitability of Exoplanets in the Goldilocks Zone
• Analyzing Gravitational Waves from Neutron Star Collisions
• Investigating the Evolution of Galaxies Across Cosmic Eras.

Health Sciences

• Evaluating the Impact of Exercise on Cardiovascular Health
• Analyzing the Relationship Between Diet and Diabetes
• Investigating the Efficacy of Vaccination Programs
• Quantifying the Psychological Effects of Social Media Use
• Studying the Genetics of Neurodegenerative Diseases
• Analyzing the Effects of Meditation on Stress Reduction
• Investigating the Correlation Between Sleep Patterns and Mental Health
• Assessing the Influence of Environmental Factors on Allergies
• Evaluating the Effectiveness of Telemedicine in Patient Care
• Studying the Health Disparities Among Different Demographic Groups

Materials Science

• Analyzing the Properties of Carbon Nanotubes for Nanoelectronics
• Investigating the Thermal Conductivity of Advanced Ceramics
• Quantifying the Strength of Composite Materials
• Studying the Optical Properties of Quantum Dots
• Evaluating the Biocompatibility of Biomaterials for Implants
• Investigating the Phase Transitions in Perovskite Materials
• Analyzing the Mechanical Behavior of Shape Memory Alloys
• Assessing the Corrosion Resistance of Coatings on Metals
• Studying the Electrical Conductivity of Polymer Blends
• Exploring the Superconducting Properties of High-Temperature Superconductors

Earth Sciences

• Assessing the Influence of Volcanic Eruptions on Climate.
• Analyzing the Geological Processes Shaping Earth’s Surface
• Investigating the Seismic Activity in Subduction Zones
• Quantifying the Rate of Glacial Retreat in Polar Regions
• Studying the Formation of Earthquakes Along Fault Lines
• Analyzing the Changes in Ocean Circulation Due to Climate Change
• Investigating the Effects of Urbanization on Groundwater Quality
• Assessing the Risk of Landslides in Hilly Terrain
• Evaluating the Impact of Coastal Erosion on Communities
• Studying the Behavior of Hurricanes in Different Oceanic Basins

Social Sciences and Economics

• Analyzing the Economic Impact of Natural Disasters
• Investigating the Relationship Between Education and Income
• Quantifying the Effects of Public Health Policies on Disease Spread
• Studying the Demographic Changes in Aging Populations
• Evaluating the Effects of Gender Diversity on Corporate Performance
• Analyzing the Influence of Social Media on Political Behavior
• Investigating the Correlation Between Happiness and Economic Growth
• Assessing the Factors Affecting Consumer Buying Behavior
• Studying the Dynamics of International Trade Flows
• Exploring the Effects of Income Inequality on Social Mobility

Robotics and Artificial Intelligence

• Evaluating the Performance of Reinforcement Learning Algorithms in Robotics
• Analyzing the Efficiency of Autonomous Navigation Systems
• Investigating Human-Robot Interaction in Collaborative Environments
• Quantifying the Accuracy of Object Detection Algorithms
• Studying the Ethics of Autonomous AI Decision-Making
• Analyzing the Robustness of Machine Learning Models to Adversarial Attacks
• Investigating the Use of AI in Healthcare Diagnosis
• Assessing the Impact of AI on Job Markets
• Evaluating the Efficiency of Natural Language Processing in Chatbots
• Studying the Potential for AI to Enhance Education

Energy and Sustainability

• Examining the Environmental Consequences of Renewable Energy Sources.
• Investigating the Efficiency of Energy Storage Systems
• Quantifying the Benefits of Green Building Technologies
• Studying the Effects of Carbon Pricing on Emissions Reduction
• Examining the Prospect for Carbon Capture and Storage
• Assessing the Sustainability of Food Production Systems
• Investigating the Impact of Electric Vehicles on Urban Air Quality
• Analyzing the Energy Consumption Patterns in Smart Cities
• Studying the Feasibility of Hydrogen as a Clean Energy Carrier
• Exploring Sustainable Agriculture Practices for Crop Yield Improvement

Neuroscience and Psychology

• Evaluating the Cognitive Effects of Video Game Play
• Analyzing Brain Activity During Decision-Making Processes
• Investigating the Neural Correlates of Emotional Regulation
• Quantifying the Impact of Music on Brain Function
• Analyzing the Outcomes of Mindfulness Meditation on Anxiety
• Analyzing Sleep Patterns and Memory Consolidation
• Investigating the Relationship Between Neurotransmitters and Mood
• Assessing the Neural Basis of Addiction
• Evaluating the Effects of Trauma on Brain Structure
• Studying the Brain’s Response to Virtual Reality Environments

Mechanical Engineering

• Analyzing the Efficiency of Heat Exchangers in Power Plants
• Investigating the Wear and Tear of Mechanical Bearings
• Quantifying the Vibrations in Mechanical Systems
• Studying the Aerodynamics of Wind Turbine Blades
• Evaluating the Frictional Properties of Lubricants
• Assessing the Efficiency of Cooling Systems in Electronics
• Investigating the Performance of Internal Combustion Engines
• Analyzing the Impact of Additive Manufacturing on Product Development
• Studying the Dynamics of Fluid Flow in Pipelines
• Exploring the Behavior of Composite Materials in Aerospace Structures

Biomedical Engineering

• Evaluating the Biomechanics of Human Joint Replacements
• Analyzing the Performance of Wearable Health Monitoring Devices
• Investigating the Biocompatibility of 3D-Printed Medical Implants
• Quantifying the Drug Release Rates from Biodegradable Polymers
• Studying the Efficiency of Drug Delivery Systems
• Assessing the Use of Nanoparticles in Cancer Therapies
• Investigating the Biomechanics of Tissue Engineering Constructs
• Analyzing the Effects of Electrical Stimulation on Nerve Regeneration
• Evaluating the Mechanical Properties of Artificial Heart Valves
• Studying the Biomechanics of Human Movement

Civil and Environmental Engineering

• Analyzing the Structural Behavior of Tall Buildings in Seismic Zones
• Investigating the Efficiency of Stormwater Management Systems
• Quantifying the Impact of Green Infrastructure on Urban Flooding
• Studying the Behavior of Soils in Slope Stability Analysis
• Evaluating the Performance of Water Treatment Plants
• Assessing the Sustainability of Transportation Systems
• Investigating the Effects of Climate Change on Infrastructure Resilience
• Analyzing the Environmental Impact of Construction Materials
• Studying the Dynamics of River Sediment Transport
• Exploring the Use of Smart Materials in Civil Engineering Applications

Chemical Engineering

• Evaluating the Efficiency of Chemical Reactors in Pharmaceutical Production
• Analyzing the Mass Transfer Rates in Membrane Separation Processes
• Investigating the Effects of Catalysis on Chemical Reactions
• Quantifying the Kinetics of Polymerization Reactions
• Studying the Thermodynamics of Gas-Liquid Absorption Processes
• Assessing the Efficiency of Adsorption-Based Carbon Capture
• Investigating the Rheological Properties of Non-Newtonian Fluids
• Analyzing the Effects of Surfactants on Foam Stability
• Studying the Mass Transport in Microfluidic Devices
• Exploring the Synthesis of Nanomaterials for Energy Applications

Electrical and Electronic Engineering

• Analyzing the Efficiency of Power Electronics in Electric Vehicles
• Investigating the Performance of Wireless Communication Systems
• Quantifying the Power Consumption of IoT Devices
• Studying the Reliability of Printed Circuit Boards
• Evaluating the Efficiency of Photovoltaic Inverters
• Assessing the Electromagnetic Compatibility of Electronic Devices
• Investigating the Behavior of Antenna Arrays in Beamforming
• Analyzing the Power Quality in Electrical Grids
• Studying the Security of IoT Networks
• Exploring the Use of Machine Learning in Signal Processing

These 200 quantitative research titles offer a diverse array of options to inspire your next STEM research endeavor. Always remember to select a subject that truly captivates your interest and curiosity, as your enthusiasm and curiosity will drive your research to new heights. Good luck with your research journey, STEM student!

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	STEM Science, Technology Engineering, and Mathematics (STEM) is one of the most talked about topics in education, emphasizing research, problem solving, critical thinking, and creativity. The following compendium of open-access articles are inclusive of all substantive AERA journal content regarding STEM published since 1969. This page will be updated as new articles are published.  Jason Jabbari, Yung Chun, Wenrui Huang, Stephen Roll October 2023 Researchers found that program acceptance was significantly associated with increased earnings and probabilities of working in a science, technology, engineering, and math (STEM) profession. Robert R. Martinez, Jr., James M. Ellis September 2023 Researchers found that STEM-CR involves four related yet distinct dimensions of Think, Know, Act, and Go. Results also demonstrated soundness of these STEM-CR dimensions by race and gender (key learning skills and techniques/Act). Rosemary J. Perez, Rudisang Motshubi, Sarah L. Rodriguez April 2023 Researchers found that because participants did not attend to how racism and White supremacy fostered negative climate, their strategies (e.g., increased recruitment, committees, workshops) left systemic racism intact and (un)intentionally amplified labor for racially minoritized graduate students and faculty champions who often led change efforts with little support. Kathleen Lynch, Lily An, Zid Mancenido , July 2022 Researchers found an average weighted impact estimate of +0.10 standard deviations on mathematics achievement outcomes. Luis A. Leyva, R. Taylor McNeill, B R. Balmer, Brittany L. Marshall, V. Elizabeth King, Zander D. Alley , May 2022 Researchers address this research gap by exploring four Black queer students’ experiences of oppression and agency in navigating invisibility as STEM majors. Angela Starrett, Matthew J. Irvin, Christine Lotter, Jan A. Yow , May 2022 Researchers found that the more place-based workforce development adolescents reported, the higher their expectancy beliefs, STEM career interest, and rural community aspirations. Matthew H. Rafalow, Cassidy Puckett May 2022 Researchers found that educational resources, like digital technologies, are also sorted by schools. Pamela Burnard, Laura Colucci-Gray, Carolyn Cooke  April 2022 This article makes a case for repositioning STEAM education as democratized enactments of transdisciplinary education, where arts and sciences are not separate or even separable endeavors. Salome Wörner, Jochen Kuhn, Katharina Scheiter , April 2022 Researchers conclude that for combining real and virtual experiments, apart from the individual affordances and the learning objectives of the different experiment types, especially their specific function for the learning task must be considered. Seung-hyun Han, Eunjung Grace Oh, Sun “Pil” Kang April 2022 Researchers found that the knowledge sharing mechanism and student learning outcomes can be explained in terms of their social capital within social networks. Barbara Schneider, Joseph Krajcik, Jari Lavonen, Katariina Salmela-Aro, Christopher Klager, Lydia Bradford, I-Chien Chen, Quinton Baker, Israel Touitou, Deborah Peek-Brown, Rachel Marias Dezendorf, Sarah Maestrales, Kayla Bartz March 2022  Researchers found that improving secondary school science learning is achievable with a coherent system comprising teacher and student learning experiences, professional learning, and formative unit assessments that support students in “doing” science. Paulo Tan, Alexis Padilla, Rachel Lambert , March 2022 Researchers found that studies continue to avoid meaningful intersectional considerations of race and disability. Ta-yang Hsieh, Sandra D. Simpkins March 2022 Researchers found patterns with overall high/low beliefs, patterns with varying levels of motivational beliefs, and patterns characterized by domain differentiation. Jonté A. Myers, Bradley S. Witzel, Sarah R. Powell, Hongli Li, Terri D. Pigott, Yan Ping Xin, Elizabeth M. Hughes , February 2022 Findings of meta-regression analyses showed several moderators, such as sample composition, group size, intervention dosage, group assignment approach, interventionist, year of publication, and dependent measure type, significantly explained heterogeneity in effects across studies. Grace A. Chen, Ilana S. Horn , January 2022 The findings from this review highlight the interconnectedness of structures and individual lives, of the material and ideological elements of marginalization, of intersectionality and within-group heterogeneity, and of histories and institutions. Victor R. Lee, Michelle Hoda Wilkerson, Kathryn Lanouette December 2021 Researchers offer an interdisciplinary framework based on literature from multiple bodies of educational research to inform design, teaching and research for more effective, responsible, and inclusive student learning experiences with and about data. Ido Davidesco, Camillia Matuk, Dana Bevilacqua, David Poeppel, Suzanne Dikker December 2021 This essay critically evaluates the value added by portable brain technologies in education research and outlines a proposed research agenda, centered around questions related to student engagement, cognitive load, and self-regulation. Guan K. Saw, Charlotte A. Agger December 2021 Researchers found that during high school rural and small-town students shifted away from STEM fields and that geographic disparities in postsecondary STEM participation were largely explained by students’ demographics and precollege STEM career aspirations and academic preparation. Kyle M. Whitcomb, Sonja Cwik, Chandralekha Singh November 2021 Researchers found that on average across all years of study, underrepresented minority (URM) students experience a larger penalty to their mean overall and STEM GPA than even the most disadvantaged non-URM students. Lana M. Minshew, Amanda A. Olsen, Jacqueline E. McLaughlin , October 2021 Researchers found that the CA framework is a useful and effective model for supporting faculty in cultivating rich learning opportunities for STEM graduate students. Xin Lin, Sarah R. Powell , October 2021 Findings suggested fluency in both mathematics and reading, as well as working memory, yielded greater impacts on subsequent mathematics performance. Christine L. Bae, Daphne C. Mills, Fa Zhang, Martinique Sealy, Lauren Cabrera, Marquita Sea , September 2021 This systematic literature review is guided by a complex systems framework to organize and synthesize empirical studies of science talk in urban classrooms across individual (student or teacher), collective (interpersonal), and contextual (sociocultural, historical) planes. Toya Jones Frank, Marvin G. Powell, Jenice L. View, Christina Lee, Jay A. Bradley, Asia Williams  August/September 2021 Researchers found that teachers’ experiences of microaggressions accounted for most of the variance in our modeling of teachers’ thoughts of leaving the profession. Ebony McGee, Yuan Fang, Yibin (Amanda) Ni, Thema Monroe-White August 2021 Researchers found that 40.7% of the respondents reported that their career plans have been affected by Trump’s antiscience policies, 54.5% by the COVID-19 pandemic. Martha Cecilia Bottia, Roslyn Arlin Mickelson, Cayce Jamil, Kyleigh Moniz, Leanne Barry , May 2021 Consistent with cumulative disadvantage and critical race theories, findings reveal that the disproportionality of racially minoritized students in STEM is related to their inferior secondary school preparation; the presence of racialized lower quality educational contexts; reduced levels of psychosocial factors associated with STEM success; less exposure to inclusive and appealing curricula and instruction; lower levels of family social, cultural, and financial capital that foster academic outcomes; and fewer prospects for supplemental STEM learning opportunities. Policy implications of findings are discussed. Iris Daruwala, Shani Bretas, Douglas D. Ready  April 2021 Researchers describe how teachers, school leaders, and program staff navigated institutional pressures to improve state grade-level standardized test scores while implementing tasks and technologies designed to personalize student learning. Michael A. Gottfried, Jay Plasman, Jennifer A. Freeman, Shaun Dougherty March 2021 Researchers found that students with learning disabilities were more likely to earn more units in CTE courses compared with students without disabilities. Ebony Omotola McGee  December 2020 This manuscript also discusses how universities institutionalize diversity mentoring programs designed mostly to fix (read “assimilate”) underrepresented students of color while ignoring or minimizing the role of the STEM departments in creating racially hostile work and educational spaces. Miray Tekkumru-Kisa, Mary Kay Stein, Walter Doyle  November 2020 The purpose of this article is to revisit theory and research on tasks, a construct introduced by Walter Doyle nearly 40 years ago. Elizabeth S. Park, Federick Ngo November 2020 Researchers found that lower math placement may have supported women, and to a lesser extent URM students, in completing transferable STEM credits. Karisma Morton, Catherine Riegle-Crumb  August/September 2020 Results of regression analyses reveal that, net of school, teacher, and student characteristics, the time that teachers report spending on algebra and more advanced content in eighth grade algebra classes is significantly lower in schools that are predominantly Black compared to those that are not predominantly minority. Implications for future research are discussed. Qi Zhang, Jessaca Spybrook, Fatih Unlu , July 2020 Researchers consider strategies to maximize the efficiency of the study design when both student and teacher effects are of primary interest. Jennifer Lin Russell, Richard Correnti, Mary Kay Stein, Ally Thomas, Victoria Bill, Laurie Speranzo , July 20, 2020 Analysis of videotaped coaching conversations and teaching events suggests that model-trained coaches improved their capacity to use a high-leverage coaching practice—deep and specific prelesson planning conversations—and that growth in this practice predicted teaching improvement, specifically increased opportunities for students to engage in conceptual thinking. Maithreyi Gopalan, Kelly Rosinger, Jee Bin Ahn , April 21, 2020 The overarching purpose of this chapter is to explore and document the growth, applicability, promise, and limitations of quasi-experimental research designs in education research. Thomas M. Philip, Ayush Gupta , April 21, 2020 By bringing this collection of articles together, this chapter provides collective epistemic and empirical weight to claims of power and learning as co-constituted and co-constructed through interactional, microgenetic, and structural dynamics. Steve Graham, Sharlene A. Kiuhara, Meade MacKay , March 19, 2020 This meta-analysis examined if students writing about content material in science, social studies, and mathematics facilitated learning. Janina Roloff, Uta Klusmann, Oliver Lüdtke, Ulrich Trautwein , January 2020  Multilevel regression analyses revealed that agreeableness, high school GPA, and the second state examination grade predicted teachers’ instructional quality. : Contemporary Views on STEM Subjects and Language With English Learners Okhee Lee, Amy Stephens , 2020  With the release of the consensus report , the authors highlight foundational constructs and perspectives associated with STEM subjects and language with English learners that frame the report. Angela Calabrese Barton and Edna Tan , 2020  This essay presents a rightful presence framework to guide the study of teaching and learning in justice-oriented ways. Day Greenberg, Angela Calabrese Barton, Carmen Turner, Kelly Hardy, Akeya Roper, Candace Williams, Leslie Rupert Herrenkohl, Elizabeth A. Davis, Tammy Tasker , 2020 Researchers  report on how one community builds capacity for disrupting injustice and supporting each other during the COVID-19 crisis. Tatiana Melguizo, Federick Ngo , 2020 This study explores the extent to which “college-ready” students, by high school standards, are assigned to remedial courses in college. Karisma Morton and Catherine Riegle-Crumb , 2020 Results of regression analyses reveal that, net of school, teacher, and student characteristics, the time that teachers report spending on algebra and more advanced content in eighth grade algebra classes is significantly lower in schools that are predominantly Black compared to those that are not predominantly minority. Implications for future research are discussed. Jonathan D. Schweig, Julia H. Kaufman, and V. Darleen Opfer , 2020 Researchers found that there are both substantial fluctuations in students’ engagement in these practices and reported cognitive demand from day to day, as well as large differences across teachers. David Blazar and Casey Archer , 2020 Researchers found that exposure to “ambitious” mathematics practices is more strongly associated with test score gains of English language learners compared to those of their peers in general education classrooms. Megan Hopkins, Hayley Weddle, Maxie Gluckman, Leslie Gautsch , December 2019  Researchers show how both researchers and practitioners facilitated research use. Adrianna Kezar, Samantha Bernstein-Sierra , October 2019 Findings suggest that Association of American Universities’ influence was a powerful motivator for institutions to alter deeply ingrained perceptions and behaviors. Denis Dumas, Daniel McNeish, Julie Sarama, Douglas Clements , October 2019 While students who receive a short-term intervention in preschool may not differ from a control group in terms of their long-term mathematics outcomes at the end of elementary school, they do exhibit significantly steeper growth curves as they approach their eventual skill level. Jessica Thompson, Jennifer Richards, Soo-Yean Shim, Karin Lohwasser, Kerry Soo Von Esch, Christine Chew, Bethany Sjoberg, Ann Morris , September 2019 Researchers used data from professional learning communities to analyze pathways into improvement work and reflective data to understand practitioners’ perspectives. Ross E. O’Hara, Betsy Sparrow , September 2019 Results indicate that interventions that target psychosocial barriers experienced by community college STEM students can increase retention and should be considered alongside broader reforms. Ran Liu, Andrea Alvarado-Urbina, Emily Hannum , September 2019 Findings reveal disparate national patterns in gender gaps across the performance distribution. Adam Kirk Edgerton , September 2019  Through an analysis of 52 interviews with state, regional, and district officials in California, Texas, Ohio, Pennsylvania, and Massachusetts, the author investigates the decline in the popularity of K–12 standards-based reform. Amy Noelle Parks , September 2019  The study suggests that more research needs to represent mathematics lessons from the perspectives of children and youth, particularly those students who engage with teachers infrequently or in atypical ways. Rajeev Darolia, Cory Koedel, Joyce B. Main, J. Felix Ndashimye, Junpeng Yan , September 30, 2019 Researchers found that differential access to high school courses does not affect postsecondary STEM enrollment or degree attainment. Laura A. Davis, Gregory C. Wolniak, Casey E. George, Glen R. Nelson , August 2019 The findings point to variation in informational quality across dimensions ranging from clarity of language use and terminology, to consistency and coherence of visual displays, which accompany navigational challenges stemming from information fragmentation and discontinuity across pages. Juan E. Saavedra, Emma Näslund-Hadley, Mariana Alfonso , August 12, 2019 Researchers present results from the first randomized experiment of a remedial inquiry-based science education program for low-performing elementary students in a developing country. F. Chris Curran, James Kitchin , July 2019 Researchers found suggestive evidence in some models (student fixed effects and regression with observable controls) that time on science instruction is related to science achievement but little evidence that the number of science topics/skills covered are related to greater science achievement. Kathleen Lynch, Heather C. Hill, Kathryn E. Gonzalez, Cynthia Pollard , June 2019 Programs saw stronger outcomes when they helped teachers learn to use curriculum materials; focused on improving teachers’ content knowledge, pedagogical content knowledge, and/or understanding of how students learn; incorporated summer workshops; and included teacher meetings to troubleshoot and discuss classroom implementation. We discuss implications for policy and practice. Elizabeth Stearns, Martha Cecilia Bottia, Jason Giersch, Roslyn Arlin Mickelson, Stephanie Moller, Nandan Jha, Melissa Dancy , June 2019  Researchers found that relative advantages in college academic performance in STEM versus non-STEM subjects do not contribute to the gender gap in STEM major declaration. Nicole Shechtman, Jeremy Roschelle, Mingyu Feng, Corinne Singleton , May 2019 As educational leaders throughout the United States adopt digital mathematics curricula and adaptive, blended approaches, the findings provide a relevant caution. Colleen M. Ganley, Robert C. Schoen, Mark LaVenia, Amanda M. Tazaz , March 2019 Factor analyses support a distinction between components of general math anxiety and anxiety about teaching math. Felicia Moore Mensah , February 2019  The implications for practice in both teacher education and science education show that educational and emotional support for teachers of color throughout their educational and professional journey is imperative to increasing and sustaining Black teachers. Herbert W. Marsh, Brooke Van Zanden, Philip D. Parker, Jiesi Guo, James Conigrave, Marjorie Seaton , February 2019  Researchers evaluated STEM coursework selection by women and men in senior high school and university, controlling achievement and expectancy-value variables. Yasemin Copur-Gencturk, Debra Plowman, Haiyan Bai , January 2019  The results showed that a focus on curricular content knowledge and examining students’ work were significantly related to teachers’ learning. Rebecca Colina Neri, Maritza Lozano, Louis M. Gomez , 2019 Researchers found that teacher resistance to CRE as a multilevel learning problem stems from (a) limited understanding and belief in the efficacy of CRE and (b) a lack of know-how needed to execute it. Russell T. Warne, Gerhard Sonnert, and Philip M. Sadler , 2019 Researchers  investigated the relationship between participation in AP mathematics courses (AP Calculus and AP Statistics) and student career interest in STEM. Catherine Riegle-Crumb, Barbara King, and Yasmiyn Irizarry , 2019  Results reveal evidence of persistent racial/ethnic inequality in STEM degree attainment not found in other fields. Eben B. Witherspoon, Paulette Vincent-Ruz, and Christian D. Schunn , 2019  Researchers found that high-performing women often graduate with lower paying, lower status degrees. Bruce Fuller, Yoonjeon Kim, Claudia Galindo, Shruti Bathia, Margaret Bridges, Greg J. Duncan, and Isabel García Valdivia , 2019 This article details the growing share of Latino children from low-income families populating schools, 1998 to 2010. Rebekka Darner , 2019 Drawing from motivated reasoning and self-determination theories, this essay builds a theoretical model of how negative emotions, thwarting of basic psychological needs, and the backfire effect interact to undermine critical evaluation of evidence, leading to science denial. Okhee Lee , 2019 As the fast-growing population of English learners (ELs) is expected to meet college- and career-ready content standards, the purpose of this article is to highlight key issues in aligning ELP standards with content standards. Mark C. Long, Dylan Conger, and Raymond McGhee, Jr. , 2019 The authors offer the first model of the components inherent in a well-implemented AP science course and the first evaluation of AP implementation with a focus on public schools newly offering the inquiry-based version of AP Biology and Chemistry courses. Yasemin Copur-Gencturk, Joseph R. Cimpian, Sarah Theule Lubienski, and Ian Thacker , 2019 Results indicate that teachers are not free of bias, and that teachers from marginalized groups may be susceptible to bias that favors stereotype-advantaged groups. Geoffrey B. Saxe and Joshua Sussman , 2019  Multilevel analysis of longitudinal data on a specialized integers and fractions assessment, as well as a California state mathematics assessment, revealed that the ELs in LMR classrooms showed greater gains than comparison ELs and gained at similar rates to their EP peers in LMR classrooms. Jordan Rickles, Jessica B. Heppen, Elaine Allensworth, Nicholas Sorensen, and Kirk Walters , 2019  The authors discuss whether it would have been appropriate to test for nominally equivalent outcomes, given that the study was initially conceived and designed to test for significant differences, and that the conclusion of no difference was not solely based on a null hypothesis test. Soobin Kim, Gregory Wallsworth, Ran Xu, Barbara Schneider, Kenneth Frank, Brian Jacob, Susan Dynarski , 2019 Using detailed Michigan high school transcript data, this article examines the effect of the MMC on various students’ course-taking and achievement outcomes. Dario Sansone , December 2018 Researchers found that students were less likely to believe that men were better than women in math or science when assigned to female teachers or to teachers who valued and listened to ideas from their students. Ebony McGee , December 2018 The authors argues that both racial groups endure emotional distress because each group responds to its marginalization with an unrelenting motivation to succeed that imposes significant costs. Barbara Means, Haiwen Wang, Xin Wei, Emi Iwatani, Vanessa Peters , November 2018 Students overall and from under-represented groups who had attended inclusive STEM high schools were significantly more likely to be in a STEM bachelor’s degree program two years after high school graduation. Paulo Tan, Kathleen King Thorius , November 2018  Results indicate identity and power tensions that worked against equitable practices. Caesar R. Jackson , November 2018 This study investigated the validity and reliability of the Motivated Strategies for Learning Questionnaire (MSLQ) for minority students enrolled in STEM courses at a historically black college/university (HBCU). Tuan D. Nguyen, Christopher Redding , September 2018 The results highlight the importance of recruiting qualified STEM teachers to work in high-poverty schools and providing supports to help them thrive and remain in the classroom. Joseph A. Taylor, Susan M. Kowalski, Joshua R. Polanin, Karen Askinas, Molly A. M. Stuhlsatz, Christopher D. Wilson, Elizabeth Tipton, Sandra Jo Wilson , August 2018 The meta-analysis examines the relationship between science education intervention effect sizes and a host of study characteristics, allowing primary researchers to access better estimates of effect sizes for a priori power analyses. The results of this meta-analysis also support programmatic decisions by setting realistic expectations about the typical magnitude of impacts for science education interventions. Brian A. Burt, Krystal L. Williams, Gordon J. M. Palmer , August 2018 Three factors are identified as helping them persist from year to year, and in many cases through completion of the doctorate: the role of family, spirituality and faith-based community, and undergraduate mentors. Anna-Lena Rottweiler, Jamie L. Taxer, Ulrike E. Nett , June 2018 Suppression improved mood in exam-related anxiety, while distraction improved mood only in non-exam-related anxiety. Gabriel Estrella, Jacky Au, Susanne M. Jaeggi, Penelope Collins , April 2018 Although an analysis of 26 articles confirmed that inquiry instruction produced significantly greater impacts on measures of science achievement for ELLs compared to direct instruction, there was still a differential learning effect suggesting greater efficacy for non-ELLs compared to ELLs. Heather C. Hill, Mark Chin , April 2018 In this article, evidence from 284 teachers suggests that accuracy can be adequately measured and relates to instruction and student outcomes. Darrell M. Hull, Krystal M. Hinerman, Sarah L. Ferguson, Qi Chen, Emma I. Näslund-Hadley , April 20, 2018 Both quantitative and qualitative evidence suggest students within this culture respond well to this relatively simple and inexpensive intervention that departs from traditional, expository math instruction in many developing countries. Erika C. Bullock , April 2018 The author reviews CME studies that employ intersectionality as a way of analyzing the complexities of oppression. Angela Calabrese Barton, Edna Tan , March 2018  Building a conceptual argument for an equity-oriented culture of making, the authors discuss the ways in which making with and in community opened opportunities for youth to project their communities’ rich culture knowledge and wisdom onto their making while also troubling and negotiating the historicized injustices they experience. Sabrina M. Solanki, Di Xu , March 2018  Researchers found that having a female instructor narrows the gender gap in terms of engagement and interest; further, both female and male students tend to respond to instructor gender. Susanne M. Jaeggi, Priti Shah , February 2018 These articles provide excellent examples for how neuroscientific approaches can complement behavioral work, and they demonstrate how understanding the neural level can help researchers develop richer models of learning and development. Danyelle T. Ireland, Kimberley Edelin Freeman, Cynthia E. Winston-Proctor, Kendra D. DeLaine, Stacey McDonald Lowe, Kamilah M. Woodson , 2018 Researchers found that (1) identity; (2) STEM interest, confidence, and persistence; (3) achievement, ability perceptions, and attributions; and (4) socializers and support systems are key themes within the experiences of Black women and girls in STEM education. Ann Y. Kim, Gale M. Sinatra, Viviane Seyranian , 2018 Findings indicate that young women experience challenges to their participation and inclusion when they are in STEM settings. Guan Saw, Chi-Ning Chang, and Hsun-Yu Chan , 2018  Results indicated that female, Black, Hispanic, and low SES students were less likely to show, maintain, and develop an interest in STEM careers during high school years. Di Xu, Sabrina Solanki, Peter McPartlan, and Brian Sato , 2018 This paper estimates the causal effects of a first-year STEM learning communities program on both cognitive and noncognitive outcomes at a large public 4-year institution. Christina S. Chhin, Katherine A. Taylor, and Wendy S. Wei , 2018 Data showed that IES has not funded any direct replications that duplicate all aspects of the original study, but almost half of the funded grant applications can be considered conceptual replications that vary one or more dimensions of a prior study. Okhee Lee , 2018 As federal legislation requires that English language proficiency (ELP) standards are aligned with content standards, this article addresses issues and concerns in aligning ELP standards with content standards in English language arts, mathematics, and science. Jordan Rickles, Jessica B. Heppen, Elaine Allensworth, Nicholas Sorensen, and Kirk Walters , 2018 Researchers found no statistically significant differences in longer term outcomes between students in the online and face-to-face courses. Implications of these null findings are discussed. Colleen M. Ganley, Casey E. George, Joseph R. Cimpian, Martha B. Makowski , December 2017  Researchers found that perceived gender bias against women emerges as the dominant predictor of the gender balance in college majors. James P. Spillane, Megan Hopkins, Tracy M. Sweet , December 2017 This article examines the relationship between teachers’ instructional ties and their beliefs about mathematics instruction in one school district working to transform its approach to elementary mathematics education.  Susan A. Yoon, Sao-Ee Goh, Miyoung Park , December 6, 2017 Results revealed needs in five areas of research: a need to diversify the knowledge domains within which research is conducted, more research on learning about system states, agreement on the essential features of complex systems content, greater focus on contextual factors that support learning including teacher learning, and a need for more comparative research. Candace Walkington, Virginia Clinton, Pooja Shivraj , November 2017  Textual features that make problems more difficult to process appear to differentially negatively impact struggling students, while features that make language easier to process appear to differentially positively impact struggling students. Rebecca L. Matz, Benjamin P. Koester, Stefano Fiorini, Galina Grom, Linda Shepard, Charles G. Stangor, Brad Weiner, Timothy A. McKay , November 2017 Biology, chemistry, physics, accounting, and economics lecture courses regularly exhibit gendered performance differences that are statistically and materially significant, whereas lab courses in the same subjects do not. Adam V. Maltese, Christina S. Cooper , August 2017 The results reveal that although there is no singular pathway into STEM fields, self-driven interest is a large factor in persistence, especially for males, and females rely more heavily on support from others. Brian R. Belland, Andrew E. Walker, Nam Ju Kim , August 2017 Scaffolding has a consistently strong effect across student populations, STEM disciplines, and assessment levels, and a strong effect when used with most problem-centered instructional and educational levels. Di Xu, Shanna Smith Jaggars , July 2017 The findings indicate a robust negative impact of online course taking for both subjects. Maisie L. Gholson, Charles E. Wilkes , June 2017 This chapter reviews two strands of identity-based research in mathematics education related to Black children, exemplified by Martin (2000) and Nasir (2002). Sarah Theule Lubienski, Emily K. Miller, and Evthokia Stephanie Saclarides , November 2017  Using data from a survey of doctoral students at one large institution, this study finds that men submitted and published more scholarly works than women across many fields, with differences largest in natural/biological sciences and engineering.  David Blazar, Cynthia Pollard , October 2017 Drawing on classroom observations and teacher surveys, researchers find that test preparation activities predict lower quality and less ambitious mathematics instruction in upper-elementary classrooms. Nicole M. Joseph, Meseret Hailu, Denise Boston , June 2017 This integrative review used critical race theory (CRT) and Black feminism as interpretive frames to explore factors that contribute to Black women’s and girls’ persistence in the mathematics pipeline and the role these factors play in shaping their academic outcomes. Benjamin L. Wiggins, Sarah L. Eddy, Daniel Z. Grunspan, Alison J. Crowe , May 2017 Researchers describe the results of a quasi-experimental study to test the apex of the ICAP framework (interactive, constructive, active, and passive) in this ecological classroom environment. Sean Gehrke, Adrianna Kezar , May 2017  This study examines how involvement in four cross-institutional STEM faculty communities of practice is associated with local departmental and institutional change for faculty members belonging to these communities. Lawrence Ingvarson, Glenn Rowley , May 2017 This study investigated the relationship between policies related to the recruitment, selection, preparation, and certification of new teachers and (a) the quality of future teachers as measured by their mathematics content and pedagogy content knowledge and (b) student achievement in mathematics at the national level.  Will Tyson, Josipa Roksa , April 2017 This study examines how course grades and course rigor are associated with math attainment among students with similar eighth-grade standardized math test scores.  Anne K. Morris, James Hiebert , March 2017 Researchers investigated whether the content pre-service teachers studied in elementary teacher preparation mathematics courses was related to their performance on a mathematics lesson planning task 2 and 3 years after graduation.  Laura M. Desimone, Kirsten Lee Hill , March 2017 Researchers use data from a randomized controlled trial of a middle school science intervention to explore the causal mechanisms by which the intervention produced previously documented gains in student achievement. Okhee Lee , March 2017 This article focuses on how the Common Core State Standards (CCSS) and the Next Generation Science Standards (NGSS) treat “argument,” especially in Grades K–5, and the extent to which each set of standards is grounded in research literature, as claimed. Cory Koedel, Diyi Li, Morgan S. Polikoff, Tenice Hardaway, Stephani L. Wrabel , February 2017 Researchers estimate relative achievement effects of the four most commonly adopted elementary mathematics textbooks in the fall of 2008 and fall of 2009 in California. Mary Kay Stein, Richard Correnti, Debra Moore, Jennifer Lin Russell, Katelynn Kelly , January 2017 Researchers argue that large-scale, standards-based improvements in the teaching and learning of mathematics necessitate advances in theories regarding how teaching affects student learning and progress in how to measure instruction. Alan H. Schoenfeld , December 2016 The author begins by tracing the growth and change in research in mathematics education and its interdependence with research in education in general over much of the 20th century, with an emphasis on changes in research perspectives and methods and the philosophical/empirical/disciplinary approaches that underpin them.  Marcia C. Linn, Libby Gerard, Camillia Matuk, Kevin W. McElhaney , December 2016 This chapter focuses on how investigators from varied fields of inquiry who initially worked separately began to interact, eventually formed partnerships, and recently integrated their perspectives to strengthen science education. : Are Teachers’ Implicit Cognitions Another Piece of the Puzzle? Almut E. Thomas , December 2016 Drawing on expectancy-value theory, this study investigated whether teachers’ implicit science-is-male stereotypes predict between-teacher variation in males’ and females’ motivational beliefs regarding physical science.  : A By-Product of STEM College Culture? Ebony O. McGee , December 2016  The researcher found that the 38 high-achieving Black and Latino/a STEM study participants, who attended institutions with racially hostile academic spaces, deployed an arsenal of strategies (e.g., stereotype management) to deflect stereotyping and other racial assaults (e.g., racial microaggressions), which are particularly prevalent in STEM fields.  James Cowan, Dan Goldhaber, Kyle Hayes, Roddy Theobald , November 2016 Researchers discuss public policies that contribute to teacher shortages in specific subjects (e.g., STEM and special education) and specific types of schools (e.g., disadvantaged) as well as potential solutions. : A Sociological Analysis of Multimethod Data From Young Women Aged 10–16 to Explore Gendered Patterns of Post-16 Participation Louise Archer, Julie Moote, Becky Francis, Jennifer DeWitt, Lucy Yeomans , November 2016 Researchers draw on survey data from more than 13,000 year 11 (age 15/16) students and interviews with 70 students (who had been tracked from age 10 to 16), focusing in particular on seven girls who aspired to continue with physics post-16, discussing how the cultural arbitrary of physics requires these girls to be highly “exceptional,” undertaking considerable identity work and deployment of capital in order to “possibilize” a physics identity—an endeavor in which some girls are better positioned to be successful than others. Jeremy Roschelle, Mingyu Feng, Robert F. Murphy, Craig A. Mason , October 2016 In a randomized field trial with 2,850 seventh-grade mathematics students, researchers evaluated whether an educational technology intervention increased mathematics learning. : Making Research Participation Instructionally Effective Sherry A. Southerland, Ellen M. Granger, Roxanne Hughes, Patrick Enderle, Fengfeng Ke, Katrina Roseler, Yavuz Saka, Miray Tekkumru-Kisa , October 2016 As current reform efforts in science place a premium on student sense making and participation in the practices of science, researchers use a close examination of 106 science teachers participating in Research Experiences for Teachers (RET) to identify, through structural equation modeling, the essential features in supporting teacher learning from these experiences. Brian R. Belland, Andrew E. Walker, Nam Ju Kim, Mason Lefler , October 2016 This review addresses the need for a comprehensive meta-analysis of research on scaffolding in STEM education by synthesizing the results of 144 experimental studies (333 outcomes) on the effects of computer-based scaffolding designed to assist the full range of STEM learners (primary through adult education) as they navigated ill-structured, problem-centered curricula. Vaughan Prain, Brian Hand , October 2016 Researchers claim that there are strong evidence-based reasons for viewing writing as a central but not sole resource for learning, drawing on both past and current research on writing as an epistemological tool and on their professional background in science education research, acknowledging its distinctive take on the use of writing for learning.  June Ahn, Austin Beck, John Rice, Michelle Foster , September 2016 Researchers present analyses from a researcher-practitioner partnership in the District of Columbia Public Schools, where the researchers are exploring the impact of educational software on students’ academic achievement. Barbara King , September 2016 This study uses nationally representative data from a recent cohort of college students to investigate thoroughly gender differences in STEM persistence.  Ryan C. Svoboda, Christopher S. Rozek, Janet S. Hyde, Judith M. Harackiewicz, Mesmin Destin , August 2016 This longitudinal study draws on identity-based and expectancy-value theories of motivation to explain the socioeconomic status (SES) and mathematics and science course-taking relationship.  Mathematics Course Placements in California Middle Schools, 2003–2013 Thurston Domina, Paul Hanselman, NaYoung Hwang, Andrew McEachin , July 2016  Researchers consider the organizational processes that accompanied the curricular intensification of the proportion of California eighth graders enrolled in algebra or a more advanced course nearly doubling to 65% between 2003 and 2013. Lina Shanley , July 2016 Using a nationally representative longitudinal data set, this study compared various models of mathematics achievement growth on the basis of both practical utility and optimal statistical fit and explored relationships within and between early and later mathematics growth parameters.  Mimi Engel, Amy Claessens, Tyler Watts, George Farkas , June 2016 Analyzing data from two nationally representative kindergarten cohorts, researchers examine the mathematics content teachers cover in kindergarten. F. Chris Curran, Ann T. Kellogg , June 2016 Researchers present findings from the recently released Early Childhood Longitudinal Study, Kindergarten Class of 2010–2011 that demonstrate significant gaps in science achievement in kindergarten and first grade by race/ethnicity. Rachel Garrett, Guanglei Hong , June 2016 Analyzing the Early Childhood Longitudinal Study–Kindergarten cohort data, researchers find that heterogeneous grouping or a combination of heterogeneous and homogeneous grouping under relatively adequate time allocation is optimal for enhancing teacher ratings of language minority kindergartners’ math performance, while using homogeneous grouping only is detrimental.  Jennifer Gnagey, Stéphane Lavertu , May 2016 This study is one of the first to estimate the impact of “inclusive” science, technology, engineering, and mathematics (STEM) high schools using student-level data.  Hanna Gaspard, Anna-Lena Dicke, Barbara Flunger, Isabelle Häfner, Brigitte M. Brisson, Ulrich Trautwein, Benjamin Nagengast , May 2016  Through data from a cluster-randomized study in which a value intervention was successfully implemented in 82 ninth-grade math classrooms, researchers address how interventions on students’ STEM motivation in school affect motivation in subjects not targeted by the intervention. Rebecca M. Callahan, Melissa H. Humphries , April 2016  Researchers employ multivariate methods to investigate immigrant college going by linguistic status using the Educational Longitudinal Study of 2002. Federick Ngo, Tatiana Melguizo , March 2016 Researchers take advantage of heterogeneous placement policy in a large urban community college district in California to compare the effects of math remediation under different policy contexts. : An Analysis of German Fourth- and Sixth-Grade Classrooms Steffen Tröbst, Thilo Kleickmann, Kim Lange-Schubert, Anne Rothkopf, Kornelia Möller , February 2016  Researchers examined if changes in instructional practices accounted for differences in situational interest in science instruction and enduring individual interest in science between elementary and secondary school classrooms. : A Mixed-Methods Study David F. Feldon, Michelle A. Maher, Josipa Roksa, James Peugh , February 2016  Researchers offer evidence of a similar phenomenon to cumulative advantage, accounting for differential patterns of research skill development in graduate students over an academic year and explore differences in socialization that accompany diverging developmental trajectories.   : The Influence of Time, Peers, and Place Luke Dauter, Bruce Fuller , February 2016  Researchers hypothesize that pupil mobility stems from the (a) student’s time in school and grade; (b) student’s race, class, and achievement relative to peers; (c) quality of schooling relative to nearby alternatives; and (4) proximity, abundance, and diversity of local school options.  : How Workload and Curricular Affordances Shape STEM Faculty Decisions About Teaching and Learning Matthew T. Hora , January 2016 In this study the idea of the “problem space” from cognitive science is used to examine how faculty construct mental representations for the task of planning undergraduate courses.  Jessaca Spybrook, Carl D. Westine, Joseph A. Taylor , January 2016 This article provides empirical estimates of design parameters necessary for planning adequately powered cluster randomized trials (CRTs) focused on science achievement.  Paul L. Morgan, George Farkas, Marianne M. Hillemeier, Steve Maczuga , January 2016 Researchers examined the age of onset, over-time dynamics, and mechanisms underlying science achievement gaps in U.S. elementary and middle schools.  : Opportunity Structures and Outcomes in Inclusive STEM-Focused High Schools Lois Weis, Margaret Eisenhart, Kristin Cipollone, Amy E. Stich, Andrea B. Nikischer, Jarrod Hanson, Sarah Ohle Leibrandt, Carrie D. Allen, Rachel Dominguez , December 2015  Researchers present findings from a three-year comparative longitudinal and ethnographic study of how schools in two cities, Buffalo and Denver, have taken up STEM education reform, including the idea of “inclusive STEM-focused schools,” to address weaknesses in urban high schools with majority low-income and minority students.  : How Do They Interact in Promoting Science Understanding? Jasmin Decristan, Eckhard Klieme, Mareike Kunter, Jan Hochweber, Gerhard Büttner, Benjamin Fauth, A. Lena Hondrich, Svenja Rieser, Silke Hertel, Ilonca Hardy , December 2015 Researchers examine the interplay between curriculum-embedded formative assessment—a well-known teaching practice—and general features of classroom process quality (i.e., cognitive activation, supportive climate, classroom management) and their combined effect on elementary school students’ understanding of the scientific concepts of floating and sinking. : An International Perspective William H. Schmidt, Nathan A. Burroughs, Pablo Zoido, Richard T. Houang , October 2015 In this paper, student-level indicators of opportunity to learn (OTL) included in the 2012 Programme for International Student Assessment are used to explore the joint relationship of OTL and socioeconomic status (SES) to student mathematics literacy.  Xueli Wang , September 2015 This study examines the effect of beginning at a community college on baccalaureate success in science, technology, engineering, and mathematics (STEM) fields.  : Trends and Predictors David M. Quinn, North Cooc , August 2015 With research on science achievement disparities by gender and race/ethnicity often neglecting the beginning of the pipeline in the early grades, researchers address this limitation using nationally representative data following students from Grades 3 to 8.  Shaun M. Dougherty, Joshua S. Goodman, Darryl V. Hill, Erica G. Litke, Lindsay C. Page , May 2015 Researchers highlight a collaboration to investigate one district’s effort to increase middle school algebra course-taking. David F. Feldon, Michelle A. Maher, Melissa Hurst, Briana Timmerman , April 2015 This mixed-method study investigates agreement between student mentees’ and their faculty mentors’ perceptions of the students’ developing research knowledge and skills in STEM.  : Reviving Science Education for Civic Ends John L. Rudolph , December 2014  This article revisits John Dewey’s now-well-known address “Science as Subject-Matter and as Method” and examines the development of science education in the United States in the years since that address. Dermot F. Donnelly, Marcia C. Linn Sten Ludvigsen , December 2014 The National Science Foundation–sponsored report Fostering Learning in the Networked World called for “a common, open platform to support communities of developers and learners in ways that enable both to take advantage of advances in the learning sciences”; we review research on science inquiry learning environments (ILEs) to characterize current platforms.  : A Longitudinal Case Study of America’s Chemistry Teachers Gregory T. Rushton, Herman E. Ray, Brett A. Criswell, Samuel J. Polizzi, Clyde J. Bearss, Nicholas Levelsmier, Himanshu Chhita, Mary Kirchhoff , November 2014  Researchers perform a longitudinal case study of U.S. public school chemistry teachers to illustrate a diffusion of responsibility within the STEM community regarding who is responsible for the teacher workforce.  : Relations Between Early Mathematics Knowledge and High School Achievement Tyler W. Watts, Greg J. Duncan, Robert S. Siegler, Pamela E. Davis-Kean , October 2014 Researchers find that preschool mathematics ability predicts mathematics achievement through age 15, even after accounting for early reading, cognitive skills, and family and child characteristics. T. Jared Robinson, Lane Fischer, David Wiley, John Hilton, III , October 2014 The purpose of this quantitative study is to analyze whether the adoption of open science textbooks significantly affects science learning outcomes for secondary students in earth systems, chemistry, and physics. : 1968–2009 Robert N. Ronau, Christopher R. Rakes, Sarah B. Bush, Shannon O. Driskell, Margaret L. Niess, David K. Pugalee , October 2014  We examined 480 dissertations on the use of technology in mathematics education and developed a Quality Framework (QF) that provided structure to consistently define and measure quality. Andrew D. Plunk, William F. Tate, Laura J. Bierut, Richard A. Grucza , June 2014 Using logistic regression with Census and American Community Survey (ACS) data (  = 2,892,444), researchers modeled mathematics and science course graduation requirement (CGR) exposure on (a) high school dropout, (b) beginning college, and (c) obtaining any college degree.  Corey Drake, Tonia J. Land, Andrew M. Tyminski , April 2014 Building on the work of Ball and Cohen and that of Davis and Krajcik, as well as more recent research related to teacher learning from and about curriculum materials, researchers seek to answer the question, How can prospective teachers (PTs) learn to read and use educative curriculum materials in ways that support them in acquiring the knowledge needed for teaching? Lorraine M. McDonnell, M. Stephen Weatherford , December 2013 This article draws on theories of political and policy learning and interviews with major participants to examine the role that the Common Core State Standards (CCSS) supporters have played in developing and implementing the standards, supporters’ reasons for mobilizing, and the counterarguments and strategies of recently emerging opposition groups. : Motivation, High School Learning, and Postsecondary Context of Support Xueli Wang , October 2013  This study draws upon social cognitive career theory and higher education literature to test a conceptual framework for understanding the entrance into science, technology, engineering, and mathematics (STEM) majors by recent high school graduates attending 4-year institutions.  Philip M. Sadler, Gerhard Sonnert, Harold P. Coyle, Nancy Cook-Smith, Jaimie L. Miller , October 2013 This study examines the relationship between teacher knowledge and student learning for 9,556 students of 181 middle school physical science teachers. : Teaching Critical Mathematics in a Remedial Secondary Classroom Andrew Brantlinger , October 2013  The researcher presents results from a practitioner research study of his own teaching of critical mathematics (CM) to low-income students of color in a U.S. context.  Jason G. Hill, Ben Dalton , October 2013 This study investigates the distribution of math teachers with a major or certification in math using data from the National Center for Education Statistics’ High School Longitudinal Study of 2009 (HSLS:09). Kristin F. Butcher, Mary G. Visher , September 2013 This study uses random assignment to investigate the impact of a “light-touch” intervention, where an individual visited math classes a few times during the semester, for a few minutes each time, to inform students about available services. Janet M. Dubinsky, Gillian Roehrig, Sashank Varma , August 2013  Researchers argue that the neurobiology of learning, and in particular the core concept of  , have the potential to directly transform teacher preparation and professional development, and ultimately to affect how students think about their own learning.  : The Impact of Undergraduate Research Programs M. Kevin Eagan, Jr., Sylvia Hurtado, Mitchell J. Chang, Gina A. Garcia, Felisha A. Herrera, Juan C. Garibay , August 2013  Researchers’ findings indicate that participation in an undergraduate research program significantly improved students’ probability of indicating plans to enroll in a STEM graduate program. Okhee Lee, Helen Quinn, Guadalupe Valdés , May 2013 This article addresses language demands and opportunities that are embedded in the science and engineering practices delineated in “A Framework for K–12 Science Education,” released by the National Research Council (2011). Liliana M. Garces , April 2013  This study examines the effects of affirmative action bans in four states (California, Florida, Texas, and Washington) on the enrollment of underrepresented students of color within six different graduate fields of study: the natural sciences, engineering, social sciences, business, education, and humanities. : Learning Lessons From Research on Diversity in STEM Fields Shirley M. Malcom, Lindsey E. Malcom-Piqueux , April 2013 Researchers argue that social scientists ought to look to the vast STEM education research literature to begin the task of empirically investigating the questions raised in the   case.  Roslyn Arlin Mickelson, Martha Cecilia Bottia, Richard Lambert , March 2013 This metaregression analysis reviewed the social science literature published in the past 20 years on the relationship between mathematics outcomes and the racial composition of the K–12 schools students attend.  Jeffrey Grigg, Kimberle A. Kelly, Adam Gamoran, Geoffrey D. Borman , March 2013 Researchers examine classroom observations from a 3-year large-scale randomized trial in the Los Angeles Unified School District (LAUSD) to investigate the extent to which a professional development initiative in inquiry science influenced teaching practices in in 4th and 5th grade classrooms in 73 schools. :  Angela Calabrese Barton, Hosun Kang, Edna Tan, Tara B. O’Neill, Juanita Bautista-Guerra, Caitlin Brecklin , February 2013  This longitudinal ethnographic study traces the identity work that girls from nondominant backgrounds do as they engage in science-related activities across school, club, and home during the middle school years.  : A Review of the State of the Field Shuchi Grover, Roy Pea , January 2013  This article frames the current state of discourse on computational thinking in K–12 education by examining mostly recently published academic literature that uses Jeannette Wing’s article as a springboard, identifies gaps in research, and articulates priorities for future inquiries. Catherine Riegle-Crumb, Barbara King, Eric Grodsky, Chandra Muller , December 2012  This article investigates the empirical basis for often-repeated arguments that gender differences in entrance into science, technology, engineering, and mathematics (STEM) majors are largely explained by disparities in prior achievement.  Richard M. Ingersoll, Henry May , December 2012 This study examines the magnitude, destinations, and determinants of mathematics and science teacher turnover.  : How Families Shape Children’s Engagement and Identification With Science Louise Archer, Jennifer DeWitt, Jonathan Osborne, Justin Dillon, Beatrice Willis, Billy Wong , October 2012  Drawing on the conceptual framework of Bourdieu, this article explores how the interplay of family habitus and capital can make science aspirations more “thinkable” for some (notably middle-class) children than others. Erin Marie Furtak, Tina Seidel, Heidi Iverson, Derek C. Briggs , September 2012 This meta-analysis introduces a framework for inquiry-based teaching that distinguishes between cognitive features of the activity and degree of guidance given to students.  Jaekyung Lee, Todd Reeves , June 2012 This study examines the impact of high-stakes school accountability, capacity, and resources under NCLB on reading and math achievement outcomes through comparative interrupted time-series analyses of 1990–2009 NAEP state assessment data.  : Toward a Theory of Teaching Paola Sztajn, Jere Confrey, P. Holt Wilson, Cynthia Edgington , June 2012 Researchers propose a theoretical connection between research on learning and research on teaching through recent research on students’ learning trajectories (LTs).  : The Perspectives of Exemplary African American Teachers Jianzhong Xu, Linda T. Coats, Mary L. Davidson , February 2012  Researchers argue both the urgency and the promise of establishing a constructive conversation among different bodies of research, including science interest, sociocultural studies in science education, and culturally relevant teaching.  Rebecca M. Schneider, Kellie Plasman , December 2011 This review examines the research on science teachers’ pedagogical content knowledge (PCK) in order to refine ideas about science teacher learning progressions and how to support them.  Brian A. Nosek, Frederick L. Smyth , October 2011  Researchers examined implicit math attitudes and stereotypes among a heterogeneous sample of 5,139 participants.  Libby F. Gerard, Keisha Varma, Stephanie B. Corliss, Marcia C. Linn , September 2011 Researchers’ findings suggest that professional development programs that engaged teachers in a comprehensive, constructivist-oriented learning process and were sustained beyond 1 year significantly improved students’ inquiry learning experiences in K–12 science classrooms.  : Teaching and Learning Impacts of Reading Apprenticeship Professional Development Cynthia L. Greenleaf, Cindy Litman, Thomas L. Hanson, Rachel Rosen, Christy K. Boscardin, Joan Herman, Steven A. Schneider, Sarah Madden, Barbara Jones , June 2011  This study examined the effects of professional development integrating academic literacy and biology instruction on science teachers’ instructional practices and students’ achievement in science and literacy.  Paul Cobb, Kara Jackson , May 2011 The authors comment on Porter, McMaken, Hwang, and Yang’s recent analysis of the Common Core State Standards for Mathematics by critiquing their measures of the focus of the standards and the absence of an assessment of coherence.  P. Wesley Schultz, Paul R. Hernandez, Anna Woodcock, Mica Estrada, Randie C. Chance, Maria Aguilar, Richard T. Serpe , March 2011 This study reports results from a longitudinal study of students supported by a national National Institutes of Health–funded minority training program, and a propensity score matched control.  : Three Large-Scale Studies Jeremy Roschelle, Nicole Shechtman, Deborah Tatar, Stephen Hegedus, Bill Hopkins, Susan Empson, Jennifer Knudsen, Lawrence P. Gallagher , December 2010  The authors present three studies (two randomized controlled experiments and one embedded quasi-experiment) designed to evaluate the impact of replacement units targeting student learning of advanced middle school mathematics.  : Examining Disparities in College Major by Gender and Race/Ethnicity Catherine Riegle-Crumb, Barbara King , December 2010  The authors analyze national data on recent college matriculants to investigate gender and racial/ethnic disparities in STEM fields, with an eye toward the role of academic preparation and attitudes in shaping such disparities.  Mary Kay Stein, Julia H. Kaufman , September 2010  This article begins to unravel the question, “What curricular materials work best under what kinds of conditions?” The authors address this question from the point of view of teachers and their ability to implement mathematics curricula that place varying demands and provide varying levels of support for their learning.  Andy R. Cavagnetto , September 2010 This study of 54 articles from the research literature examines how argument interventions promote scientific literacy.  Victoria M. Hand , March 2010 The researcher examined how the teacher and students in a low-track mathematics classroom jointly constructed opposition through their classroom interactions. Terrence E. Murphy, Monica Gaughan, Robert Hume, S. Gordon Moore, Jr. , March 2010 Researchers evaluate the association of a summer bridge program with the graduation rate of underrepresented minority (URM) students at a selective technical university.  Privacy Policy Home » 500+ Quantitative Research Titles and Topics 500+ Quantitative Research Titles and Topics Table of Contents Quantitative research involves collecting and analyzing numerical data to identify patterns, trends, and relationships among variables. This method is widely used in social sciences, psychology , economics , and other fields where researchers aim to understand human behavior and phenomena through statistical analysis. If you are looking for a quantitative research topic, there are numerous areas to explore, from analyzing data on a specific population to studying the effects of a particular intervention or treatment. In this post, we will provide some ideas for quantitative research topics that may inspire you and help you narrow down your interests. Quantitative Research Titles Quantitative Research Titles are as follows: Business and Economics “Statistical Analysis of Supply Chain Disruptions on Retail Sales” “Quantitative Examination of Consumer Loyalty Programs in the Fast Food Industry” “Predicting Stock Market Trends Using Machine Learning Algorithms” “Influence of Workplace Environment on Employee Productivity: A Quantitative Study” “Impact of Economic Policies on Small Businesses: A Regression Analysis” “Customer Satisfaction and Profit Margins: A Quantitative Correlation Study” “Analyzing the Role of Marketing in Brand Recognition: A Statistical Overview” “Quantitative Effects of Corporate Social Responsibility on Consumer Trust” “Price Elasticity of Demand for Luxury Goods: A Case Study” “The Relationship Between Fiscal Policy and Inflation Rates: A Time-Series Analysis” “Factors Influencing E-commerce Conversion Rates: A Quantitative Exploration” “Examining the Correlation Between Interest Rates and Consumer Spending” “Standardized Testing and Academic Performance: A Quantitative Evaluation” “Teaching Strategies and Student Learning Outcomes in Secondary Schools: A Quantitative Study” “The Relationship Between Extracurricular Activities and Academic Success” “Influence of Parental Involvement on Children’s Educational Achievements” “Digital Literacy in Primary Schools: A Quantitative Assessment” “Learning Outcomes in Blended vs. Traditional Classrooms: A Comparative Analysis” “Correlation Between Teacher Experience and Student Success Rates” “Analyzing the Impact of Classroom Technology on Reading Comprehension” “Gender Differences in STEM Fields: A Quantitative Analysis of Enrollment Data” “The Relationship Between Homework Load and Academic Burnout” “Assessment of Special Education Programs in Public Schools” “Role of Peer Tutoring in Improving Academic Performance: A Quantitative Study” Medicine and Health Sciences “The Impact of Sleep Duration on Cardiovascular Health: A Cross-sectional Study” “Analyzing the Efficacy of Various Antidepressants: A Meta-Analysis” “Patient Satisfaction in Telehealth Services: A Quantitative Assessment” “Dietary Habits and Incidence of Heart Disease: A Quantitative Review” “Correlations Between Stress Levels and Immune System Functioning” “Smoking and Lung Function: A Quantitative Analysis” “Influence of Physical Activity on Mental Health in Older Adults” “Antibiotic Resistance Patterns in Community Hospitals: A Quantitative Study” “The Efficacy of Vaccination Programs in Controlling Disease Spread: A Time-Series Analysis” “Role of Social Determinants in Health Outcomes: A Quantitative Exploration” “Impact of Hospital Design on Patient Recovery Rates” “Quantitative Analysis of Dietary Choices and Obesity Rates in Children” Social Sciences “Examining Social Inequality through Wage Distribution: A Quantitative Study” “Impact of Parental Divorce on Child Development: A Longitudinal Study” “Social Media and its Effect on Political Polarization: A Quantitative Analysis” “The Relationship Between Religion and Social Attitudes: A Statistical Overview” “Influence of Socioeconomic Status on Educational Achievement” “Quantifying the Effects of Community Programs on Crime Reduction” “Public Opinion and Immigration Policies: A Quantitative Exploration” “Analyzing the Gender Representation in Political Offices: A Quantitative Study” “Impact of Mass Media on Public Opinion: A Regression Analysis” “Influence of Urban Design on Social Interactions in Communities” “The Role of Social Support in Mental Health Outcomes: A Quantitative Analysis” “Examining the Relationship Between Substance Abuse and Employment Status” Engineering and Technology “Performance Evaluation of Different Machine Learning Algorithms in Autonomous Vehicles” “Material Science: A Quantitative Analysis of Stress-Strain Properties in Various Alloys” “Impacts of Data Center Cooling Solutions on Energy Consumption” “Analyzing the Reliability of Renewable Energy Sources in Grid Management” “Optimization of 5G Network Performance: A Quantitative Assessment” “Quantifying the Effects of Aerodynamics on Fuel Efficiency in Commercial Airplanes” “The Relationship Between Software Complexity and Bug Frequency” “Machine Learning in Predictive Maintenance: A Quantitative Analysis” “Wearable Technologies and their Impact on Healthcare Monitoring” “Quantitative Assessment of Cybersecurity Measures in Financial Institutions” “Analysis of Noise Pollution from Urban Transportation Systems” “The Influence of Architectural Design on Energy Efficiency in Buildings” Quantitative Research Topics Quantitative Research Topics are as follows: The effects of social media on self-esteem among teenagers. A comparative study of academic achievement among students of single-sex and co-educational schools. The impact of gender on leadership styles in the workplace. The correlation between parental involvement and academic performance of students. The effect of mindfulness meditation on stress levels in college students. The relationship between employee motivation and job satisfaction. The effectiveness of online learning compared to traditional classroom learning. The correlation between sleep duration and academic performance among college students. The impact of exercise on mental health among adults. The relationship between social support and psychological well-being among cancer patients. The effect of caffeine consumption on sleep quality. A comparative study of the effectiveness of cognitive-behavioral therapy and pharmacotherapy in treating depression. The relationship between physical attractiveness and job opportunities. The correlation between smartphone addiction and academic performance among high school students. The impact of music on memory recall among adults. The effectiveness of parental control software in limiting children’s online activity. The relationship between social media use and body image dissatisfaction among young adults. The correlation between academic achievement and parental involvement among minority students. The impact of early childhood education on academic performance in later years. The effectiveness of employee training and development programs in improving organizational performance. The relationship between socioeconomic status and access to healthcare services. The correlation between social support and academic achievement among college students. The impact of technology on communication skills among children. The effectiveness of mindfulness-based stress reduction programs in reducing symptoms of anxiety and depression. The relationship between employee turnover and organizational culture. The correlation between job satisfaction and employee engagement. The impact of video game violence on aggressive behavior among children. The effectiveness of nutritional education in promoting healthy eating habits among adolescents. The relationship between bullying and academic performance among middle school students. The correlation between teacher expectations and student achievement. The impact of gender stereotypes on career choices among high school students. The effectiveness of anger management programs in reducing violent behavior. The relationship between social support and recovery from substance abuse. The correlation between parent-child communication and adolescent drug use. The impact of technology on family relationships. The effectiveness of smoking cessation programs in promoting long-term abstinence. The relationship between personality traits and academic achievement. The correlation between stress and job performance among healthcare professionals. The impact of online privacy concerns on social media use. The effectiveness of cognitive-behavioral therapy in treating anxiety disorders. The relationship between teacher feedback and student motivation. The correlation between physical activity and academic performance among elementary school students. The impact of parental divorce on academic achievement among children. The effectiveness of diversity training in improving workplace relationships. The relationship between childhood trauma and adult mental health. The correlation between parental involvement and substance abuse among adolescents. The impact of social media use on romantic relationships among young adults. The effectiveness of assertiveness training in improving communication skills. The relationship between parental expectations and academic achievement among high school students. The correlation between sleep quality and mood among adults. The impact of video game addiction on academic performance among college students. The effectiveness of group therapy in treating eating disorders. The relationship between job stress and job performance among teachers. The correlation between mindfulness and emotional regulation. The impact of social media use on self-esteem among college students. The effectiveness of parent-teacher communication in promoting academic achievement among elementary school students. The impact of renewable energy policies on carbon emissions The relationship between employee motivation and job performance The effectiveness of psychotherapy in treating eating disorders The correlation between physical activity and cognitive function in older adults The effect of childhood poverty on adult health outcomes The impact of urbanization on biodiversity conservation The relationship between work-life balance and employee job satisfaction The effectiveness of eye movement desensitization and reprocessing (EMDR) in treating trauma The correlation between parenting styles and child behavior The effect of social media on political polarization The impact of foreign aid on economic development The relationship between workplace diversity and organizational performance The effectiveness of dialectical behavior therapy in treating borderline personality disorder The correlation between childhood abuse and adult mental health outcomes The effect of sleep deprivation on cognitive function The impact of trade policies on international trade and economic growth The relationship between employee engagement and organizational commitment The effectiveness of cognitive therapy in treating postpartum depression The correlation between family meals and child obesity rates The effect of parental involvement in sports on child athletic performance The impact of social entrepreneurship on sustainable development The relationship between emotional labor and job burnout The effectiveness of art therapy in treating dementia The correlation between social media use and academic procrastination The effect of poverty on childhood educational attainment The impact of urban green spaces on mental health The relationship between job insecurity and employee well-being The effectiveness of virtual reality exposure therapy in treating anxiety disorders The correlation between childhood trauma and substance abuse The effect of screen time on children’s social skills The impact of trade unions on employee job satisfaction The relationship between cultural intelligence and cross-cultural communication The effectiveness of acceptance and commitment therapy in treating chronic pain The correlation between childhood obesity and adult health outcomes The effect of gender diversity on corporate performance The impact of environmental regulations on industry competitiveness. The impact of renewable energy policies on greenhouse gas emissions The relationship between workplace diversity and team performance The effectiveness of group therapy in treating substance abuse The correlation between parental involvement and social skills in early childhood The effect of technology use on sleep patterns The impact of government regulations on small business growth The relationship between job satisfaction and employee turnover The effectiveness of virtual reality therapy in treating anxiety disorders The correlation between parental involvement and academic motivation in adolescents The effect of social media on political engagement The impact of urbanization on mental health The relationship between corporate social responsibility and consumer trust The correlation between early childhood education and social-emotional development The effect of screen time on cognitive development in young children The impact of trade policies on global economic growth The relationship between workplace diversity and innovation The effectiveness of family therapy in treating eating disorders The correlation between parental involvement and college persistence The effect of social media on body image and self-esteem The impact of environmental regulations on business competitiveness The relationship between job autonomy and job satisfaction The effectiveness of virtual reality therapy in treating phobias The correlation between parental involvement and academic achievement in college The effect of social media on sleep quality The impact of immigration policies on social integration The relationship between workplace diversity and employee well-being The effectiveness of psychodynamic therapy in treating personality disorders The correlation between early childhood education and executive function skills The effect of parental involvement on STEM education outcomes The impact of trade policies on domestic employment rates The relationship between job insecurity and mental health The effectiveness of exposure therapy in treating PTSD The correlation between parental involvement and social mobility The effect of social media on intergroup relations The impact of urbanization on air pollution and respiratory health. The relationship between emotional intelligence and leadership effectiveness The effectiveness of cognitive-behavioral therapy in treating depression The correlation between early childhood education and language development The effect of parental involvement on academic achievement in STEM fields The impact of trade policies on income inequality The relationship between workplace diversity and customer satisfaction The effectiveness of mindfulness-based therapy in treating anxiety disorders The correlation between parental involvement and civic engagement in adolescents The effect of social media on mental health among teenagers The impact of public transportation policies on traffic congestion The relationship between job stress and job performance The effectiveness of group therapy in treating depression The correlation between early childhood education and cognitive development The effect of parental involvement on academic motivation in college The impact of environmental regulations on energy consumption The relationship between workplace diversity and employee engagement The effectiveness of art therapy in treating PTSD The correlation between parental involvement and academic success in vocational education The effect of social media on academic achievement in college The impact of tax policies on economic growth The relationship between job flexibility and work-life balance The effectiveness of acceptance and commitment therapy in treating anxiety disorders The correlation between early childhood education and social competence The effect of parental involvement on career readiness in high school The impact of immigration policies on crime rates The relationship between workplace diversity and employee retention The effectiveness of play therapy in treating trauma The correlation between parental involvement and academic success in online learning The effect of social media on body dissatisfaction among women The impact of urbanization on public health infrastructure The relationship between job satisfaction and job performance The effectiveness of eye movement desensitization and reprocessing therapy in treating PTSD The correlation between early childhood education and social skills in adolescence The effect of parental involvement on academic achievement in the arts The impact of trade policies on foreign investment The relationship between workplace diversity and decision-making The effectiveness of exposure and response prevention therapy in treating OCD The correlation between parental involvement and academic success in special education The impact of zoning laws on affordable housing The relationship between job design and employee motivation The effectiveness of cognitive rehabilitation therapy in treating traumatic brain injury The correlation between early childhood education and social-emotional learning The effect of parental involvement on academic achievement in foreign language learning The impact of trade policies on the environment The relationship between workplace diversity and creativity The effectiveness of emotion-focused therapy in treating relationship problems The correlation between parental involvement and academic success in music education The effect of social media on interpersonal communication skills The impact of public health campaigns on health behaviors The relationship between job resources and job stress The effectiveness of equine therapy in treating substance abuse The correlation between early childhood education and self-regulation The effect of parental involvement on academic achievement in physical education The impact of immigration policies on cultural assimilation The relationship between workplace diversity and conflict resolution The effectiveness of schema therapy in treating personality disorders The correlation between parental involvement and academic success in career and technical education The effect of social media on trust in government institutions The impact of urbanization on public transportation systems The relationship between job demands and job stress The correlation between early childhood education and executive functioning The effect of parental involvement on academic achievement in computer science The effectiveness of cognitive processing therapy in treating PTSD The correlation between parental involvement and academic success in homeschooling The effect of social media on cyberbullying behavior The impact of urbanization on air quality The effectiveness of dance therapy in treating anxiety disorders The correlation between early childhood education and math achievement The effect of parental involvement on academic achievement in health education The impact of global warming on agriculture The effectiveness of narrative therapy in treating depression The correlation between parental involvement and academic success in character education The effect of social media on political participation The impact of technology on job displacement The relationship between job resources and job satisfaction The effectiveness of art therapy in treating addiction The correlation between early childhood education and reading comprehension The effect of parental involvement on academic achievement in environmental education The impact of income inequality on social mobility The relationship between workplace diversity and organizational culture The effectiveness of solution-focused brief therapy in treating anxiety disorders The correlation between parental involvement and academic success in physical therapy education The effect of social media on misinformation The impact of green energy policies on economic growth The relationship between job demands and employee well-being The correlation between early childhood education and science achievement The effect of parental involvement on academic achievement in religious education The impact of gender diversity on corporate governance The relationship between workplace diversity and ethical decision-making The correlation between parental involvement and academic success in dental hygiene education The effect of social media on self-esteem among adolescents The impact of renewable energy policies on energy security The effect of parental involvement on academic achievement in social studies The impact of trade policies on job growth The relationship between workplace diversity and leadership styles The correlation between parental involvement and academic success in online vocational training The effect of social media on self-esteem among men The impact of urbanization on air pollution levels The effectiveness of music therapy in treating depression The correlation between early childhood education and math skills The effect of parental involvement on academic achievement in language arts The impact of immigration policies on labor market outcomes The effectiveness of hypnotherapy in treating phobias The effect of social media on political engagement among young adults The impact of urbanization on access to green spaces The relationship between job crafting and job satisfaction The effectiveness of exposure therapy in treating specific phobias The correlation between early childhood education and spatial reasoning The effect of parental involvement on academic achievement in business education The impact of trade policies on economic inequality The effectiveness of narrative therapy in treating PTSD The correlation between parental involvement and academic success in nursing education The effect of social media on sleep quality among adolescents The impact of urbanization on crime rates The relationship between job insecurity and turnover intentions The effectiveness of pet therapy in treating anxiety disorders The correlation between early childhood education and STEM skills The effect of parental involvement on academic achievement in culinary education The impact of immigration policies on housing affordability The relationship between workplace diversity and employee satisfaction The effectiveness of mindfulness-based stress reduction in treating chronic pain The correlation between parental involvement and academic success in art education The effect of social media on academic procrastination among college students The impact of urbanization on public safety services. About the author Muhammad Hassan Researcher, Academic Writer, Web developer You may also like 300+ American History Research Paper Topics 500+ Statistics Research Topics 300+ Communication Research Topics 500+ Nursing Research Topic Ideas 300+ Mental Health Research Topics 500+ Sports Research Topics Advertisement Trends and Hot Topics of STEM and STEM Education: a Co-word Analysis of Literature Published in 2011–2020 Published: 23 February 2023 Volume 33 , pages 1069–1092, ( 2024 ) Cite this article Ying-Shao Hsu   ORCID: orcid.org/0000-0002-1635-8213 1 , 2 , Kai-Yu Tang   ORCID: orcid.org/0000-0002-3965-3055 3 & Tzu-Chiang Lin   ORCID: orcid.org/0000-0003-3842-3749 4 , 5   1297 Accesses 4 Citations Explore all metrics This study explored research trends in science, technology, engineering, and mathematics (STEM) education. Descriptive analysis and co-word analysis were used to examine articles published in Social Science Citation Index journals from 2011 to 2020. From a search of the Web of Science database, a total of 761 articles were selected as target samples for analysis. A growing number of STEM-related publications were published after 2016. The most frequently used keywords in these sample papers were also identified. Further analysis identified the leading journals and most represented countries among the target articles. A series of co-word analyses were conducted to reveal word co-occurrence according to the title, keywords, and abstract. Gender moderated engagement in STEM learning and career selection. Higher education was critical in training a STEM workforce to satisfy societal requirements for STEM roles. Our findings indicated that the attention of STEM education researchers has shifted to the professional development of teachers. Discussions and potential research directions in the field are included. This is a preview of subscription content, log in via an institution to check access. Access this article Subscribe and save. Get 10 units per month Download Article/Chapter or eBook 1 Unit = 1 Article or 1 Chapter Cancel anytime Price includes VAT (Russian Federation) Instant access to the full article PDF. Rent this article via DeepDyve Institutional subscriptions Similar content being viewed by others An Integrative Review with Word Cloud Analysis of STEM Education A systematic review of STEM education research in the GCC countries: trends, gaps and barriers Mathematics and interdisciplinary STEM education: recent developments and future directions Data availability. The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. Akgunduz, D. (2016). A Research about the placement of the top thousand students placed in STEM fields in Turkey between the years 2000 and 2014. EURASIA Journal of Mathematics, Science and Technology Education, 12 (5), 1365–1377. Google Scholar   Appianing, J., & Van Eck, R. N. (2018). 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Graduate Institute of Science Education, National Taiwan Normal University, No. 88, Ting-Jou Rd., Sec. 4, Taipei City, 116, Taiwan Ying-Shao Hsu Institute for Research Excellence in Learning Sciences, National Taiwan Normal University, No. 88, Ting-Jou Rd., Sec. 4, Taipei City, 116, Taiwan Graduate Institute of Library & Information Science, National Chung Hsing University, 145 Xingda Rd., South Dist., Taichung City, 402, Taiwan Kai-Yu Tang Center for Liberal Arts, National Kaohsiung University of Science and Technology, No. 415, Jiangong Rd., Sanmin Dist, Kaohsiung City, 807618, Taiwan Tzu-Chiang Lin Center for Teacher Education, National Kaohsiung University of Science and Technology, No. 415, Jiangong Rd., Sanmin Dist, Kaohsiung City, 807618, Taiwan You can also search for this author in PubMed   Google Scholar Corresponding author Correspondence to Tzu-Chiang Lin . Ethics declarations Ethical approval and consent to participate. This study involves neither human participants’ data nor relevant biological material. Ethics approval and informed consent are hence not applicable. Conflict of Interest The authors declare that they have no conflict of interest. Additional information Publisher's note. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Rights and permissions Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Reprints and permissions About this article Hsu, YS., Tang, KY. & Lin, TC. Trends and Hot Topics of STEM and STEM Education: a Co-word Analysis of Literature Published in 2011–2020. Sci & Educ 33 , 1069–1092 (2024). https://doi.org/10.1007/s11191-023-00419-6 Download citation Accepted : 26 January 2023 Published : 23 February 2023 Issue Date : August 2024 DOI : https://doi.org/10.1007/s11191-023-00419-6 Share this article Anyone you share the following link with will be able to read this content: Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative STEM education Co-word analysis Research trends Find a journal Publish with us Track your research Open access Published: 10 March 2020 Research and trends in STEM education: a systematic review of journal publications Yeping Li 1 , Ke Wang 2 , Yu Xiao 1 & Jeffrey E. Froyd 3   International Journal of STEM Education volume  7 , Article number:  11 ( 2020 ) Cite this article 178k Accesses 180 Citations 5 Altmetric Metrics details With the rapid increase in the number of scholarly publications on STEM education in recent years, reviews of the status and trends in STEM education research internationally support the development of the field. For this review, we conducted a systematic analysis of 798 articles in STEM education published between 2000 and the end of 2018 in 36 journals to get an overview about developments in STEM education scholarship. We examined those selected journal publications both quantitatively and qualitatively, including the number of articles published, journals in which the articles were published, authorship nationality, and research topic and methods over the years. The results show that research in STEM education is increasing in importance internationally and that the identity of STEM education journals is becoming clearer over time. Introduction A recent review of 144 publications in the International Journal of STEM Education ( IJ - STEM ) showed how scholarship in science, technology, engineering, and mathematics (STEM) education developed between August 2014 and the end of 2018 through the lens of one journal (Li, Froyd, & Wang, 2019 ). The review of articles published in only one journal over a short period of time prompted the need to review the status and trends in STEM education research internationally by analyzing articles published in a wider range of journals over a longer period of time. With global recognition of the growing importance of STEM education, we have witnessed the urgent need to support research and scholarship in STEM education (Li, 2014 , 2018a ). Researchers and educators have responded to this on-going call and published their scholarly work through many different publication outlets including journals, books, and conference proceedings. A simple Google search with the term “STEM,” “STEM education,” or “STEM education research” all returned more than 450,000,000 items. Such voluminous information shows the rapidly evolving and vibrant field of STEM education and sheds light on the volume of STEM education research. In any field, it is important to know and understand the status and trends in scholarship for the field to develop and be appropriately supported. This applies to STEM education. Conducting systematic reviews to explore the status and trends in specific disciplines is common in educational research. For example, researchers surveyed the historical development of research in mathematics education (Kilpatrick, 1992 ) and studied patterns in technology usage in mathematics education (Bray & Tangney, 2017 ; Sokolowski, Li, & Willson, 2015 ). In science education, Tsai and his colleagues have conducted a sequence of reviews of journal articles to synthesize research trends in every 5 years since 1998 (i.e., 1998–2002, 2003–2007, 2008–2012, and 2013–2017), based on publications in three main science education journals including, Science Education , the International Journal of Science Education , and the Journal of Research in Science Teaching (e.g., Lin, Lin, Potvin, & Tsai, 2019 ; Tsai & Wen, 2005 ). Erduran, Ozdem, and Park ( 2015 ) reviewed argumentation in science education research from 1998 to 2014 and Minner, Levy, and Century ( 2010 ) reviewed inquiry-based science instruction between 1984 and 2002. There are also many literature reviews and syntheses in engineering and technology education (e.g., Borrego, Foster, & Froyd, 2015 ; Xu, Williams, Gu, & Zhang, 2019 ). All of these reviews have been well received in different fields of traditional disciplinary education as they critically appraise and summarize the state-of-art of relevant research in a field in general or with a specific focus. Both types of reviews have been conducted with different methods for identifying, collecting, and analyzing relevant publications, and they differ in terms of review aim and topic scope, time period, and ways of literature selection. In this review, we systematically analyze journal publications in STEM education research to overview STEM education scholarship development broadly and globally. The complexity and ambiguity of examining the status and trends in STEM education research A review of research development in a field is relatively straight forward, when the field is mature and its scope can be well defined. Unlike discipline-based education research (DBER, National Research Council, 2012 ), STEM education is not a well-defined field. Conducting a comprehensive literature review of STEM education research require careful thought and clearly specified scope to tackle the complexity naturally associated with STEM education. In the following sub-sections, we provide some further discussion. Diverse perspectives about STEM and STEM education STEM education as explicated by the term does not have a long history. The interest in helping students learn across STEM fields can be traced back to the 1990s when the US National Science Foundation (NSF) formally included engineering and technology with science and mathematics in undergraduate and K-12 school education (e.g., National Science Foundation, 1998 ). It coined the acronym SMET (science, mathematics, engineering, and technology) that was subsequently used by other agencies including the US Congress (e.g., United States Congress House Committee on Science, 1998 ). NSF also coined the acronym STEM to replace SMET (e.g., Christenson, 2011 ; Chute, 2009 ) and it has become the acronym of choice. However, a consensus has not been reached on the disciplines included within STEM. To clarify its intent, NSF published a list of approved fields it considered under the umbrella of STEM (see http://bit.ly/2Bk1Yp5 ). The list not only includes disciplines widely considered under the STEM tent (called “core” disciplines, such as physics, chemistry, and materials research), but also includes disciplines in psychology and social sciences (e.g., political science, economics). However, NSF’s list of STEM fields is inconsistent with other federal agencies. Gonzalez and Kuenzi ( 2012 ) noted that at least two US agencies, the Department of Homeland Security and Immigration and Customs Enforcement, use a narrower definition that excludes social sciences. Researchers also view integration across different disciplines of STEM differently using various terms such as, multidisciplinary, interdisciplinary, and transdisciplinary (Vasquez, Sneider, & Comer, 2013 ). These are only two examples of the ambiguity and complexity in describing and specifying what constitutes STEM. Multiple perspectives about the meaning of STEM education adds further complexity to determining the extent to which scholarly activity can be categorized as STEM education. For example, STEM education can be viewed with a broad and inclusive perspective to include education in the individual disciplines of STEM, i.e., science education, technology education, engineering education, and mathematics education, as well as interdisciplinary or cross-disciplinary combinations of the individual STEM disciplines (English, 2016 ; Li, 2014 ). On the other hand, STEM education can be viewed by others as referring only to interdisciplinary or cross-disciplinary combinations of the individual STEM disciplines (Honey, Pearson, & Schweingruber, 2014 ; Johnson, Peters-Burton, & Moore, 2015 ; Kelley & Knowles, 2016 ; Li, 2018a ). These multiple perspectives allow scholars to publish articles in a vast array and diverse journals, as long as journals are willing to take the position as connected with STEM education. At the same time, however, the situation presents considerable challenges for researchers intending to locate, identify, and classify publications as STEM education research. To tackle such challenges, we tried to find out what we can learn from prior reviews related to STEM education. Guidance from prior reviews related to STEM education A search for reviews of STEM education research found multiple reviews that could suggest approaches for identifying publications (e.g., Brown, 2012 ; Henderson, Beach, & Finkelstein, 2011 ; Kim, Sinatra, & Seyranian, 2018 ; Margot & Kettler, 2019 ; Minichiello, Hood, & Harkness, 2018 ; Mizell & Brown, 2016 ; Thibaut et al., 2018 ; Wu & Rau, 2019 ). The review conducted by Brown ( 2012 ) examined the research base of STEM education. He addressed the complexity and ambiguity by confining the review with publications in eight journals, two in each individual discipline, one academic research journal (e.g., the Journal of Research in Science Teaching ) and one practitioner journal (e.g., Science Teacher ). Journals were selected based on suggestions from some faculty members and K-12 teachers. Out of 1100 articles published in these eight journals from January 1, 2007, to October 1, 2010, Brown located 60 articles that authors self-identified as connected to STEM education. He found that the vast majority of these 60 articles focused on issues beyond an individual discipline and there was a research base forming for STEM education. In a follow-up study, Mizell and Brown ( 2016 ) reviewed articles published from January 2013 to October 2015 in the same eight journals plus two additional journals. Mizell and Brown used the same criteria to identify and include articles that authors self-identified as connected to STEM education, i.e., if the authors included STEM in the title or author-supplied keywords. In comparison to Brown’s findings, they found that many more STEM articles were published in a shorter time period and by scholars from many more different academic institutions. Taking together, both Brown ( 2012 ) and Mizell and Brown ( 2016 ) tended to suggest that STEM education mainly consists of interdisciplinary or cross-disciplinary combinations of the individual STEM disciplines, but their approach consisted of selecting a limited number of individual discipline-based journals and then selecting articles that authors self-identified as connected to STEM education. In contrast to reviews on STEM education, in general, other reviews focused on specific issues in STEM education (e.g., Henderson et al., 2011 ; Kim et al., 2018 ; Margot & Kettler, 2019 ; Minichiello et al., 2018 ; Schreffler, Vasquez III, Chini, & James, 2019 ; Thibaut et al., 2018 ; Wu & Rau, 2019 ). For example, the review by Henderson et al. ( 2011 ) focused on instructional change in undergraduate STEM courses based on 191 conceptual and empirical journal articles published between 1995 and 2008. Margot and Kettler ( 2019 ) focused on what is known about teachers’ values, beliefs, perceived barriers, and needed support related to STEM education based on 25 empirical journal articles published between 2000 and 2016. The focus of these reviews allowed the researchers to limit the number of articles considered, and they typically used keyword searches of selected databases to identify articles on STEM education. Some researchers used this approach to identify publications from journals only (e.g., Henderson et al., 2011 ; Margot & Kettler, 2019 ; Schreffler et al., 2019 ), and others selected and reviewed publications beyond journals (e.g., Minichiello et al., 2018 ; Thibaut et al., 2018 ; Wu & Rau, 2019 ). The discussion in this section suggests possible reasons contributing to the absence of a general literature review of STEM education research and development: (1) diverse perspectives in existence about STEM and STEM education that contribute to the difficulty of specifying a scope of literature review, (2) its short but rapid development history in comparison to other discipline-based education (e.g., science education), and (3) difficulties in deciding how to establish the scope of the literature review. With respect to the third reason, prior reviews have used one of two approaches to identify and select articles: (a) identifying specific journals first and then searching and selecting specific articles from these journals (e.g., Brown, 2012 ; Erduran et al., 2015 ; Mizell & Brown, 2016 ) and (b) conducting selected database searches with keywords based on a specific focus (e.g., Margot & Kettler, 2019 ; Thibaut et al., 2018 ). However, neither the first approach of selecting a limited number of individual discipline-based journals nor the second approach of selecting a specific focus for the review leads to an approach that provides a general overview of STEM education scholarship development based on existing journal publications. Current review Two issues were identified in setting the scope for this review. What time period should be considered? What publications will be selected for review? Time period We start with the easy one first. As discussed above, the acronym STEM did exist until the early 2000s. Although the existence of the acronym does not generate scholarship on student learning in STEM disciplines, it is symbolic and helps focus attention to efforts in STEM education. Since we want to examine the status and trends in STEM education, it is reasonable to start with the year 2000. Then, we can use the acronym of STEM as an identifier in locating specific research articles in a way as done by others (e.g., Brown, 2012 ; Mizell & Brown, 2016 ). We chose the end of 2018 as the end of the time period for our review that began during 2019. Focusing on publications beyond individual discipline-based journals As mentioned before, scholars responded to the call for scholarship development in STEM education with publications that appeared in various outlets and diverse languages, including journals, books, and conference proceedings. However, journal publications are typically credited and valued as one of the most important outlets for research exchange (e.g., Erduran et al., 2015 ; Henderson et al., 2011 ; Lin et al., 2019 ; Xu et al., 2019 ). Thus, in this review, we will also focus on articles published in journals in English. The discourse above on the complexity and ambiguity regarding STEM education suggests that scholars may publish their research in a wide range of journals beyond individual discipline-based journals. To search and select articles from a wide range of journals, we thought about the approach of searching selected databases with keywords as other scholars used in reviewing STEM education with a specific focus. However, existing journals in STEM education do not have a long history. In fact, IJ-STEM is the first journal in STEM education that has just been accepted into the Social Sciences Citation Index (SSCI) (Li, 2019a ). Publications in many STEM education journals are practically not available in several important and popular databases, such as the Web of Science and Scopus. Moreover, some journals in STEM education were not normalized due to a journal’s name change or irregular publication schedule. For example, the Journal of STEM Education was named as Journal of SMET Education when it started in 2000 in a print format, and the journal’s name was not changed until 2003, Vol 4 (3 and 4), and also went fully on-line starting 2004 (Raju & Sankar, 2003 ). A simple Google Scholar search with keywords will not be able to provide accurate information, unless you visit the journal’s website to check all publications over the years. Those added complexities prevented us from taking the database search as a viable approach. Thus, we decided to identify journals first and then search and select articles from these journals. Further details about the approach are provided in the “ Method ” section. Research questions Given a broader range of journals and a longer period of time to be covered in this review, we can examine some of the same questions as the IJ-STEM review (Li, Froyd, & Wang, 2019 ), but we do not have access to data on readership, articles accessed, or articles cited for the other journals selected for this review. Specifically, we are interested in addressing the following six research questions: What were the status and trends in STEM education research from 2000 to the end of 2018 based on journal publications? What were the patterns of publications in STEM education research across different journals? Which countries or regions, based on the countries or regions in which authors were located, contributed to journal publications in STEM education? What were the patterns of single-author and multiple-author publications in STEM education? What main topics had emerged in STEM education research based on the journal publications? What research methods did authors tend to use in conducting STEM education research? Based on the above discussion, we developed the methods for this literature review to follow careful sequential steps to identify journals first and then identify and select STEM education research articles published in these journals from January 2000 to the end of 2018. The methods should allow us to obtain a comprehensive overview about the status and trends of STEM education research based on a systematic analysis of related publications from a broad range of journals and over a longer period of time. Identifying journals We used the following three steps to search and identify journals for inclusion: We assumed articles on research in STEM education have been published in journals that involve more than one traditional discipline. Thus, we used Google to search and identify all education journals with their titles containing either two, three, or all four disciplines of STEM. For example, we did Google search of all the different combinations of three areas of science, mathematics, technology Footnote 1 , and engineering as contained in a journal’s title. In addition, we also searched possible journals containing the word STEAM in the title. Since STEM education may be viewed as encompassing discipline-based education research, articles on STEM education research may have been published in traditional discipline-based education journals, such as the Journal of Research in Science Teaching . However, there are too many such journals. Yale’s Poorvu Center for Teaching and Learning has listed 16 journals that publish articles spanning across undergraduate STEM education disciplines (see https://poorvucenter.yale.edu/FacultyResources/STEMjournals ). Thus, we selected from the list some individual discipline-based education research journals, and also added a few more common ones such as the Journal of Engineering Education . Since articles on research in STEM education have appeared in some general education research journals, especially those well-established ones. Thus, we identified and selected a few of those journals that we noticed some publications in STEM education research. Following the above three steps, we identified 45 journals (see Table  1 ). Identifying articles In this review, we will not discuss or define the meaning of STEM education. We used the acronym STEM (or STEAM, or written as the phrase of “science, technology, engineering, and mathematics”) as a term in our search of publication titles and/or abstracts. To identify and select articles for review, we searched all items published in those 45 journals and selected only those articles that author(s) self-identified with the acronym STEM (or STEAM, or written as the phrase of “science, technology, engineering, and mathematics”) in the title and/or abstract. We excluded publications in the sections of practices, letters to editors, corrections, and (guest) editorials. Our search found 798 publications that authors self-identified as in STEM education, identified from 36 journals. The remaining 9 journals either did not have publications that met our search terms or published in another language other than English (see the two separate lists in Table 1 ). Data analysis To address research question 3, we analyzed authorship to examine which countries/regions contributed to STEM education research over the years. Because each publication may have either one or multiple authors, we used two different methods to analyze authorship nationality that have been recognized as valuable from our review of IJ-STEM publications (Li, Froyd, & Wang, 2019 ). The first method considers only the corresponding author’s (or the first author, if no specific indication is given about the corresponding author) nationality and his/her first institution affiliation, if multiple institution affiliations are listed. Method 2 considers every author of a publication, using the following formula (Howard, Cole, & Maxwell, 1987 ) to quantitatively assign and estimate each author’s contribution to a publication (and thus associated institution’s productivity), when multiple authors are included in a publication. As an example, each publication is given one credit point. For the publication co-authored by two, the first author would be given 0.6 and the second author 0.4 credit point. For an article contributed jointly by three authors, the three authors would be credited with scores of 0.47, 0.32, and 0.21, respectively. After calculating all the scores for each author of each paper, we added all the credit scores together in terms of each author’s country/region. For brevity, we present only the top 10 countries/regions in terms of their total credit scores calculated using these two different methods, respectively. To address research question 5, we used the same seven topic categories identified and used in our review of IJ-STEM publications (Li, Froyd, & Wang, 2019 ). We tested coding 100 articles first to ensure the feasibility. Through test-coding and discussions, we found seven topic categories could be used to examine and classify all 798 items. K-12 teaching, teacher, and teacher education in STEM (including both pre-service and in-service teacher education) Post-secondary teacher and teaching in STEM (including faculty development, etc.) K-12 STEM learner, learning, and learning environment Post-secondary STEM learner, learning, and learning environments (excluding pre-service teacher education) Policy, curriculum, evaluation, and assessment in STEM (including literature review about a field in general) Culture and social and gender issues in STEM education History, epistemology, and perspectives about STEM and STEM education To address research question 6, we coded all 798 publications in terms of (1) qualitative methods, (2) quantitative methods, (3) mixed methods, and (4) non-empirical studies (including theoretical or conceptual papers, and literature reviews). We assigned each publication to only one research topic and one method, following the process used in the IJ-STEM review (Li, Froyd, & Wang, 2019 ). When there was more than one topic or method that could have been used for a publication, a decision was made in choosing and assigning a topic or a method. The agreement between two coders for all 798 publications was 89.5%. When topic and method coding discrepancies occurred, a final decision was reached after discussion. Results and discussion In the following sections, we report findings as corresponding to each of the six research questions. The status and trends of journal publications in STEM education research from 2000 to 2018 Figure  1 shows the number of publications per year. As Fig.  1 shows, the number of publications increased each year beginning in 2010. There are noticeable jumps from 2015 to 2016 and from 2017 to 2018. The result shows that research in STEM education had grown significantly since 2010, and the most recent large number of STEM education publications also suggests that STEM education research gained its own recognition by many different journals for publication as a hot and important topic area. The distribution of STEM education publications over the years Among the 798 articles, there were 549 articles with the word “STEM” (or STEAM, or written with the phrase of “science, technology, engineering, and mathematics”) included in the article’s title or both title and abstract and 249 articles without such identifiers included in the title but abstract only. The results suggest that many scholars tended to include STEM in the publications’ titles to highlight their research in or about STEM education. Figure  2 shows the number of publications per year where publications are distinguished depending on whether they used the term STEM in the title or only in the abstract. The number of publications in both categories had significant increases since 2010. Use of the acronym STEM in the title was growing at a faster rate than using the acronym only in the abstract. The trends of STEM education publications with vs. without STEM included in the title Not all the publications that used the acronym STEM in the title and/or abstract reported on a study involving all four STEM areas. For each publication, we further examined the number of the four areas involved in the reported study. Figure  3 presents the number of publications categorized by the number of the four areas involved in the study, breaking down the distribution of these 798 publications in terms of the content scope being focused on. Studies involving all four STEM areas are the most numerous with 488 (61.2%) publications, followed by involving one area (141, 17.7%), then studies involving both STEM and non-STEM (84, 10.5%), and finally studies involving two or three areas of STEM (72, 9%; 13, 1.6%; respectively). Publications that used the acronym STEAM in either the title or abstract were classified as involving both STEM and non-STEM. For example, both of the following publications were included in this category. Dika and D’Amico ( 2016 ). “Early experiences and integration in the persistence of first-generation college students in STEM and non-STEM majors.” Journal of Research in Science Teaching , 53 (3), 368–383. (Note: this article focused on early experience in both STEM and Non-STEM majors.) Sochacka, Guyotte, and Walther ( 2016 ). “Learning together: A collaborative autoethnographic exploration of STEAM (STEM+ the Arts) education.” Journal of Engineering Education , 105 (1), 15–42. (Note: this article focused on STEAM (both STEM and Arts).) Publication distribution in terms of content scope being focused on. (Note: 1=single subject of STEM, 2=two subjects of STEM, 3=three subjects of STEM, 4=four subjects of STEM, 5=topics related to both STEM and non-STEM) Figure  4 presents the number of publications per year in each of the five categories described earlier (category 1, one area of STEM; category 2, two areas of STEM; category 3, three areas of STEM; category 4, four areas of STEM; category 5, STEM and non-STEM). The category that had grown most rapidly since 2010 is the one involving all four areas. Recent growth in the number of publications in category 1 likely reflected growing interest of traditional individual disciplinary based educators in developing and sharing multidisciplinary and interdisciplinary scholarship in STEM education, as what was noted recently by Li and Schoenfeld ( 2019 ) with publications in IJ-STEM. Publication distribution in terms of content scope being focused on over the years Patterns of publications across different journals Among the 36 journals that published STEM education articles, two are general education research journals (referred to as “subject-0”), 12 with their titles containing one discipline of STEM (“subject-1”), eight with journal’s titles covering two disciplines of STEM (“subject-2”), six covering three disciplines of STEM (“subject-3”), seven containing the word STEM (“subject-4”), and one in STEAM education (“subject-5”). Table  2 shows that both subject-0 and subject-1 journals were usually mature journals with a long history, and they were all traditional subscription-based journals, except the Journal of Pre - College Engineering Education Research , a subject-1 journal established in 2011 that provided open access (OA). In comparison to subject-0 and subject-1 journals, subject-2 and subject-3 journals were relatively newer but still had quite many years of history on average. There are also some more journals in these two categories that provided OA. Subject-4 and subject-5 journals had a short history, and most provided OA. The results show that well-established journals had tended to focus on individual disciplines or education research in general. Multidisciplinary and interdisciplinary education journals were started some years later, followed by the recent establishment of several STEM or STEAM journals. Table 2 also shows that subject-1, subject-2, and subject-4 journals published approximately a quarter each of the publications. The number of publications in subject-1 journals is interested, because we selected a relatively limited number of journals in this category. There are many other journals in the subject-1 category (as well as subject-0 journals) that we did not select, and thus it is very likely that we did not include some STEM education articles published in subject-0 or subject-1 journals that we did not include in our study. Figure  5 shows the number of publications per year in each of the five categories described earlier (subject-0 through subject-5). The number of publications per year in subject-5 and subject-0 journals did not change much over the time period of the study. On the other hand, the number of publications per year in subject-4 (all 4 areas), subject-1 (single area), and subject-2 journals were all over 40 by the end of the study period. The number of publications per year in subject-3 journals increased but remained less than 30. At first sight, it may be a bit surprising that the number of publications in STEM education per year in subject-1 journals increased much faster than those in subject-2 journals over the past few years. However, as Table 2 indicates these journals had long been established with great reputations, and scholars would like to publish their research in such journals. In contrast to the trend in subject-1 journals, the trend in subject-4 journals suggests that STEM education journals collectively started to gain its own identity for publishing and sharing STEM education research. STEM education publication distribution across different journal categories over the years. (Note: 0=subject-0; 1=subject-1; 2=subject-2; 3=subject-3; 4=subject-4; 5=subject-5) Figure  6 shows the number of STEM education publications in each journal where the bars are color-coded (yellow, subject-0; light blue, subject-1; green, subject-2; purple, subject-3; dark blue, subject-4; and black, subject-5). There is no clear pattern shown in terms of the overall number of STEM education publications across categories or journals, but very much individual journal-based performance. The result indicates that the number of STEM education publications might heavily rely on the individual journal’s willingness and capability of attracting STEM education research work and thus suggests the potential value of examining individual journal’s performance. Publication distribution across all 36 individual journals across different categories with the same color-coded for journals in the same subject category The top five journals in terms of the number of STEM education publications are Journal of Science Education and Technology (80 publications, journal number 25 in Fig.  6 ), Journal of STEM Education (65 publications, journal number 26), International Journal of STEM Education (64 publications, journal number 17), International Journal of Engineering Education (54 publications, journal number 12), and School Science and Mathematics (41 publications, journal number 31). Among these five journals, two journals are specifically on STEM education (J26, J17), two on two subjects of STEM (J25, J31), and one on one subject of STEM (J12). Figure  7 shows the number of STEM education publications per year in each of these top five journals. As expected, based on earlier trends, the number of publications per year increased over the study period. The largest increase was in the International Journal of STEM Education (J17) that was established in 2014. As the other four journals were all established in or before 2000, J17’s short history further suggests its outstanding performance in attracting and publishing STEM education articles since 2014 (Li, 2018b ; Li, Froyd, & Wang, 2019 ). The increase was consistent with the journal’s recognition as the first STEM education journal for inclusion in SSCI starting in 2019 (Li, 2019a ). Publication distribution of selected five journals over the years. (Note: J12: International Journal of Engineering Education; J17: International Journal of STEM Education; J25: Journal of Science Education and Technology; J26: Journal of STEM Education; J31: School Science and Mathematics) Top 10 countries/regions where scholars contributed journal publications in STEM education Table  3 shows top countries/regions in terms of the number of publications, where the country/region was established by the authorship using the two different methods presented above. About 75% (depending on the method) of contributions were made by authors from the USA, followed by Australia, Canada, Taiwan, and UK. Only Africa as a continent was not represented among the top 10 countries/regions. The results are relatively consistent with patterns reported in the IJ-STEM study (Li, Froyd, & Wang, 2019 ) Further examination of Table 3 reveals that the two methods provide not only fairly consistent results but also yield some differences. For example, Israel and Germany had more publication credit if only the corresponding author was considered, but South Korea and Turkey had more publication credit when co-authors were considered. The results in Table 3 show that each method has value when analyzing and comparing publications by country/region or institution based on authorship. Recognizing that, as shown in Fig. 1 , the number of publications per year increased rapidly since 2010, Table  4 shows the number of publications by country/region over a 10-year period (2009–2018) and Table 5 shows the number of publications by country/region over a 5-year period (2014–2018). The ranks in Tables  3 , 4 , and 5 are fairly consistent, but that would be expected since the larger numbers of publications in STEM education had occurred in recent years. At the same time, it is interesting to note in Table 5 some changes over the recent several years with Malaysia, but not Israel, entering the top 10 list when either method was used to calculate author's credit. Patterns of single-author and multiple-author publications in STEM education Since STEM education differs from traditional individual disciplinary education, we are interested in determining how common joint co-authorship with collaborations was in STEM education articles. Figure  8 shows that joint co-authorship was very common among these 798 STEM education publications, with 83.7% publications with two or more co-authors. Publications with two, three, or at least five co-authors were highest, with 204, 181, and 157 publications, respectively. Number of publications with single or different joint authorship. (Note: 1=single author; 2=two co-authors; 3=three co-authors; 4=four co-authors; 5=five or more co-authors) Figure  9 shows the number of publications per year using the joint authorship categories in Fig.  8 . Each category shows an increase consistent with the increase shown in Fig. 1 for all 798 publications. By the end of the time period, the number of publications with two, three, or at least five co-authors was the largest, which might suggest an increase in collaborations in STEM education research. Publication distribution with single or different joint authorship over the years. (Note: 1=single author; 2=two co-authors; 3=three co-authors; 4=four co-authors; 5=five or more co-authors) Co-authors can be from the same or different countries/regions. Figure  10 shows the number of publications per year by single authors (no collaboration), co-authors from the same country (collaboration in a country/region), and co-authors from different countries (collaboration across countries/regions). Each year the largest number of publications was by co-authors from the same country, and the number increased dramatically during the period of the study. Although the number of publications in the other two categories increased, the numbers of publications were noticeably fewer than the number of publications by co-authors from the same country. Publication distribution in authorship across different categories in terms of collaboration over the years Published articles by research topics Figure  11 shows the number of publications in each of the seven topic categories. The topic category of goals, policy, curriculum, evaluation, and assessment had almost half of publications (375, 47%). Literature reviews were included in this topic category, as providing an overview assessment of education and research development in a topic area or a field. Sample publications included in this category are listed as follows: DeCoito ( 2016 ). “STEM education in Canada: A knowledge synthesis.” Canadian Journal of Science , Mathematics and Technology Education , 16 (2), 114–128. (Note: this article provides a national overview of STEM initiatives and programs, including success, criteria for effective programs and current research in STEM education.) Ring-Whalen, Dare, Roehrig, Titu, and Crotty ( 2018 ). “From conception to curricula: The role of science, technology, engineering, and mathematics in integrated STEM units.” International Journal of Education in Mathematics Science and Technology , 6 (4), 343–362. (Note: this article investigates the conceptions of integrated STEM education held by in-service science teachers through the use of photo-elicitation interviews and examines how those conceptions were reflected in teacher-created integrated STEM curricula.) Schwab et al. ( 2018 ). “A summer STEM outreach program run by graduate students: Successes, challenges, and recommendations for implementation.” Journal of Research in STEM Education , 4 (2), 117–129. (Note: the article details the organization and scope of the Foundation in Science and Mathematics Program and evaluates this program.) Frequencies of publications’ research topic distributions. (Note: 1=K-12 teaching, teacher and teacher education; 2=Post-secondary teacher and teaching; 3=K-12 STEM learner, learning, and learning environment; 4=Post-secondary STEM learner, learning, and learning environments; 5=Goals and policy, curriculum, evaluation, and assessment (including literature review); 6=Culture, social, and gender issues; 7=History, philosophy, Epistemology, and nature of STEM and STEM education) The topic with the second most publications was “K-12 teaching, teacher and teacher education” (103, 12.9%), followed closely by “K-12 learner, learning, and learning environment” (97, 12.2%). The results likely suggest the research community had a broad interest in both teaching and learning in K-12 STEM education. The top three topics were the same in the IJ-STEM review (Li, Froyd, & Wang, 2019 ). Figure  11 also shows there was a virtual tie between two topics with the fourth most cumulative publications, “post-secondary STEM learner & learning” (76, 9.5%) and “culture, social, and gender issues in STEM” (78, 9.8%), such as STEM identity, students’ career choices in STEM, and inclusion. This result is different from the IJ-STEM review (Li, Froyd, & Wang, 2019 ), where “post-secondary STEM teacher & teaching” and “post-secondary STEM learner & learning” were tied as the fourth most common topics. This difference is likely due to the scope of journals and the length of the time period being reviewed. Figure  12 shows the number of publications per year in each topic category. As expected from the results in Fig.  11 the number of publications in topic category 5 (goals, policy, curriculum, evaluation, and assessment) was the largest each year. The numbers of publications in topic category 3 (K-12 learner, learning, and learning environment), 1 (K-12 teaching, teacher, and teacher education), 6 (culture, social, and gender issues in STEM), and 4 (post-secondary STEM learner and learning) were also increasing. Although Fig.  11 shows the number of publications in topic category 1 was slightly more than the number of publications in topic category 3 (see Fig.  11 ), the number of publications in topic category 3 was increasing more rapidly in recent years than its counterpart in topic category 1. This may suggest a more rapidly growing interest in K-12 STEM learner, learning, and learning environment. The numbers of publications in topic categories 2 and 7 were not increasing, but the number of publications in IJ-STEM in topic category 2 was notable (Li, Froyd, & Wang, 2019 ). It will be interesting to follow trends in the seven topic categories in the future. Publication distributions in terms of research topics over the years Published articles by research methods Figure  13 shows the number of publications per year by research methods in empirical studies. Publications with non-empirical studies are shown in a separate category. Although the number of publications in each of the four categories increased during the study period, there were many more publications presenting empirical studies than those without. For those with empirical studies, the number of publications using quantitative methods increased most rapidly in recent years, followed by qualitative and then mixed methods. Although there were quite many publications with non-empirical studies (e.g., theoretical or conceptual papers, literature reviews) during the study period, the increase of the number of publications in this category was noticeably less than empirical studies. Publication distributions in terms of research methods over the years. (Note: 1=qualitative, 2=quantitative, 3=mixed, 4=Non-empirical) Concluding remarks The systematic analysis of publications that were considered to be in STEM education in 36 selected journals shows tremendous growth in scholarship in this field from 2000 to 2018, especially over the past 10 years. Our analysis indicates that STEM education research has been increasingly recognized as an important topic area and studies were being published across many different journals. Scholars still hold diverse perspectives about how research is designated as STEM education; however, authors have been increasingly distinguishing their articles with STEM, STEAM, or related words in the titles, abstracts, and lists of keywords during the past 10 years. Moreover, our systematic analysis shows a dramatic increase in the number of publications in STEM education journals in recent years, which indicates that these journals have been collectively developing their own professional identity. In addition, the International Journal of STEM Education has become the first STEM education journal to be accepted in SSCI in 2019 (Li, 2019a ). The achievement may mark an important milestone as STEM education journals develop their own identity for publishing and sharing STEM education research. Consistent with our previous reviews (Li, Froyd, & Wang, 2019 ; Li, Wang, & Xiao, 2019 ), the vast majority of publications in STEM education research were contributed by authors from the USA, where STEM and STEAM education originated, followed by Australia, Canada, and Taiwan. At the same time, authors in some countries/regions in Asia were becoming very active in the field over the past several years. This trend is consistent with findings from the IJ-STEM review (Li, Froyd, & Wang, 2019 ). We certainly hope that STEM education scholarship continues its development across all five continents to support educational initiatives and programs in STEM worldwide. Our analysis has shown that collaboration, as indicated by publications with multiple authors, has been very common among STEM education scholars, as that is often how STEM education distinguishes itself from the traditional individual disciplinary based education. Currently, most collaborations occurred among authors from the same country/region, although collaborations across cross-countries/regions were slowly increasing. With the rapid changes in STEM education internationally (Li, 2019b ), it is often difficult for researchers to get an overall sense about possible hot topics in STEM education especially when STEM education publications appeared in a vast array of journals across different fields. Our systematic analysis of publications has shown that studies in the topic category of goals, policy, curriculum, evaluation, and assessment have been the most prevalent, by far. Our analysis also suggests that the research community had a broad interest in both teaching and learning in K-12 STEM education. These top three topic categories are the same as in the IJ-STEM review (Li, Froyd, & Wang, 2019 ). Work in STEM education will continue to evolve and it will be interesting to review the trends in another 5 years. Encouraged by our recent IJ-STEM review, we began this review with an ambitious goal to provide an overview of the status and trends of STEM education research. In a way, this systematic review allowed us to achieve our initial goal with a larger scope of journal selection over a much longer period of publication time. At the same time, there are still limitations, such as the decision to limit the number of journals from which we would identify publications for analysis. We understand that there are many publications on STEM education research that were not included in our review. Also, we only identified publications in journals. Although this is one of the most important outlets for scholars to share their research work, future reviews could examine publications on STEM education research in other venues such as books, conference proceedings, and grant proposals. Availability of data and materials The data and materials used and analyzed for the report are publicly available at the various journal websites. Journals containing the word "computers" or "ICT" appeared automatically when searching with the word "technology". Thus, the word of "computers" or "ICT" was taken as equivalent to "technology" if appeared in a journal's name. Abbreviations Information and Communications Technology International Journal of STEM Education Kindergarten–Grade 12 Science, Mathematics, Engineering, and Technology Science, Technology, Engineering, Arts, and Mathematics Science, Technology, Engineering, and Mathematics Borrego, M., Foster, M. J., & Froyd, J. E. (2015). 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International Journal of Technology and Design Education . https://doi.org/10.1007/s10798-019-09508-6 . Download references Not applicable Author information Authors and affiliations. Texas A&M University, College Station, TX, 77843-4232, USA Yeping Li & Yu Xiao Nicholls State University, Thibodaux, LA, 70310, USA Ohio State University, Columbus, OH, 43210, USA Jeffrey E. Froyd You can also search for this author in PubMed   Google Scholar Contributions YL conceptualized the study and drafted the manuscript. KW and YX contributed with data collection, coding, and analyses. JEF reviewed drafts and contributed to manuscript revisions. All authors read and approved the final manuscript. Corresponding author Correspondence to Yeping Li . Ethics declarations Competing interests. The authors declare that they have no competing interests. Additional information Publisher’s note. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Rights and permissions Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Reprints and permissions About this article Cite this article. Li, Y., Wang, K., Xiao, Y. et al. Research and trends in STEM education: a systematic review of journal publications. IJ STEM Ed 7 , 11 (2020). https://doi.org/10.1186/s40594-020-00207-6 Download citation Received : 10 February 2020 Accepted : 12 February 2020 Published : 10 March 2020 DOI : https://doi.org/10.1186/s40594-020-00207-6 Share this article Anyone you share the following link with will be able to read this content: Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative Journal publication Literature review STEM education research 6.1 Overview of Non-Experimental Research Learning objectives. Define non-experimental research, distinguish it clearly from experimental research, and give several examples. Explain when a researcher might choose to conduct non-experimental research as opposed to experimental research. What Is Non-Experimental Research? Non-experimental research  is research that lacks the manipulation of an independent variable. Rather than manipulating an independent variable, researchers conducting non-experimental research simply measure variables as they naturally occur (in the lab or real world). Most researchers in psychology consider the distinction between experimental and non-experimental research to be an extremely important one. This is because although experimental research can provide strong evidence that changes in an independent variable cause differences in a dependent variable, non-experimental research generally cannot. As we will see, however, this inability to make causal conclusions does not mean that non-experimental research is less important than experimental research. When to Use Non-Experimental Research As we saw in the last chapter , experimental research is appropriate when the researcher has a specific research question or hypothesis about a causal relationship between two variables—and it is possible, feasible, and ethical to manipulate the independent variable. It stands to reason, therefore, that non-experimental research is appropriate—even necessary—when these conditions are not met. There are many times in which non-experimental research is preferred, including when: the research question or hypothesis relates to a single variable rather than a statistical relationship between two variables (e.g., How accurate are people’s first impressions?). the research question pertains to a non-causal statistical relationship between variables (e.g., is there a correlation between verbal intelligence and mathematical intelligence?). the research question is about a causal relationship, but the independent variable cannot be manipulated or participants cannot be randomly assigned to conditions or orders of conditions for practical or ethical reasons (e.g., does damage to a person’s hippocampus impair the formation of long-term memory traces?). the research question is broad and exploratory, or is about what it is like to have a particular experience (e.g., what is it like to be a working mother diagnosed with depression?). Again, the choice between the experimental and non-experimental approaches is generally dictated by the nature of the research question. Recall the three goals of science are to describe, to predict, and to explain. If the goal is to explain and the research question pertains to causal relationships, then the experimental approach is typically preferred. If the goal is to describe or to predict, a non-experimental approach will suffice. But the two approaches can also be used to address the same research question in complementary ways. For example, Similarly, after his original study, Milgram conducted experiments to explore the factors that affect obedience. He manipulated several independent variables, such as the distance between the experimenter and the participant, the participant and the confederate, and the location of the study (Milgram, 1974) [1] . Types of Non-Experimental Research Non-experimental research falls into three broad categories: cross-sectional research, correlational research, and observational research.  First, cross-sectional research  involves comparing two or more pre-existing groups of people. What makes this approach non-experimental is that there is no manipulation of an independent variable and no random assignment of participants to groups. Imagine, for example, that a researcher administers the Rosenberg Self-Esteem Scale to 50 American college students and 50 Japanese college students. Although this “feels” like a between-subjects experiment, it is a cross-sectional study because the researcher did not manipulate the students’ nationalities. As another example, if we wanted to compare the memory test performance of a group of cannabis users with a group of non-users, this would be considered a cross-sectional study because for ethical and practical reasons we would not be able to randomly assign participants to the cannabis user and non-user groups. Rather we would need to compare these pre-existing groups which could introduce a selection bias (the groups may differ in other ways that affect their responses on the dependent variable). For instance, cannabis users are more likely to use more alcohol and other drugs and these differences may account for differences in the dependent variable across groups, rather than cannabis use per se. Cross-sectional designs are commonly used by developmental psychologists who study aging and by researchers interested in sex differences. Using this design, developmental psychologists compare groups of people of different ages (e.g., young adults spanning from 18-25 years of age versus older adults spanning 60-75 years of age) on various dependent variables (e.g., memory, depression, life satisfaction). Of course, the primary limitation of using this design to study the effects of aging is that differences between the groups other than age may account for differences in the dependent variable. For instance, differences between the groups may reflect the generation that people come from (a cohort effect) rather than a direct effect of age. For this reason, longitudinal studies in which one group of people is followed as they age offer a superior means of studying the effects of aging. Once again, cross-sectional designs are also commonly used to study sex differences. Since researchers cannot practically or ethically manipulate the sex of their participants they must rely on cross-sectional designs to compare groups of men and women on different outcomes (e.g., verbal ability, substance use, depression). Using these designs researchers have discovered that men are more likely than women to suffer from substance abuse problems while women are more likely than men to suffer from depression. But, using this design it is unclear what is causing these differences. So, using this design it is unclear whether these differences are due to environmental factors like socialization or biological factors like hormones? When researchers use a participant characteristic to create groups (nationality, cannabis use, age, sex), the independent variable is usually referred to as an experimenter-selected independent variable (as opposed to the experimenter-manipulated independent variables used in experimental research). Figure 6.1 shows data from a hypothetical study on the relationship between whether people make a daily list of things to do (a “to-do list”) and stress. Notice that it is unclear whether this is an experiment or a cross-sectional study because it is unclear whether the independent variable was manipulated by the researcher or simply selected by the researcher. If the researcher randomly assigned some participants to make daily to-do lists and others not to, then the independent variable was experimenter-manipulated and it is a true experiment. If the researcher simply asked participants whether they made daily to-do lists or not, then the independent variable it is experimenter-selected and the study is cross-sectional. The distinction is important because if the study was an experiment, then it could be concluded that making the daily to-do lists reduced participants’ stress. But if it was a cross-sectional study, it could only be concluded that these variables are statistically related. Perhaps being stressed has a negative effect on people’s ability to plan ahead. Or perhaps people who are more conscientious are more likely to make to-do lists and less likely to be stressed. The crucial point is that what defines a study as experimental or cross-sectional l is not the variables being studied, nor whether the variables are quantitative or categorical, nor the type of graph or statistics used to analyze the data. It is how the study is conducted. Figure 6.1  Results of a Hypothetical Study on Whether People Who Make Daily To-Do Lists Experience Less Stress Than People Who Do Not Make Such Lists Second, the most common type of non-experimental research conducted in Psychology is correlational research. Correlational research is considered non-experimental because it focuses on the statistical relationship between two variables but does not include the manipulation of an independent variable.  More specifically, in correlational research , the researcher measures two continuous variables with little or no attempt to control extraneous variables and then assesses the relationship between them. As an example, a researcher interested in the relationship between self-esteem and school achievement could collect data on students’ self-esteem and their GPAs to see if the two variables are statistically related. Correlational research is very similar to cross-sectional research, and sometimes these terms are used interchangeably. The distinction that will be made in this book is that, rather than comparing two or more pre-existing groups of people as is done with cross-sectional research, correlational research involves correlating two continuous variables (groups are not formed and compared). Third,   observational research  is non-experimental because it focuses on making observations of behavior in a natural or laboratory setting without manipulating anything. Milgram’s original obedience study was non-experimental in this way. He was primarily interested in the extent to which participants obeyed the researcher when he told them to shock the confederate and he observed all participants performing the same task under the same conditions. The study by Loftus and Pickrell described at the beginning of this chapter is also a good example of observational research. The variable was whether participants “remembered” having experienced mildly traumatic childhood events (e.g., getting lost in a shopping mall) that they had not actually experienced but that the researchers asked them about repeatedly. In this particular study, nearly a third of the participants “remembered” at least one event. (As with Milgram’s original study, this study inspired several later experiments on the factors that affect false memories. The types of research we have discussed so far are all quantitative, referring to the fact that the data consist of numbers that are analyzed using statistical techniques. But as you will learn in this chapter, many observational research studies are more qualitative in nature. In  qualitative research , the data are usually nonnumerical and therefore cannot be analyzed using statistical techniques. Rosenhan’s observational study of the experience of people in a psychiatric ward was primarily qualitative. The data were the notes taken by the “pseudopatients”—the people pretending to have heard voices—along with their hospital records. Rosenhan’s analysis consists mainly of a written description of the experiences of the pseudopatients, supported by several concrete examples. To illustrate the hospital staff’s tendency to “depersonalize” their patients, he noted, “Upon being admitted, I and other pseudopatients took the initial physical examinations in a semi-public room, where staff members went about their own business as if we were not there” (Rosenhan, 1973, p. 256) [2] . Qualitative data has a separate set of analysis tools depending on the research question. For example, thematic analysis would focus on themes that emerge in the data or conversation analysis would focus on the way the words were said in an interview or focus group. Internal Validity Revisited Recall that internal validity is the extent to which the design of a study supports the conclusion that changes in the independent variable caused any observed differences in the dependent variable.  Figure 6.2  shows how experimental, quasi-experimental, and non-experimental (correlational) research vary in terms of internal validity. Experimental research tends to be highest in internal validity because the use of manipulation (of the independent variable) and control (of extraneous variables) help to rule out alternative explanations for the observed relationships. If the average score on the dependent variable in an experiment differs across conditions, it is quite likely that the independent variable is responsible for that difference. Non-experimental (correlational) research is lowest in internal validity because these designs fail to use manipulation or control. Quasi-experimental research (which will be described in more detail in a subsequent chapter) is in the middle because it contains some, but not all, of the features of a true experiment. For instance, it may fail to use random assignment to assign participants to groups or fail to use counterbalancing to control for potential order effects. Imagine, for example, that a researcher finds two similar schools, starts an anti-bullying program in one, and then finds fewer bullying incidents in that “treatment school” than in the “control school.” While a comparison is being made with a control condition, the lack of random assignment of children to schools could still mean that students in the treatment school differed from students in the control school in some other way that could explain the difference in bullying (e.g., there may be a selection effect). Figure 6.2 Internal Validity of Correlation, Quasi-Experimental, and Experimental Studies. Experiments are generally high in internal validity, quasi-experiments lower, and correlation studies lower still. Notice also in  Figure 6.2  that there is some overlap in the internal validity of experiments, quasi-experiments, and correlational studies. For example, a poorly designed experiment that includes many confounding variables can be lower in internal validity than a well-designed quasi-experiment with no obvious confounding variables. Internal validity is also only one of several validities that one might consider, as noted in Chapter 5. Key Takeaways Non-experimental research is research that lacks the manipulation of an independent variable. There are two broad types of non-experimental research. Correlational research that focuses on statistical relationships between variables that are measured but not manipulated, and observational research in which participants are observed and their behavior is recorded without the researcher interfering or manipulating any variables. In general, experimental research is high in internal validity, correlational research is low in internal validity, and quasi-experimental research is in between. A researcher conducts detailed interviews with unmarried teenage fathers to learn about how they feel and what they think about their role as fathers and summarizes their feelings in a written narrative. A researcher measures the impulsivity of a large sample of drivers and looks at the statistical relationship between this variable and the number of traffic tickets the drivers have received. A researcher randomly assigns patients with low back pain either to a treatment involving hypnosis or to a treatment involving exercise. She then measures their level of low back pain after 3 months. A college instructor gives weekly quizzes to students in one section of his course but no weekly quizzes to students in another section to see whether this has an effect on their test performance. Milgram, S. (1974). Obedience to authority: An experimental view . New York, NY: Harper & Row. ↵ Rosenhan, D. L. (1973). On being sane in insane places. Science, 179 , 250–258. ↵ Share This Book Increase Font Size Cellular Biology Cell Culture Electron Microscopy Transmission Electron Microscopy (TEM) Cytological Techniques Cell Culture Techniques A Comparison of Students’ Quantitative Reasoning Skills in STEM and Non-STEM Math Pathways This person is not on ResearchGate, or hasn't claimed this research yet. Florida Institute of Technology Discover the world's research 25+ million members 160+ million publication pages 2.3+ billion citations Adeneye O. A. Awofala Emily Elrod Tanvir Prince Kristin Lilly Alicia Grunow Corrine Taylor Edwin Villafane-Hernandez Jeremy A. Taylor Bernard L. Madison Lynn Arthur Steen EDUC LEADERSHIP Sch Sci Math M Z Agustin Recruit researchers Join for free Login Email Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google Welcome back! Please log in. Email · Hint Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google No account? Sign up 23+ Quantitative Research Topics For STEM Students In The Philippines Post author By Ankit February 6, 2024 “Did you know only 28% of college graduates in the Philippines get degrees in STEM fields? Finding good research topics is vital to getting more Filipino students curious about quantitative studies. With limited research money and resources, it can be hard for STEM students to find quantitative projects that are possible, new, and impactful. Often, researchers end up feeling apart from local issues and communities. This blog post offers a unique collection of quantitative research topics for STEM students in the Philippines. Thus, drawing from current events, social issues, and the country’s needs, these project ideas will feel relevant and help students do research that creates positive change.  Philippines students can find inspiration for quantitative studies that make a difference at home through many examples across science, technology, engineering, and math. Read Our Blog: 120+ Best Quantitative Research Topics for Nursing Students (2024 Edition) Table of Contents 30 Great Quantitative Research Topics for STEM Students in The Philippines Here are the top quantitative research topics for STEM students in the Philippines in 2024 1. Impact of Climate Change on Farming Analyze how changing weather affects the growth of crops like rice and corn in different parts of the Philippines. Use numbers to find ways and suggest ways farmers can adapt. 2. Using Drones to Watch Nature See how well drones with special sensors can watch over forests and coasts in the Philippines. Look at the data they gather to figure out how to save these places. 3. Making Solar Panels Work Better Experiment with various ways to make more power with solar panels in sunny, humid places like the Philippines. Utilize math to guess how well they’ll work. 4. Checking How Pollution Hurts Coral Reefs Count how much damage pollution does to coral reefs in the Philippines. Try to predict how bad it’ll get if we don’t stop polluting. 5. Watching Traffic to Fix Roads Look at how cars move in big cities like Manila. Use math to figure out how to make traffic flow better and help people get around faster. 6. at Air and Sick People Measure how clean the air is in various parts of the Philippines and see if it affects how many people get sick. Find out which areas need help to stay healthy. 7. Guessing When Earthquakes Might Happen Look at data from sensors all over the Philippines to see if we can tell when earthquakes might come. Try to guess where they’ll occur next. 8. Making Water Pipes Better Use math tricks to design cheap pipes that bring clean water to small towns in the Philippines. Think about things like hills and how many people need water. 9. Checking If Planting Trees Helps Measure if planting trees helps stop the shore from washing away during storms. Use photos from far away and math to see if it’s working. 10. Teaching Computers to Find Sickness Teach computers to look at pictures and records from hospitals to see if people are sick. Check if they’re good at spotting problems in the Philippines. 11. Finding Better Bags That Break Down Test different materials like banana leaves to see which ones can be made into bags that don’t hurt the environment. Compare them to regular plastic bags. 12. Making Gardens in the City See if we can grow vegetables in tall buildings in big cities like Manila. Use numbers to figure out if it’s a good idea. 13. Checking If Bugs Spread Easily in Crowded Places Use computers to see if diseases spread fast in busy places in the Philippines. Look at how people move around to stop diseases from spreading. 14. Storing Energy for Islands Without Power Think about ways to save power for small islands without electricity. Try out different ways to save energy and see which one works best. 15. Seeing How Much Storms Hurt Farms Calculate how much damage storms do to farms in the Philippines. Use numbers to see how much money farmers lose. 16. Testing Ways to Stop Dirt from Washing Away Try out different ways to stop dirt from being washed away when it rains. Use math to see which way works best on hills in the Philippines. 17. Checking How Healthy Local Food Is Look at the vitamins and minerals in local foods like sweet potatoes and moringa leaves. See if eating them is good for people in the Philippines. 18. Making Cheap Water Cleaners Build simple machines that clean dirty water in small towns. Notice if they work better than expensive ones. 19. Seeing How Hot Cities Get Use satellites to see how hot cities like Manila get compared to places with more trees. Think about how this affects people. 20. Thinking About Trash in Cities Look at how much trash cities in the Philippines make and find ways to deal with it. Consider what people can do to make less trash. 21. Checking If We Can Use Hot Rocks for Power Look at rocks under the ground to see if we can get power from them. Consider whether it is beneficial for the environment. 22. Counting Animals in the Forest Use cameras to count how many animals are in forests in the Philippines. Notice which places need the most help to keep animals safe. 23. Making Fishing Fair Look at how many fish are caught in the Philippines and see if it’s fair. Think about ways to make sure there will always be enough fish to catch. 24. Making Power Lines Smarter Design power lines that can change how much power they use. Try to make sure power goes where it’s needed most. 25. Looking at Dirty Water Find out if chopping down trees and building things by rivers makes the water dirty. Think about what this means for people and animals. 26. Thinking About Big Waves Use computers to see if big waves could hit the Philippines and what might happen. Think about how to keep people safe. 27. Seeing If Parks Help Cities Ask people if they like having parks in their city and see what animals live there. Think about if parks make cities better. 28. Making Houses That Don’t Break in Storms Make houses that don’t fall when there are big storms. Try to make them cheap so more people can have them. 29. Stopping Food from Going Bad Look at how food gets from farms to people’s houses and see if we can stop it from going bad. Think about how to make sure people have enough to eat. 30. Seeing How Hot Cities Get Put machines around cities to see how hot they get. Consider how this affects people and what we can do to help. These topics will help you to make a good project that assists you in getting better scores. Importance Of Quantitative Research For STEM Students Read why quantitative research matters to Filipino students. Helps us understand problems more clearly by revealing trends, patterns, and connections in the data Provides an accurate picture by removing personal biases and opinions Allows quantitative comparison of results if studies use the same methods Enables testing hypotheses and theories through experiments that can prove/disprove predictions Allows replication and verification as other researchers can redo experiments and study methods Numbers give a more precise, factual understanding compared to qualitative data. Removes subjectivity through quantitative data rather than opinions A key part of the scientific process is that data helps confirm or reject proposed explanations. Overall, collecting and analyzing quantitative data is crucial for gaining insights, testing ideas, ensuring consistency, and reducing bias It’s time to see what challenges students face with their quantitative research. Challenge Philippines Students Face With Their Quantitative Research  Here are the common challenges that students face with their quantitative research topics: Lack of resources and funding Doing quantitative research needs access to equipment, software , datasets etc, which can be costly. Many students lack funding and access to these resources. Lack of background in mathematics and statistics Quantitative research relies heavily on math and statistical skills. However, many students haven’t developed strong enough skills in these areas yet. Difficulty accessing scholarly databases Students need access to academic journals and databases for literature reviews. However, these can be costly for people to access. Language barriers Many of the academic literature is in English. This can make reading and learning complex statistical concepts more difficult. Lack of mentorship Having an experienced mentor to provide guidance is invaluable. However, not all students have access to mentorship in quantitative research. Managing large datasets Collecting, cleaning and analyzing large datasets requires advanced technical skills. Students may struggle without proper guidance. Presenting results clearly Learning how to visualize and communicate statistical findings effectively is an important skill that takes practice. Ethical challenges Ensuring quantitative studies are designed ethically can be difficult for novice researchers. Writing scientifically Adopting the formal, precise writing style required in quantitative research is challenging initially. Maintaining motivation Quantitative research is complex and time-consuming. Students may lose motivation without a strong support network. While quantitative research presents many challenges, Philippines STEM students can overcome these through access to proper resources and support. With hard work, mentorship and collaborative opportunities, students can build essential skills and contribute to the quantitative research landscape. Tips For Conducting Quantitative Research In The Philippines When conducting research in a new cultural context like the Philippines, it is vital to take time to understand local norms and build trust. Approaching research openly and collaboratively will lead to more meaningful insights. 1. Get Required Approvals Be sure to get any necessary ethics reviews or approvals from local governing boards before conducting the analysis. It is wise to follow proper protocols and permissions. 2. Hire Local Assistants Hire local research helpers to help navigate logistics, translation, and cultural sensitivities. This provides jobs and insider insights. 3. Use Multiple Research Methods Triangulate findings using interviews, focus groups, surveys, participant observation, etc. Multiple methods provide more potent and well-rounded results. 4. Verify Information Politely verify information collected from interviews before publication. Follow up to ensure accurate representation and context. 5. Share Results Report back to participants and communities on research findings and next steps. This shows respect and accountability for their contributions. 6. Acknowledge Limitations Openly acknowledge the limitations of perspective and methods as an outside researcher. Remain humble and keep improving approaches. Keep in mind, when entering a new community to conduct research, taking an open, patient, and collaborative approach leads to more ethical and meaningful results. Thus, making the effort to understand and work within cultural norms demonstrates respect. STEM students in the Philippines have many possible research topics using numbers. They could look at renewable energy, sustainability, pollution, environment, disease prevention, farming improvements, preparing for natural disasters, building projects, transportation, and technology access.  By carefully analyzing statistics and creating mathematical models, young Filipino researchers can provide key ideas to guide future policies and programs. Quantitative research allows real observations and suggestions based on evidence to make the country better now and later.  Number-based methods help young researchers in the Philippines give tangible recommendations to improve their communities. How can I limit my choices and pick the right research topic? Think about what you enjoy and what you’re skilled at. Consider if your topic is meaningful and if you have the resources to study it. Get advice from teachers or friends to help you decide. What are some common problems in doing math research in science, technology, engineering, and math? Problems might include: 1. Finding data. 2. Make sure your measurements are correct. 3. Following rules about ethics. 4. Handling big sets of data. How can I make sure my research is done well? Plan your study carefully, use the correct methods and tools, write down everything you do, and think about the strengths and weaknesses of your work. Tags Quantitative Research Topics For STEM Students In The Philippines australia (2) duolingo (13) Education (284) General (77) How To (18) IELTS (127) Latest Updates (162) Malta Visa (6) Permanent residency (1) Programming (31) Scholarship (1) Sponsored (4) Study Abroad (187) Technology (12) work permit (8) Recent Posts 489 IMAGES 189+ Good Quantitative Research Topics For STEM Students 151+ Great Quantitative Research Topics For STEM Students Best 151+ Quantitative Research Topics for STEM Students 199+ Engaging Quantitative Research Topics for STEM Students 101 Best Quantitative Research Topics for STEM Students 190+ Best Quantitative Research Topics for STEM Students VIDEO non experimental research design with examples and characteristics New Classification of Non-experimental Quantitative Research by Joseph Reyes Research Design AP Psychology: Science Practices- Non-Experimental Methods Quantitative Research || Experimental Research || Non Experimental Research Best Research Topics For Senior High School Students COMMENTS Best 151+ Quantitative Research Topics for STEM Students Here are some quantitative research topics in physics for stem students: 1. Investigating the behavior of subatomic particles in high-energy collisions. 2. Analyzing the properties of dark matter and dark energy. 3. Studying the quantum properties of entangled particles. 4. 189+ Good Quantitative Research Topics For STEM Students Following are the best Quantitative Research Topics For STEM Students in mathematics and statistics. Prime Number Distribution: Investigate the distribution of prime numbers. Graph Theory Algorithms: Develop algorithms for solving graph theory problems. Statistical Analysis of Financial Markets: Analyze financial data and market trends. 240+ Experimental Quantitative Research Topics For Stem Students Here are 10 qualitative research topics for STEM students: Exploring the experiences of female STEM students in overcoming gender bias in academia. Understanding the perceptions of teachers regarding the integration of technology in STEM education. Investigating the motivations and challenges of STEM educators in underprivileged schools. 55 Brilliant Research Topics For STEM Students There are several science research topics for STEM students. Below are some possible quantitative research topics for STEM students. A study of protease inhibitor and how it operates. A study of how men's exercise impacts DNA traits passed to children. A study of the future of commercial space flight. 110+ Best Quantitative Research Topics for STEM Students Quantitative Research Topics for STEM Students. Check out quantitative research topics for STEM students:-Physics. Friction: Compare friction on different surfaces.; Light Diffraction: Measure light patterns through slits.; Heat Engines: Test efficiency with different fluids.; Magnetism: Study magnetic field strength in wires.; Quantum: Analyze electron patterns in a slit experiment. 60+ Best Quantitative Research Topics for STEM Students: Dive into Data Embark on a captivating journey through the cosmos of knowledge with our curated guide on Quantitative Research Topics for STEM Students. Explore innovative ideas in science, technology, engineering, and mathematics, designed to ignite curiosity and shape the future. Unleash the power of quantitative research and dive into uncharted territories ... Best 101 Quantitative Research Topics for STEM Students Mathematics Research Topics. Prime Number Distribution Patterns: Study the distribution of prime numbers and look for patterns. Graph Theory and Network Analysis: Analyze real-world networks using graph theory techniques. Optimization of Algorithms: Optimize algorithms for faster computation and efficiency. 55 Brilliant Research Topics For STEM Students (2024) There are several science research topics for STEM students. Below are some possible quantitative research topics for STEM students. A study of protease inhibitor and how it operates. A study of how men's exercise impacts DNA traits passed to children. A study of the future of commercial space flight. 11 STEM Research Topics for High School Students Topic 1: Artificial Intelligence (AI) AI stands at the forefront of technological innovation. Students can engage in research on AI applications in various sectors and the ethical implications of AI. This field is suitable for students with interests in computer science, AI, data analytics, and related areas. Topic 2: Applied Math and AI. Quantitative Research with Nonexperimental Designs Leung and Shek (2018) explain: Experimental research design utilizes the principle of manipulation of the independent variables and examines its cause-and-effect relationship on the dependent variables by controlling the effects of other variables. Usually, the experimenter assigns two or more groups with similar characteristics. 199+ Quantitative Research Topics For STEM Students to Try Now 30 Quantitative Research Topic Ideas For STEM Students. Investigating the properties and applications of novel materials created through 3D printing. Studying the effectiveness of virtual reality simulations for medical training programs. Analyzing the feasibility and methods for mineral extraction from asteroids. 200 Quantitative Research Title for Stem Students Quantitative research involves gathering numerical data to answer specific questions, and it's a fundamental part of STEM fields. To help you get started on your research journey, we've compiled a list of 200 quantitative research title for stem students. These titles span various STEM disciplines, from biology to computer science. Trending Topic Research: STEM Trending Topic Research File. Science, Technology Engineering, and Mathematics (STEM) is one of the most talked about topics in education, emphasizing research, problem solving, critical thinking, and creativity. The following compendium of open-access articles are inclusive of all substantive AERA journal content regarding STEM published since ... 500+ Quantitative Research Titles and Topics Quantitative research involves collecting and analyzing numerical data to identify patterns, trends, and relationships among variables. This method is widely used in social sciences, psychology, economics, and other fields where researchers aim to understand human behavior and phenomena through statistical analysis. If you are looking for a quantitative research topic, there are numerous areas ... Trends and Hot Topics of STEM and STEM Education: a Co-word Analysis of This study explored research trends in science, technology, engineering, and mathematics (STEM) education. Descriptive analysis and co-word analysis were used to examine articles published in Social Science Citation Index journals from 2011 to 2020. From a search of the Web of Science database, a total of 761 articles were selected as target samples for analysis. A growing number of STEM ... Research and trends in STEM education: a systematic review of journal With the rapid increase in the number of scholarly publications on STEM education in recent years, reviews of the status and trends in STEM education research internationally support the development of the field. For this review, we conducted a systematic analysis of 798 articles in STEM education published between 2000 and the end of 2018 in 36 journals to get an overview about developments ... (PDF) Nonexperimental Quantitative Research and Its Role in Guiding The quantitative, non-experimental correlational design was easy to use for the calculation of the correlation coefficients that indicated both extent and direction of impact of the variables ... 6.1 Overview of Non-Experimental Research Non-experimental research is research that lacks the manipulation of an independent variable. Rather than manipulating an independent variable, researchers conducting non-experimental research simply measure variables as they naturally occur (in the lab or real world). Most researchers in psychology consider the distinction between experimental ... A Comparison of Students' Quantitative Reasoning Skills in STEM and Non Students in the STEM math pathway whe n completing this assessment on. average scored 5.58% higher than those in the Non-STEM pathways ( =4.74, p <0.05). (See Table 2.) Students who identified as ... 23+ Quantitative Research Topics For STEM Students In ... Here are the top quantitative research topics for STEM students in the Philippines in 2024. 1. Impact of Climate Change on Farming. Analyze how changing weather affects the growth of crops like rice and corn in different parts of the Philippines. Use numbers to find ways and suggest ways farmers can adapt. 2. A Comparison of Students Quantitative Reasoning Skills in STEM and Non Non-STEM math pathways using a non-proprietary, NSF grant-funded instrument, the Quantitative Literacy & Reasoning Assessment (QLRA). Participants were students enrolled in at least one college-level math pathway course at a large public institution in the southeastern US. The results showed a significant difference between STEM and Non-STEM ... Enhancing Students' Critical Thinking Through Mathematics in Higher Interviews, observation questionnaires and questionnaires were used to collect qualitative data and tests for quantitative results. Regarding research design, eight of the 15 studies examined (53%) used a quasi-experimental methodology. One study (7%) used an experimental methodology, while two (13%) used a longitudinal methodology. Any good experimental quantitative research topic for STEM students Since you are a STEM student (like me but Im already College), most experimental quanti researches I've read so far are alternatives of this and that (eg. Alternative for Cell Staining)... so take time to go to library and read existing research. Need help please, I made 5 proposals for the past weeks but all got rejected dahil either not STEM ... essay homework paper phd project resume review speech study thesis