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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.

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!

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.

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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10 Catchy Research Title For Stem Students

1. " nano power : harnessing energy at the molecular scale" - nanotech's energy revolution., 2. " mars colonization: engineering challenges and solutions" - stem for interplanetary life., 3. " quantum computing: unlocking unprecedented computational power" - quantum leaps in stem., 4. " crispr -cas9: gene editing for health and beyond" - precision in dna manipulation., 5. " green chemistry : sustainable solutions for a greener tomorrow" - stem for eco-friendliness., 6. "artificial intelligence in medicine : transforming healthcare" - stem meets healthcare., 7. " renewable energy integration : powering the future sustainably" - stem for energy transition., 8. " space debris management: safeguarding our orbital environment" - stem in space cleanup., 9. " neural interfaces : connecting brain and machine" - stem for mind-machine interaction., 10. "3d printing in biomedical applications : building better bodies" - stem shaping medical futures., discover more stories.

STEM Research Topics for an Educational Paper

STEM stands for Science, Technology, Engineering, and Math. It is essential for learning and discovery, helping us understand the world, solve problems, and think critically. STEM research goes beyond classroom learning, allowing us to explore specific areas in greater detail. But what is a good topic for research STEM?

Here are a few examples to get you thinking:

Can computers be used to help doctors diagnose diseases?
How can we build houses that are strong and don't hurt the environment?
What are the mysteries of space that scientists haven't figured out yet?

Why is STEM important? STEM is everywhere—from the phones we use to the medicine that keeps us healthy. Learning about these fields helps us build a better future by developing new technologies, protecting our environment, and solving critical problems.

Now that you understand the basics, let's dive into some of the most interesting and important research topics you can choose from.

The List of 260 STEM Research Topics

The right topic will keep you engaged and motivated throughout the writing process. However, with so many areas to explore and problems to solve, finding a unique topic can seem a bit tough. To help you with this, we have compiled a list of 260 STEM research topics. This list aims to guide your decision-making and help you discover a subject that holds significant potential for impact. And if you need further help writing about your chosen topic, feel free to hire someone to write a paper on our professional platform!

Feeling Overwhelmed by Your STEM Research Paper?

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Physics Research Topics

Physics, the study of matter, energy, and their interactions, is the foundation for understanding our universe. Here are 20 topics to ignite your curiosity:

Can we develop more efficient solar panels to capture and utilize solar energy for a sustainable future?
How can we further explore the fundamental building blocks of matter, like quarks and leptons, to understand the nature of our universe?
How can we detect and understand dark matter and dark energy, which make up most of the universe's mass and energy but remain a mystery?
What happens to matter and energy when they enter a black hole?
How can we reconcile the theories of quantum mechanics and general relativity to understand gravity at the atomic level?
How can materials with zero electrical resistance be developed and used for more efficient power transmission and next-generation technologies?
What were the conditions of the universe moments after the Big Bang?
How can we manipulate and utilize sound for applications in areas like medical imaging and communication?
How does light behave as both a wave and a particle?
Can we harness the power of nuclear fusion, the process that powers stars, to create a clean and sustainable energy source for the future?
How can physics principles be used to understand and predict the effects of climate change and develop solutions to mitigate its impact?
Can we explore new physics concepts to design more efficient and sustainable aircraft?
What is the fundamental nature of magnetism?
How can we develop new materials with specific properties like superconductivity, high strength, or self-healing capabilities?
How do simple toys like pendulums or gyroscopes demonstrate fundamental physics concepts like motion and energy transfer?
How do physics principles like aerodynamics, momentum, and force transfer influence the performance of athletes and sports equipment?
What is the physics behind sound waves that allow us to hear and appreciate music?
How do technologies like X-rays, MRIs, and CT scans utilize physics principles to create images of the human body for medical diagnosis?
How do waves, currents, and tides behave in the ocean?
How do basic physics concepts like friction, gravity, and pressure play a role in everyday activities like walking, riding a bike, or playing sports?

Use our physics helper to write a paper on any of these topics of your choice!

Chemistry Research Topics

If you're curious about the world around you at the molecular level, here are 20 intriguing topic questions for you:

Can we create chemical reactions that are kinder to the environment?
How can we design new drugs to fight diseases more effectively?
Is it possible to develop materials with properties never seen before?
Can we store energy using chemical reactions for a sustainable future?
What's the chemistry behind creating delicious and nutritious food?
Can chemistry help us analyze evidence and solve crimes more efficiently?
Are there cleaner ways to power our vehicles using chemistry?
How can we reduce plastic pollution with innovative chemical solutions?
What chemicals influence our brain function and behavior?
What exciting new applications can we discover for versatile polymers?
What's the science behind the fascinating world of scents?
How can we develop effective methods for purifying water for safe consumption?
Can we explore the potential of nanochemistry to create revolutionary technologies?
What chemicals are present in the air we breathe, and how do they affect our health?
Why do objects have different colors? Can we explain it through the lens of chemistry?
Do natural catalysts like enzymes hold the key to more efficient chemical processes?
Can we use chemistry to analyze historical objects and uncover their stories?
What's the science behind the beauty products we use every day?
Are artificial sweeteners and flavors safe for consumption?
What chemicals are present in space, and how do they contribute to our universe's composition?

Engineering Research Topics

The world of engineering is all about applying scientific knowledge to solve practical problems. Here are some thought-provoking questions to guide you:

Can we design robots that can assist us in complex surgeries?
How can we create self-driving cars that are safe and reliable?
Is it possible to build sustainable cities that minimize environmental impact?
What innovative materials can we develop for stronger and more resilient buildings?
How can we harness renewable energy sources like wind and solar more efficiently?
Can we design more sustainable and eco-friendly water treatment systems?
What technologies can improve communication and connectivity, especially in remote areas?
How can we create next-generation prosthetics that provide a natural feel and function?
Is it possible to engineer solutions for food security and sustainable agriculture?
What innovative bridges and transportation systems can we design for smarter cities?
How can we engineer safer and more efficient methods for space exploration?
Can we develop robots that can perform hazardous tasks in dangerous environments?
Is it possible to create new manufacturing processes that minimize waste and pollution?
How can we engineer smarter and more efficient power grids to meet our energy demands?
What innovative solutions can we develop to mitigate the effects of climate change?
Can we design more accessible technologies that improve the lives of people with disabilities?
How can we engineer better disaster preparedness and response systems?
Is it possible to create sustainable and efficient methods for waste management?
What innovative clothing and protective gear can we engineer for extreme environments?
Can we develop new technologies for faster and more accurate medical diagnostics?

Mathematics Research Topics

Mathematics, the language of patterns and relationships, offers endless possibilities for exploration. While you ask us to do my math homework for me online , you can choose the topic for your math paper below.

Can we develop new methods to solve complex mathematical problems more efficiently?
Is there a hidden mathematical structure behind seemingly random events?
How can we apply mathematical models to understand and predict real-world phenomena?
Are there undiscovered prime numbers waiting to be found, stretching the boundaries of number theory?
Can we develop new methods for data encryption and security based on advanced mathematical concepts?
How can we utilize game theory to understand competition, cooperation, and decision-making?
Can we explore the fascinating world of fractals and their applications in various fields?
Is it possible to solve long standing mathematical problems like the Goldbach conjecture?
How can we apply topology to understand the properties of shapes and spaces?
Can we develop new mathematical models for financial markets and risk analysis?
What role does cryptography play in the future of secure communication?
How can abstract algebra help us solve problems in other areas of mathematics and science?
Is it possible to explore the connections between mathematics and computer science for groundbreaking discoveries?
Can we utilize calculus to optimize processes and solve problems in engineering and physics?
How can mathematical modeling help us understand and predict weather patterns?
Is it possible to develop new methods for solving differential equations?
Can we explore the applications of set theory in various branches of mathematics?
How can mathematical logic help us analyze arguments and ensure their validity?
Is it possible to apply graph theory to model complex networks like social media or transportation systems?
Can we explore the fascinating world of infinity and its implications for our understanding of numbers and sets?

STEM Topics for Research in Biology

Biology is the amazing study of living things, from the tiniest creatures to giant ecosystems. If you're curious about the world around you, here are 20 interesting research topics to explore:

Can we change plants to catch more sunlight and grow better, helping us get food in a more eco-friendly way?
How do animals like whales or bees use sounds or dances to chat with each other?
Can tiny living things in our gut be used to improve digestion, fight sickness, or even affect our mood?
How can special cells called stem cells be used to repair damaged organs or tissues, leading to brand-new medical treatments?
What happens inside our cells that makes us age, and can we possibly slow it down?
How do internal clocks in living things influence sleep, how their body works, and overall health?
How does pollution from things like tiny plastic pieces harm sea creatures and maybe even us humans?
Can we understand how our brains learn and remember things to create better ways of teaching?
Explore the relationships between different species, like clownfish and anemones, where both creatures benefit.
Can we use living things like bacteria to make new, eco-friendly materials like bioplastics for different uses?
How similar or different are identical twins raised in separate environments, helping us understand how genes and surroundings work together?
Can changing crops using science be a solution to hunger and not having enough healthy food in some countries?
How do viruses change and spread, and how can we develop better ways to fight new viruses that appear?
Explore how amazing creatures like fireflies make their own light and see if there are ways to use this knowledge for other things.
What is the purpose of play in animals' lives, like helping them grow, socialize, or even learn?
How can tools like drones, special cameras from a distance, or other new technology be used to help protect wildlife?
How can we crack the code of DNA to understand how genes work and their role in different diseases?
As a new science tool called CRISPR lets us change genes very precisely, what are the ethical concerns and possible risks involved?
Can spending time in nature, like forests, improve how we feel mentally and physically?
What signs could we look for to find planets with potential life on them besides Earth?

STEM Topics for Research in Robotics

Robotics is a great area for exploration. Here is the topics list that merely scratches the surface of the exciting possibilities in robotics research.

How can robots be programmed to make their own decisions, like self-driving cars navigating traffic?
How can robots be equipped with sensors to "see" and understand their surroundings?
How can robots be programmed to move with precision and coordination, mimicking human actions or performing delicate tasks?
Can robots be designed to learn and improve their skills over time, adapting to new situations?
How can multiple robots work together seamlessly to achieve complex tasks?
How can robots be designed to assist people with disabilities?
How can robots be built to explore the depths of oceans and aid in underwater endeavors?
How can robots be designed to fly for tasks like search and rescue or environmental monitoring?
Can robots be built on an incredibly tiny scale for medical applications or super-precise manufacturing?
How can robots be used to assist surgeons in operating rooms?
How can robots be designed to explore space and assist astronauts?
How can robots be used in everyday life, helping with chores or providing companionship?
How can robots be designed by mimicking the movement and abilities of animals?
What are the ethical considerations in the development and use of robots?
How can robots be designed to interact with humans in a safe and user-friendly way?
How can robots be used in agriculture to automate tasks?
How can robots be used in educational settings to enhance learning?
How will the rise of robots impact the workforce?
How can robots be made more affordable and accessible?
What exciting advancements can we expect in the future of robotics?

Experimental Research Topics for STEM Students

Here are some great topics that can serve as your starting point.

Test how different light intensities affect plant growth rate.
Compare the effectiveness of compost and fertilizer on plant growth.
Experiment with different materials for water filtration and compare their efficiency.
Does playing specific types of music affect plant growth rate?
Test the strength of different bridge designs using readily available materials.
Find the optimal angle for solar panels to maximize energy production.
Compare the insulating properties of different building materials.
Test the effectiveness of different materials (straw, feathers) in absorbing oil spills.
Explore the impact of social media algorithms on user behavior.
Evaluate the effectiveness of different cybersecurity awareness training methods.
Develop and test a mobile app for learning a new language through interactive exercises.
Experiment with different blade shapes to optimize wind turbine energy generation.
Test different techniques to improve website loading speed.
Build a simple air quality monitoring system using low-cost sensors.
Investigate how different light wavelengths affect the growth rate of algae.
Compare the effectiveness of different food preservation methods (drying, salting) on food spoilage.
Test the antibacterial properties of common spices.
Investigate the impact of sleep duration on learning and memory retention.
Research the development of biodegradable packaging materials from natural resources like cellulose or mushroom mycelium.
Compare the effectiveness of different handwashing techniques in reducing bacteria.

Qualitative Research Topics for STEM Students

Qualitative research delves into the experiences, perceptions, and opinions surrounding STEM fields.

How do stellar STEM teachers inspire students to become scientists, engineers, or math whizzes?
As artificial intelligence advances, what are people's biggest concerns and hopes?
What are the hurdles women in engineering face, and how can we make the field more welcoming?
Why do some students freeze up during math tests, and how can we build their confidence?
How do different cultures approach protecting the environment?
What makes scientists passionate about their work, and what keeps them motivated?
When creating new technology, what are the ethical dilemmas developers face?
What are the best ways to explain complex scientific concepts to everyday people?
What fuels people's fascination with exploring space and sending rockets beyond Earth?
How are STEM jobs changing, and what skills will be crucial for the future workforce?
Would people be comfortable with robots becoming our companions, not just machines?
How can we create products that everyone can use, regardless of their abilities?
What makes some people hesitant about vaccines while others readily get them?
What motivates people to volunteer their time and contribute to scientific research?
Does learning to code early on give kids an edge in problem-solving?
Can games and activities make learning math less intimidating and more enjoyable?
What are people's thoughts on the ethical implications of using new technology to change genes?
What motivates people to adopt sustainable practices and protect the environment?
What are people's hopes and anxieties about using technology in medicine and healthcare?
Why do students choose to pursue careers in science, technology, engineering, or math?

Consider using our research paper writer online to create a perfectly-researched and polished paper.

Quantitative Research Topics for STEM Students

Quantitative research uses data and statistics to uncover patterns and relationships in STEM fields.

Does the type of music played affect plant growth rate?
Investigate the relationship between light intensity and the rate of photosynthesis in plants.
Test the impact of bridge design on its weight-bearing capacity.
Analyze how the angle of solar panels affects their energy production.
Quantify the impact of different website optimization techniques on loading speed.
Explore the correlation between social media use and user engagement metrics (likes, shares).
Test the effectiveness of various spices in inhibiting bacterial growth.
Investigate the relationship between sleep duration and memory retention in students.
Compare the effectiveness of different handwashing techniques in reducing bacterial count.
Quantify the impact of play-based learning on children's problem-solving skills.
Measure the efficiency of different materials in filtering microplastics from water samples.
Compare the impact of compost and traditional fertilizer on plant growth yield.
Quantify the insulating properties of various building materials for energy efficiency.
Evaluate the effectiveness of a newly designed learning app through user performance data.
Develop and test a low-cost sensor system to measure air quality parameters.
Quantify the impact of different light wavelengths on the growth rate of algae cultures.
Compare the effectiveness of different food preservation methods (drying, salting) on food spoilage rates.
Analyze the impact of a website redesign on user engagement and retention metrics.
Quantify the effectiveness of different cybersecurity awareness training methods through simulated hacking attempts.
Investigate the relationship between website color schemes and user conversion rates (purchases, sign-ups).

Environmental Sciences Research Topics for STEM students

These environmental science topics explore the connections between our planet's ecosystems and the influence of humans.

Can we track microplastic movement (water, soil, organisms) to understand environmental accumulation?
How can we seamlessly integrate renewable energy (solar, wind) into existing power grids?
Green roofs, urban forests, permeable pavements: their impact on cityscapes and environmental health.
Sustainable forest management: balancing timber production with biodiversity conservation.
Rising CO2: impact on ocean acidity and consequences for marine ecosystems.
Nature's clean-up crew: plants/microbes for decontaminating polluted soil and water.
Evaluating conservation strategies (protected areas, patrols) for endangered species.
Citizen science: potential and limitations for environmental monitoring and data collection.
Circular economy: reducing waste, promoting product reuse/recycling in an eco-friendly framework.
Water conservation strategies: rainwater harvesting, wastewater treatment for a sustainable future.
Agricultural practices (organic vs. conventional): impact on soil health and water quality.
Lab-grown meat: environmental and ethical implications of this alternative protein source.
A potential solution for improving soil fertility and carbon sequestration.
Mangrove restoration: effectiveness in mitigating coastal erosion and providing marine habitat.
Air pollution control technologies: investigating efficiency in reducing emissions.
Climate change and extreme weather events: the link between a warming planet and weather patterns.
Responsible disposal and recycling solutions for electronic waste.
Environmental education: effectiveness in fostering pro-environmental attitudes and behaviors.
Sustainable fashion: exploring alternatives like organic materials and clothing recycling.
Smart cities: using technology to improve environmental sustainability and resource management.

Check out more science research topics in our special guide!

Health Sciences Research Topic Ideas for STEM Students

If you're curious about how the body works and how to stay healthy, these research topics are for you:

Can changing your diet affect your happiness by influencing gut bacteria?
Can your genes help doctors create a treatment plan just for you?
Can viruses that attack bacteria be a new way to fight infections?
Does getting enough sleep help students remember things better?
Can listening to music help people feel less pain during medical procedures?
Can wearable devices warn people about health problems early?
Can doctors use technology to treat people who live far away?
Can meditation techniques help people feel calmer?
Can staying active keep your brain healthy as you age?
Can computers help doctors make better diagnoses?
Can looking at social media make people feel bad about their bodies?
Why are some people hesitant to get vaccinated, and how can we encourage them?
Can scientists create materials for implants that the body won't reject?
Can we edit genes to cure diseases caused by faulty genes?
Does dirty air make it harder to breathe?
Can therapy offered online be just as helpful as in-person therapy?
Can what you eat affect your chances of getting cancer?
Can we use 3D printing to create organs for transplant surgeries?
Do artificial sweeteners harm the good bacteria in your gut?
Can laughter actually be good for your body and mind?

Interdisciplinary STEM Research Topics

Here are 20 thought-provoking questions that explore the exciting intersections between different areas of science, technology, engineering, and math:

Can video games become educational tools, boosting memory and learning for all ages?
Can artificial intelligence compose music that evokes specific emotions in listeners?
Could robots be designed to assist surgeons in complex operations with greater precision?
Does virtual reality therapy hold promise for treating phobias and anxiety?
Can big data analysis predict and prevent natural disasters, saving lives?
Is there a link between dirty air and the rise of chronic diseases in cities?
Can we develop strong, eco-friendly building materials for a sustainable future?
Could wearable tech monitor athletes' performance and prevent injuries?
Will AI advancements lead to the creation of conscious machines, blurring the line between humans and technology?
Can social media platforms be designed to promote positive interactions and reduce online bullying?
Can personalized learning algorithms improve educational outcomes for all students?
Could neuroimaging technologies unlock the secrets of human consciousness?
Will advancements in gene editing allow us to eradicate inherited diseases?
Is there a connection between gut bacteria and mental health issues like depression?
Can drones be used for efficient and safe delivery of medical supplies in remote areas?
Is there potential for using artificial intelligence to design life-saving new drugs?
Could advances in 3D printing revolutionize organ transplantation procedures?
Will vertical farming techniques offer a sustainable solution to food security concerns?
Can we harness the power of nanotechnology to create self-cleaning and self-repairing materials?
Will advancements in space exploration technology lead to the discovery of life on other planets?

STEM Topics for Research in Technology

These research topics explore how technology can solve problems, make life easier, and unlock new possibilities:

How can self-driving cars navigate busy roads safely, reducing accidents?
In what ways can robots explore the deep ocean and unlock its mysteries?
How might technology automate tasks in our homes, making them more efficient and comfortable?
What advancements are possible for directly controlling computers with our thoughts using brain-computer interfaces?
How can we develop stronger cybersecurity solutions to protect our online information and devices from hackers?
What are the methods for harnessing natural resources like wind and sun for clean energy through renewable energy sources?
How can wearable translators instantly translate languages, breaking down communication barriers?
In what ways can virtual reality allow us to explore amazing places without leaving home?
How can games and apps make learning more engaging and effective through educational tools?
What technologies can help us reduce the amount of food that gets thrown away?
How can online platforms tailor education to each student's needs with personalized learning systems?
What new technologies can help us travel farther and learn more about space?
How can desalination techniques turn saltwater into clean drinking water for everyone?
What are the ways drones can deliver aid and supplies quickly and efficiently in emergencies?
How can robots allow doctors to remotely examine and treat patients in distant locations?
What possibilities exist for 3D printers to create customized medical devices and prosthetics?
How can technology overlay information onto the real world, enhancing our learning and experiences with augmented reality tools?
What methods can we use for secure access to devices and information with biometric security systems?
How can AI help us develop strategies to combat climate change?
In what ways can we ensure technology benefits everyone and is used ethically?

While you're researching these STEM topics, learn more about how to get better at math in our dedicated article.

How Do You Choose a Research Topic in STEM?

Choosing research topics for STEM students can be an exciting task. Here are several tips to help you find a topic that is both unique and meaningful:

Identify Your Interests: Start by considering what areas of STEM excite you the most. Do you have a passion for renewable energy, artificial intelligence, biomedical engineering, or environmental science? Your interest in the subject will keep you motivated throughout the research process.
Review Current Research: Conduct a thorough review of existing research in your field. Read recent journal articles, attend seminars, and follow relevant news. This will help you understand what has already been studied and where there might be gaps or opportunities for new research.
Consult with Experts: Talking to professors, advisors, or professionals in your field can provide valuable insights. They can help you identify important research questions, suggest resources, and guide you toward a feasible and impactful topic.
Consider Real-World Problems: Think about the practical applications of your research. Focus on real-world problems that need solutions. This not only makes your research more relevant but also increases its potential impact.
Narrow Down Your Focus: A broad topic can be overwhelming and difficult to manage. Narrow down your focus to a specific question or problem. This will make your research more manageable and allow you to delve deeper into the subject.
Assess Feasibility: Consider the resources and time available to you. Ensure that you have access to the necessary equipment, data, and expertise to complete your research. A feasible topic will help you stay on track and complete your project successfully.
Stay Flexible: Be open to adjusting your topic as you delve deeper into your research. Sometimes, initial ideas may need refinement based on new findings or practical constraints.

These research topics have shown us a glimpse of the exciting things happening in science, technology, engineering, and math (STEM). From understanding our planet to figuring out how the human body works, STEM fields are full of new things to learn and problems to solve.

Don't be afraid to challenge ideas and work with others to find answers. The future of STEM belongs to people who think carefully, try new things, and want to make the world a better place. Remember the famous scientist Albert Einstein, who said, "It is important never to stop asking questions. Curiosity has its own reason for existing."

Drowning in Data Analysis or Struggling to Craft a Strong Argument?

Don't let a challenging STEM research paper derail your academics!

What is STEM in Research?

What are the keys to success in stem fields, what should women in stem look for in a college.

is an expert in nursing and healthcare, with a strong background in history, law, and literature. Holding advanced degrees in nursing and public health, his analytical approach and comprehensive knowledge help students navigate complex topics. On EssayPro blog, Adam provides insightful articles on everything from historical analysis to the intricacies of healthcare policies. In his downtime, he enjoys historical documentaries and volunteering at local clinics.

Trending Topic Research: STEM . (n.d.). Www.aera.net. Retrieved July 15, 2024, from https://www.aera.net/Newsroom/Trending-Topic-Research-Files/Trending-Topic-Research-STEM

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Publishes integrative reviews and syntheses of literature relevant to STEM education and research.
Promotes research on frontier topics, such as those in the intersection of technology and STEM education.
Advances theoretical perspectives and research methodologies in STEM education.
Encourages contributions from scholars across diverse subject content and social science fields.

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Published: 10 July 2020

Evidence of STEM enactment effectiveness in Asian student learning outcomes

Bevo Wahono 1 , 2 ,
Pei-Ling Lin 3 &
Chun-Yen Chang ORCID: orcid.org/0000-0003-2373-2004 3

International Journal of STEM Education volume 7 , Article number: 36 ( 2020 ) Cite this article

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This study used a systematic review and meta-analysis as a method to investigate whether STEM enactment in Asia effectively enhances students’ learning outcomes. Verifiable examples of science, technology, engineering, and mathematics (STEM) education, effectively being applied in Asia, are presented in this study. The study involved 4768 students from 54 studies. Learning outcomes focused on the students’ academic learning achievement, higher-order thinking skills (HOTS), and motivation. The analysis results of effect sizes showed that the STEM enactments in Asia were effective at a moderate level (0.69 [0.58, 0.81 of 95% CI]) of improving students’ learning outcomes. Sequentially, the effectiveness of STEM enactment starts from students’ higher-order thinking skills, moves to students’ academic learning achievement, and ends with the motivation. In addition, STEM enactments in Asia were carried out with several variations where STEM integrated with project-based learning was preferred. The recommendations of this study include a combination of the learning approach, learning orientation, and duration of instruction, all of which contribute to the STEM enactment effectiveness and maximize results in STEM education. Some practical implications, such as the central role of the teacher during the STEM enactment, are extensively discussed. This study supports that STEM education is a universally crucial tool which effectively prepares students from various national and cultural backgrounds, across Asia, toward improved learning outcomes.

Introduction

The role of science, technology, engineering, and mathematics (STEM) education in terms of students’ learning outcome is a central topic for the educational field. However, STEM education is a very broad term (Baran, Bilici, Mesutoglu, & Ocak, 2016 ; Bybee, 2013 ; Hsu, Lin, & Yang, 2017 ). Therefore, in this current study, STEM education (enactment) refers to teaching, learning, and integrating the disciplines and skills of science, technology, mathematics, and engineering in STEM topics, with an emphasis on solving real-world problems. Indeed, STEM education focuses on hands-on activity (Cameron & Craig, 2016 ; Yildirim & Turk, 2018 ) to prepare students in facing the developments of a new competitive era. In STEM learning activities, soft skills such as problem-solving, higher-order thinking skills, and collaborative work are the main focuses on which students’ learning is geared toward (Li, Huang, Jiang, & Chang, 2016 ; Meyrick, 2011 ).

STEM activities in the classroom endeavor to improve the quality of the learning process (Meyrick, 2011 ), as well as learning outcomes (Adam, 2004 ; Cedefop, 2017 ). Student-learning outcomes vary in areas, including academic learning achievement, attitude, motivation, and higher-order thinking skills. Moreover, some studies said that the learning process and learning outcomes might differ on many factors, such as the subject of study, learning duration, or even kinds of environmental conditions (Marton, Alba, & Kun, 2014 ; OECD, 2018 ). Furthermore, a strong link between the quality of the learning process and outcomes from STEM education, which originated from the west, constitutes a fundamental reason for educators and policy-makers to apply the same principles in Asian countries (Khaeroningtyas, Permanasari & Hamidah, 2016 ; Yildirim, 2016 ).

Even though the eastern countries (Asia) and western countries (notably, the USA) have many differences such as in teaching and learning characteristics as well as their culture (Di, 2017 ; Hassan & Jamaludin, 2010 ; Lee, Chai, & Hong, 2019 ), both regions have similarities, primarily in terms of problems and challenges faced in the education field. The birth and development of STEM education in the west were motivated by the low interest of the younger generation in work related to the STEM field (Chesky & Wolfmeyer, 2015 ). This low-interest condition was also exacerbated by the increasing competitiveness of workplace and uncertain global world challenges (Chesky & Wolfmeyer, 2015 ). Indeed, this condition is also the same as that faced by most countries in Asia. The problem of low student interest in a subject related to STEM, the lack of interest for young people in STEM-related work, and the highly competitive global challenges of the world, are similar to what happened in the USA (Jayarajah, Saat, Rauf, & Amnah, 2014 ; Kim, Chu, & Lim, 2015 ).

New changes are needed for the teaching and learning process that can address the challenges faced by Asian countries. Therefore, it is not surprising that over the last decade, there has been a good deal of research done by researchers and teachers in Asia, especially related to STEM enactment in classrooms (Lee et al., 2019; Lutfi, Ismail, & Azis, 2018 ; Yildirim, 2016 ; Yıldırım & Altun, 2015 ; Yıldırım & Sevi, 2016 ). Currently, STEM enactments in Asia not only focus on extending STEM-related subjects and students’ interest but also on concerns about students’ twenty-first-century learning outcomes such as real-world problem-solving capacity, academic learning achievement, as well as higher-order thinking skills (Lee et al., 2019). STEM implementation in Asia is often accompanied by a learning approach or model (Suratno, Wahono, Chang, Retnowati, & Yushardi, 2020 ). An evaluation and current status of whether STEM education also has a good impact, specifically in terms of learning outcomes in the Asian region, is logically necessary.

Several extensive works on the effectiveness of STEM education on learning outcomes have been published (Jayarajah et al., 2014 ; Saraç, 2018 ; Yildirim, 2016 ). Research showed that STEM education is effective in improving students’ learning outcomes, such as academic learning achievement, student motivation, attitude, problem-solving skills (Saraç, 2018 ; Yildirim, 2016 ). Further research shows that more than two-thirds of publications in the STEM field come from America (Lee et al., 2019). Lee et al. also state that further research is needed to adjust the STEM education for the conditions faced by Asian countries. The statement indicates that an important consideration is how to redesign curricula in Asia in a way that accommodates STEM education. Another research conducted by Mustafa, Ismail, Tasir, Said, and Haruzuan ( 2016 ) reviewed effective strategies in integrating STEM education globally for many purposes, including student-learning outcomes. Based on this study, project-based learning was the most effective strategy to implement STEM education among Asian countries; especially studies were focused on students in the secondary setting. Furthermore, some studies have recently reviewed the trend of research in STEM education. The studies argued that research in STEM education is increasing in importance globally and being an international field (Li, Froyd, & Wang, 2019 ; Li, Wang, Xiao, & Froyd, 2020 ). However, none of the studies revealed the effectiveness of STEM enactment in the Asian sphere with all the characteristics inherent in said countries. It is crucial to delve into the effectiveness of STEM enactment in Asian countries, which from some aspects, are quite different. However, many problems faced in education have similarities to the western country, the USA, where STEM education originated. Moreover, that is important to know whether STEM education is a fundamental tool in Asia toward improved learning outcomes. Therefore, this current study will have considerable impacts and substantial contributions to the knowledge body of STEM education throughout the world.

Research focus

This study points out a systematic result of the review and a meta-analysis pertinent to how the impact of STEM enactment to Asian students’ learning outcomes. The main focus of learning outcomes under investigation is students’ academic learning achievement, higher-order thinking skills, and motivation. The key questions that guide this study are as follows:

What is the portrait of STEM enactment in Asian countries in terms of region, subject, and education level?

Do the STEM enactments influence students’ academic learning achievement, higher-order thinking skills (HOTS), and motivation in Asian countries?

Under what circumstances and for what learning outcomes are STEM enactments more effective in Asian students?

STEM education and its significant development in Asian regions

STEM education has a very broad meaning. Therefore, many definitions were developed and discovered during the last two decades. Bybee ( 2013 ) states that STEM education can consist of a subject, intradisciplinary, interdisciplinary, or can be a particular discipline. Furthermore, Bybee ( 2013 ) and Sanders ( 2009 ) asserted that STEM education is a spectrum that focuses on solving real problems, which have an interdisciplinary nature at its core. Another opinion states that STEM education is a meta-discipline based on learning standards where teaching has integrated teaching and learning approaches, and where specific content is undivided, contemplating a dynamic and fluid instruction (Merrill & Daugherty, 2009 ). A more modern definition states that STEM education is an interdisciplinary teaching method that integrates science, technology, engineering, mathematics, and other knowledge, skills, and beliefs, in particular, to these disciplines (Baran et al., 2016 ; Koul, Fraser, Maynard, & Tade, 2018 ; Thibaut et al., 2018 ). Thus, STEM education is a term referring to teaching and learning in a STEM subject, which emphasizes problem-solving with real-world problems integrating many disciplines and other skills such as science, technology, mathematics, and engineering.

STEM education has been present for more than two decades (Timms, Moyle, Weldon, & Mitchell, 2018 ). The term STEM started from the term SMET (science, mathematics, engineering, technology), which came into existence in the 1990s (Chesky & Wolfmeyer, 2015 ). Some education experts from western countries (notably, the USA) initiated STEM education. This approach grew in popularity after the US government announced the plan to advance education into STEM education in 2009 (Burke & McNeill, 2011 ). STEM education is highly promoted in the USA to encourage the next generation into training within the fields of STEM. Furthermore, Burke & McNeill argued that another goal was to maintain the enthusiasm of the younger generation in their interest in STEM-related careers. However, the essential goal is that both students and the younger generation can face the competition of the new global world.

The rapid development and functional effects of STEM education programs in western countries have attracted the interest of many researchers and policy-makers from other countries (Sheffield et al., 2018 ; Timms et al., 2018 ), including Asia. Eastern countries face similar problems where there is a lack of interest from the younger generation in careers related to STEM (Jayarajah et al., 2014 ; Kim et al., 2015 ; Sin, Ng, Shiu, & Chung, 2017 ). Furthermore, Jayarajah et al. ( 2014 ) and Shahali, Halim, Rasul, Osman, & Zulkifeli ( 2017 ) exemplify Malaysia consistently registers lower numbers of citizens interested in science, engineering, and technology issues compared to the USA. As for the Malaysian population, it shows that more than one-third of the children clearly expressed a lack of interest in science and technology. Another researcher, Kim et al. ( 2015 ), asserts that in the last two decades, Korea has faced a problem in science and engineering education, which is students’ disinterest in science and math, even though their achievement in science and math is high. Another crucial reason is that STEM education promises as an appropriate tool for students in facing challenges and global competition (Kim et al., 2015 ; Meyrick, 2011 ; Yildirim, 2016 ).

Several parts of Asia, such as Western Asia, Eastern Asia, and Southeastern Asia, are now aggressively implementing and developing STEM education (Chen & Chang, 2018 ; Choi & Hong, 2015 ; Karahan, Bilici & Unal, 2015 ; Park & Yoo, 2013 ). Some countries such as Korea, Thailand, and Malaysia have focused on STEM/ STEAM education as an essential part of their education system (Cho, 2013 ; Hong, 2017 ; Hsiao et al., 2017 ; Kang, Ju, & Jang, 2013 ; Shahali, Ismail, & Halim, 2017 ). While in other countries in Asia, even though STEM education has not become a regular part of the education system, many researchers or teachers have enacted STEM education. Several review studies have pointed out that the trend of research on STEM education in Asia began in 2013. Today, STEM has become a phenomenon that attracts many people (Jayarajah et al., 2014 ; Lee et al., 2019). Therefore, during this booming stage in Asia, it is crucial to know the extent of the impact of STEM enactments, especially concerning the students’ learning outcomes.

The supporting of instructional strategies on STEM education

The implementation of STEM education is carried out in various ways throughout the world, including in Asia. Some learning approaches or learning models are combined and or juxtaposed with the STEM enactment (Chung, Lin, & Lou, 2018 ; Lou, Tsai, Tseng, & Shih, 2014 ). For example, the researchers used project-based learning, problem-based learning, or the 6E learning model in enacting STEM education. This combination is needed to strengthen the expected effect after STEM learning (Mustafa et al., 2016 ). Furthermore, the modification and or combination of STEM with learning approaches or models have a high potential in facilitating implementation and for achieving effective instruction (Martín-Páez, Aguilera, Perales-Palacios, & Vílchez-González, 2019 ; Mustafa et al., 2016 ). However, STEM learning may be implemented with or without other learning approaches (Chung, Lin, & Lou, 2018 ; Martín-Páez et al., 2019 ). Moreover, Jeong and Kim ( 2015 ) proposes that effective instruction occurs when students are given the learning opportunity to demonstrate, adapt, modify, and transform new knowledge to meet the needs of new contexts and situations. Successful implementation of instruction, of course, leads to the accomplishment of predetermined targets, in this case, improved student learning outcomes.

Ample studies suggest using the project-based learning (PjBL) approach to implement STEM education. Mustafa et al. ( 2016 ) investigated the dominant instructional strategies to promote the integration of STEM education at different institutional levels. Mustafa et al. argued that combined with project-based learning was the most effective way to implement STEM education. This assertion is reasonable because PjBL characteristics are quite similar to the integrated STEM approach (Siew, Amir, & Chong, 2015 ). Chiang and Lee ( 2016 ) said that the characteristics of PjBL are encouraging students to work cooperatively, developing students’ thinking skills, allowing them to have creativity, and leading them to access the information on their own and to demonstrate this information. Finally, Çevik ( 2018 ) revealed that a learning environment created with STEM-PjBL is vital for solving the complexity of critical concepts in STEM fields. Thus, the role of several factors, such as learning approaches (e.g., PjBL), learning models, and or modifying STEM itself, become critical elements that must be considered when implementing STEM education.

Students’ learning outcomes estimated on STEM enactment

Learning outcomes are the main target in a learning process, including on STEM enactment. Cedefop ( 2017 ) argued that students’ learning outcomes are all types of results expected during and after the learning process. Another researcher, Adam ( 2004 ), states that learning outcome is a teaching result, which is expected to be obtained by students after a learning process. Further, Adam stated that learning outcomes are usually expressed in the form of knowledge, skills, and or attitude. Slightly different, Gosling and Moon ( 2002 ) state that there is no precise way of defining or writing the meaning of such learning outcomes, but a learning outcome must be measurable. It can be concluded that a learning outcome is a result of the learning process. Consequently, learning outcomes can be various forms, depending on the purpose expected by a teacher.

In this study, the estimated learning outcomes after STEM enactments concentrated on academic learning achievement, higher-order thinking skills (HOTS), and motivation. Theodore ( 1995 ) defined students’ achievement as a measurable behavior in a standardized series of tests. HOTS is the ability to apply skills, knowledge, and values in reasoning as well as in reflection (Pratama & Retnawati, 2018 ; Wahono & Chang, 2019a ). Indeed, such an ability is crucial to making decisions, solve problems, innovate, and create. In terms of practical application, HOTS includes students’ thinking ranked above level three, according to Bloom’s taxonomy (Baharin, Kamarudin, & Manaf, 2018 ). Finally, the students’ learning motivation defines as a process where the learners’ attention becomes focused on meeting their educational objectives (Christophel, 1990 ; Kuo, Tseng, & Yang, 2019 ). Therefore, the educational and developmental fields give strategic reasons for the focus on these particular skills. For instance, these skills have been related to twenty-first-century skills, future educational attainment, and participation in STEM careers later in life (Martín-Páez et al., 2019 ; Wahono & Chang, 2019b ). Furthermore, HOTS can be used in STEM, and research verifies these abilities in STEM fields can be transferred to other learning fields (Lin, Yu, Hsiao, Chang, & Chien, 2018 ; Yıldırım & Sidekli, 2018 ). Moreover, the learning outcomes can be influenced by several external factors, including culture and learner characteristics.

Asian culture and characteristics of teaching and learning

Many factors may influence the effectiveness of learning outcomes in STEM learning. However, Han, Capraro, and Capraro ( 2015 ) explained that the two most important factors were the learning environment and the level of individual students. The learning environment can be either a classroom environment or a cultural environment. Based on the literature review, there are many definitions of culture. However, most general definitions include that culture is a combination of many things such as beliefs, values, and assumptions trusted and understood among society (Rossman, Corbett, & Firestone, 1988 ; Schein, 2010 ). It is widely accepted that the characteristics of a culture affect individuals’ social behavior (Hampden-Turner & Trompenaars, 1997 ; Hofstede, 2005 ). More specifically, when cultural influences are insignificant and less integrated into a learning activity, students will likely experience a misunderstanding that hinders interactions between students and teachers (Popov, Biemans, Brinkman, Kuznetsov, & Mulder, 2013 ; Popov et al., 2019 ). Many studies show that culture, ethnics, geographical position, gender, language proficiency, and/or a combination of these components have a significant influence on students’ learning success (Han et al., 2015 ; Konstantopoulos, 2009 ; Shores, Shannon, & Smith, 2010 ). Rodriguez and Bell ( 2018 ) mentioned that the instruction in the STEM learning should acknowledge some specific contributions of members from diverse cultures. Thus, culture holds a crucial role in the successful process of student learning in class. Therefore, highly probable that the Asian cultural characteristics and habits have a significant impact on students’ performance and learning outcomes by STEM enactment.

In general, in eastern education, students practice remembering concepts; this philosophy focuses mainly on learning and memorization within the teaching and learning process (Lin, 2006 ; Thang, 2004 ). The eastern education system is exam-oriented. Time (duration) is a fundamental factor in teachers’ performance (Tytler, Murcia, Hsiung, & Ramseger, 2017 ) as they must go over textbooks to prepare students for the final tests. As a result, students tend to memorize the facts in textbooks rather than understanding it due to time constraints. Thus, the situation creates positive competition among students and eventually triggers the efforts of students to obtain and understand the knowledge considered pivotal to achieving a good score in their examination. Eastern-culture education is more generally systematic, with a standardized syllabus and timetable, when compared to western-culture education (Hassan & Jamaludin, 2010 ; Tytler et al., 2017 ). However, it is undeniable that this type of character (rote learning, exam-oriented, and curriculum oriented) is one of the reasons many of the Asian countries score inside the top ten, in international tests (Marton et al., 2014 ; OECD, 2018 ). Therefore, in the case of STEM enactment, in-depth investigation, whether the time (duration) has a significant impact on the students’ learning outcome is paramount.

Moreover, Asian countries are very different from western countries, especially in their educational philosophy, which tends to be robustly laden with religious and cultural-centric elements (Hassan & Jamaludin, 2010 ). By contrast, the opinions on such characteristics of the eastern-culture education must be addressed carefully. However, any consequences of those educational characteristics in the implementation of STEM in Asia can be assumed, such as the main target of STEM enactments are not merely to attract student interest in the lesson or higher-order thinking skills, but also more to obtain a higher academic learning achievement. In terms of learning materials and processes, the consequences are seen from many STEM enactments that actively grappled to cultural values, i.e., identify halal products by augmented reality (Majid & Majid, 2018 ; Mustafa et al., 2016 ). We firmly believed that such consequences are unique, which led to the potential impact of STEM enactment outcomes in Asia. Therefore, the current research aims to prove that STEM enactments carried out in the past few years have generated a wide range of impacts, especially in Asia.

Research model

This research applied a quantitative approach. A meta-analysis method was used to determine the effectiveness of STEM education for students’ learning outcomes in the Asian region. The meta-analysis method was operative in this study because it enabled an objective investigation of the effect of the independent variable on the dependent variable that is STEM education toward the student’s learning outcome, respectively. Cohen, Manion, and Morrison ( 2007 ) state that with a meta-analysis, researchers can evaluate, compare, or combine quantitative data obtained from previous experimental research studies to acquire more convincing and comprehensive results. We identified studies to include in the review, coded for potential moderators, and calculated and analyzed effect sizes.

Selection of studies

The data collection in this study was carried out over 3 months, from February to April 2019. In the screening, several databases, including Scopus, ERIC, ScienceDirect, and Google Scholar, were utilized as the primary search references. We collected the data in the form of journal papers, proceeding conferences, books, or dissertations. Conferences, books, and dissertations were also included as data sources, namely to capture and find what is called the “file drawer” for information, which might not be published in journals (Rosenthal, 1979 ). Most of the data sources were in English, but there were also some non-English ones. However, from these data sources, at least the title or abstract were in English. The following keywords were at work upon data collection, including the effect of STEM, the effect of STEM learning, the effect of STEM approach, STEM and learning outcomes, STEM and student achievement, STEM and student motivation, and STEM and higher-order thinking skills. When searching, all the keywords used were in English.

A multilevel screening was carried out by applying several criteria, as shown in Fig. 1 . The first-level screening of the papers was geared to collecting research papers aimed to examine the effectiveness of STEM education, such as the effectiveness of STEM on academic achievement, motivation, and HOTS. The second screening was based on whether the data was collected from Asian countries or not. The third stage of screening was concerned with whether the study was qualitative, quantitative, or mixed-method research. At this stage, we applied quantitative and mixed-methods research. The last step dealt with whether the paper had the minimum quantitative data required for calculating an effect size, such as mean, standard deviation, variance, number of respondents, the value of t , and the value of F . The results obtained from the first stage were more than 283 papers, while those that satisfied the second-stage criteria were 86 pieces. In the third selection, there were 63 articles. Finally, at the ultimate stage, there were 54 studies (see Supplementary Materials for the list of reviewed articles).

Process of studies selection

Concerning the quality of studies collected in this review, most of the studies came from research papers published by peer-reviewed journals and conferences. The studies were taken from journal papers (46), conference papers (6), book chapter (1), and a thesis (1). All the studies were carried out in the form of classroom-based research from Asian countries. The total participants involved in this study were 4768 students, or in other words, about 111 students in each study. Those studies included primary school students, secondary school students, or higher-education students. The number of countries involved in this study was ten countries, including Turkey, Israel, Uni Emirate Arab, Taiwan, Korea, China, Hong Kong, Malaysia, Indonesia, and Thailand.

Data coding

Coding in this study was done to make it easier to analyze the obtained data. The coding included several biographical features such as sample size, year of publication, region, topic or subject, education level, and the type of learning outcome. The year of publication in this search ranged from the publications in 2009 to those in 2019. This range allowed for a vast number of studies in the last decade to be investigated. In terms of the region, we divided the Asian region into five regions based on the United Nations. The region included Eastern Asia, Western Asia, Southern Asia, South-Eastern Asia, and Central Asia. The term “subject” here meant a name of discipline or a class where the STEM enactment took place in the data source. In this case, we focused on three groups, particularly science, mathematics, and technology or engineering subjects. For instance, a STEM enactment from Sarican and Akgunduz ( 2018 ) has a topic about force and motion, which is a sort of “science” subject source. Furthermore, we divided educational levels into three groups, namely higher education level, secondary education level, and primary education level.

Finally, we divided learning outcomes into three major groups, namely academic learning achievement (ALA), higher-order thinking skills (HOTS), and students’ motivation (Mo). ALA defined as students’ scores, from either the mean of pretest/posttest or only the mean of the posttest score. ALA was tested to get information regarding students’ content knowledge. Meanwhile, HOTS score was collected from HOTS subset codes such as problem-solving, design thinking, creative thinking, reflective thinking, and includes students’ thinking ranked above level three (level 4–level 6) according to Bloom’s taxonomy. The HOTS studies, in general, performed such as a creativity test (fluency, flexibility, originality, and elaboration), a score of analyzing, evaluating, and creating assessment tests. Then, we recognized the Mo score from the domain, namely student motivation or student interest. In general, students’ motivation was measured in the studies through a questionnaire, including intrinsic motivation, self-determination, self-efficacy, and grade motivation.

In doing so, a description of the measure or process on those variables (ALA, HOTS, Mo) in this current study are discussed. Inevitably, each outcome was measured differently among the studies reviewed. For instance, a HOTS study reported scores of students’ problem-solving abilities, whereas another study of HOTS reported a set score of students’ creative thinking, and even a study of HOTS had reported an effect size of what the article authors called “HOTS scores before and after an intervention.” To deal with this concern, we performed some technical works. For example, initially, as a primary resource, we collected all the existing effect size scores of ALA, HOTS, and Mo studies. In the situation where we could not directly find the effect size scores of the selected studies, we would collect other supporting data. We required the supporting data for calculating the effect size, namely standard deviation, mean score, number of respondents, the value of t , and the value of F . Finally, we computed and standardized the collected data by statistical software (see data analysis).

To address the third research question in this study, we coded three moderator variables that could contribute to the STEM enactment effectiveness, namely, approach or learning model, learning orientation, and duration of instruction. The coding was distilled from the theoretical review framework in the introduction part. For instance, several studies revealed that some learning approaches or learning models are combined and or juxtaposed with the STEM enactment (Chung, Lin, & Lou, 2018 ; Lou, Tsai, Tseng, & Shih, 2014 ). Likewise, the duration of instruction is a fundamental factor in teachers’ performance in Asia (Tytler, Murcia, Hsiung, & Ramseger, 2017 ). Eastern-culture education is more generally systematic, with a standardized syllabus and timetable, when compared to western-culture education (Hassan & Jamaludin, 2010 ; Tytler et al., 2017 ). Moreover, Asian countries tend to be robustly laden with religious and cultural-centric elements (Hassan & Jamaludin, 2010 ).

In terms of the approach or learning model , the authors coded each study, whether it was accompanied by another approach/learning model (present) or only STEM lesson without clearly the presence of other approaches (absent). The authors have coded learning orientation into two types, namely culture centric and universal oriented. The culture centric refers to the study, which much follows the unique characteristics of Asian students, such as strongly curriculum oriented, more systematic with standardized syllabus and timetable, or tends to be robustly laden with religious and local cultural elements. The universal oriented study refers to a freer lesson, the selected studies because the curriculum was not as strict, and or the themes on STEM lesson did not much emphasize unique themes, in particular, Asian countries. Finally, the authors coded the duration of instruction as a short or long period. The long duration refers to STEM enactment that was conducted by more than two-time class periods, and the short was conducted by only one-time class periods (2 h or less).

Publication bias

Another thing that needed to be clarified was how the researchers coded whether a study investigated the STEM enactment or not. In this case, the researchers referred to several works (Bybee, 2013 ; Li, Wang, Xiao, & Froyd, 2020 ; Martín-Páez et al., 2019 ). The researchers point out that there is not a fixed consensus in the literature about under what condition(s) learning was said to be STEM learning. However, in general, they (Bybee & Martin-Paez et al.) say that STEM learning emphasizes problem-solving with real-world problems involving many disciplines and other skills such as science, technology, mathematics, and engineering in integrated ways. Furthermore, this study focused on articles related to such STEM definitions, and/or at least, the authors in the paper mentioned that they used the STEM education approach (an integrated STEM). Moreover, we selected publications from 2009 to 2019, meaning that a vast number of STEM enactments by this time were included in the intended definition.

Concerning publication bias, we have met some difficulties in obtaining unpublished papers, especially in the research area of STEM enactment in Asia, in terms of its impact on learning outcomes. In terms of an alpha level significance (0.05), this current study shows, specifically, that more than 14% of the reported effects were not/less significant. These findings are consistent with the varieties in perspectives concerning the inferiority, superiority, or equivalence of STEM enactment for various learning styles. The condition that only 14% of the study was not a significant effect is not because of the file drawer studies remain unpublished due to the magnitude, significance, or direction of their effects, but rather because of other factors such as written in local language as well as the quality of the studies (McElhaney, Chang, Chiu, & Linn, 2015 ).

Data analysis

The data collected from various references, such as journals, books, proceedings, and dissertations investigating the effect of STEM enactment, were then analyzed using the meta-analysis method. Data were all aimed at accessing the same target, namely students’ learning outcomes (academic learning achievement, motivation, and higher-order thinking skills). The multitude of data was examined using the meta-analysis method for systematic and beneficial analysis. We argued that making quantitative data comparisons of various studies as one of the challenging and vital jobs in the world of research today.

A summary effect size (E.S.) using a random effect model value was the dependent variable in this study, while the independent variable was the STEM enactment in diversified ways and types. A random effect model assumes that the true E.S. varies from one study to the next, and the summary effect is our estimate of the mean of these effects (Pigott, 2012 ). Therefore, in this study, we do not want that overall estimate to be overly influenced by any of them. Meanwhile, in terms of potential moderator variables, a mixed-effect model was used. The mixed-effect model allows us to get a trade-off from the true E.S. In the moderator variable case, the trade-off from the true E.S. is vital due to the comparison between two sub-variables (e.g., short and long of the instruction duration). In doing so, the investigations of effect size and visualization were carried out using the Jeffreys’s amazing statistics program (JASP) version 0.11.1 program, especially by the Hunter-Schmidt method. This method was used due to the ability to estimate the variability of the distribution of effect sizes through a two-step process, namely subtracts to yield a residual variance and boosts by a function of the reliability and range restriction distributions (Hunter & Schmidt, 2004 ). To deal with the effect sizes for some studies reporting only F or t values, or even reported Hedges g , the authors used algebraic techniques (Lipsey & Wilson, 2001 ) as well. In social science, a common practice for overcoming this task is to calculate Cohen’s coefficient (Cohen, 2013 ). In this study, Cohen’s theory was determined by the difference between the average control group and the experimental group (see Eq. 1 ) or the difference between the average posttest score and the pretest score (Eq. 2 ) (Howell, 2016 ).

Let \( \overline{x} \) i , S i , and n i be the sample mean, standard deviation, and size of the group I, while S pooled , S diff , r , and S d be the pooled standard deviation, the differences of standard deviation between pre and post, the correlation between pre- and post-treatment score, and standard deviation of Cohen’s d.

When the calculated magnitude effect size was large, a classification was deployed in this meta-analysis method. In the current study, the authors used the classification level of (Sawilowsky, 2009 ). This classification system was a revised version of Cohen’s work in 1988. Thus, when the effect size was less than 0.20, it was considered very small, while when it ranged from 0.20 to 0.49, it was classified as small. The effect size, which ranged from 0.49 to 0.79, was at a medium level. A large level was evident from 0.80 to 1.19. Between 1.20 and 1.99 was classified at a very large level. A value over 2.0 was regarded to have a huge effect. A d coefficient of one indicates that the difference between two means is equal to the standard deviation (S.D.). If Cohen’s d is larger than one, the difference between two means is larger than one S.D. Anything larger than two means that the difference is larger than two standard deviations. This calculation afforded a uniform scale in expressing all possibilities that show a relationship between variables. Regarding the variability observed in this study, we have standardized the magnitudes between the differences in interventions and outcomes measured. The results of the study were summarized and combined systematically using a commonly termed the standardized effect size, namely the standardized difference in means.

The main objective of this study was to investigate whether STEM education originating and developing from the western countries (the USA) also affected students learning outcomes in the Asian environment. Another aim was to investigate whether there is a specific factor that contributes to the effectiveness of STEM enactment. Finally, another aim was to know more about the development and the enactment of STEM education in Asian countries. As a result, in terms of effect size, this current study found varies or heterogeneity. The value ranged from negative (− 0.19; 95% CI = − 0.78 to 0.40) to positive effect (+ 2.81; 95% CI = 2.01 to 3.61) (see Supplementary Materials for the list of effect sizes, study features, and coding elements).

The general portrait of study

Based on the literature reviewed, the first publications to assess the effect of STEM education on the learning outcome in Asia began in 2013. This time was only 4 years after the advent of STEM by the US government in 2009. Nevertheless, the authors assume that STEM education studies in Asia began to gain traction long before 2013. However, many of those studies were qualitative research, or the studies were not directly related to students’ learning outcomes. Table 1 illustrates the descriptive analysis of STEM educations in Asia, especially those related to the students’ learning outcomes.

In this study, we found that three Asian regions substantially contributed to the implementation and development of STEM education. Table 1 also shows that the Asian countries have conducted most studies on STEM education and its impact on students’ learning outcomes, with East Asia being the biggest contributor (25 studies), followed by West Asia (16 studies) and Southeast Asia (13 studies). However, there were significant differences in results between the three regions (Q .B. = 4.208, p < .05). Furthermore, the difference evinces that STEM education is significantly effective in Southeast Asia, as evidenced by its impact on the learning outcome, greater than that in other regions (E.S. = 1.211). This value is a combination of the value of academic learning achievement, higher-order thinking skills, and motivation.

In terms of the subject or topic guiding the implementation of STEM education in Asia, Science is the most widely researched. Conversely, mathematics is the least popular topic. However, there was no significant difference (Q .B. = 0.638, p > .05) when the effect of STEM education on the learning outcome related to topic or subject matter was investigated. Also, related to the level of education, this study found that the level of secondary education (junior and senior high school) has been widely researched (28 studies). In contrast, the higher education level (college or university level) is the least researched area (10 studies). At the same time, the statistical analysis also showed no significant difference (Q .B. = 2.880, p > .05), the effect of STEM enactment on learning outcomes in terms of education levels. Nevertheless, this difference suggests that STEM education tends to influence at secondary-level education (E.S. = 1.009) compared to the other two levels (primary and higher education level).

The effect of STEM enactment on students’ learning outcomes

In terms of student learning outcome, in line with the second research question, the investigated focused on academic learning achievement, higher-order thinking skills, and motivation. Furthermore, based on the analysis results, the summary effect of the overall effect size is 0.69 [0.58, 0.81 of 95% CI]. According to Sawilowsky ( 2009 ), this value is classified as a medium level of effect. Detailed results between the three types of learning outcomes (learning achievement, higher-order thinking skills, and motivation) can be seen in Figs. 2 , 3 , and 4 .

A forest plot of students’ academic learning achievement (ALA)

A forest plot of higher-order thinking skills (HOTS)

A forest plot of students’ motivation (Mo)

Academic learning achievement

This study assumes that academic learning achievement is crucial in Asian students, even for the students’ parents. The rationale of this statement is related to the culture and characteristics of education, which is embraced in Asian countries (Hassan & Jamaludin, 2010 ; Tytler et al., 2017 ). Thus, one of the objectives of this study was to determine whether the implementation of STEM enactment in Asian countries affected the students’ academic learning achievement. In this study, we analyzed academic learning achievements from 24 studies that met the criteria (see the criteria on the “Selection of studies” section). The results of the analysis and distribution are shown in Fig. 2 . Figure 2 below is a forest plot of students’ academic learning achievement.

The forest plot shows black squares and whisker lines (see Fig. 2 ). The black squares indicate the magnitude of the STEM effect on academic learning achievement, whereas the whisker lines indicate the upper and lower limit of the value of the confidence interval. The vertical dashed line is a line that shows the position of the effect size with a zero value. Thus, the right area of the line is positive values, whereas the left area of the line shows a negative value of effect sizes.

In Fig. 2 , there are 20 studies where the Cohen value of d is below 1.0, while the other four studies have an effect size of more than 1.0. In addition, it is also known that a study seems a different appearance from the others, namely a study from Han, Rosli, Capraro, and Capraro, (2016) with Cohen’s values d 0.28 [0.16, 0.40 of 95% CI]. The black squares with short whisker lines indicate that the study has a very small range of the confidence interval. The minimum value of the confidence interval was due to the huge sample size in the study. Overall, the effect of STEM enactment for students’ academic learning achievement was 0.64 [0.48, 0.79 of 95% CI]. This positive d value indicates that STEM education affects students’ academic learning achievement in Asia. In classifying effect size, the value of .64 belongs to the medium effect category.

Higher-order thinking Skills

The second objective of this research is to find out more about whether STEM education affects students’ higher-order thinking skills (HOTS). To address this question, Fig. 3 below is a forest plot from Cohen d analysis about 16 previous studies that helped provide sufficient details.

Figure 3 illustrates the spread of effect size from 16 studies on students’ higher-order thinking skills (HOTS). The analysis results of the forest plot illustrate ample information. One interesting insight is the summary effect of 1.02 [0.71, 1.32 of 95% CI]. According to Sawilowsky ( 2009 ), this value is classified as a large effect. However, the largest d value in the study is reaching 2.81 [2.01, 3.61]. The value of d (2.81) means that the effect size value is twice the standard deviation value, while the smallest d value is at .06 [− 0.45, 0.57]. At a glance, there is a considerable difference between the largest values, the data distribution pattern, and the summary effect. This state is due to a study, which is Han et al. ( 2016 ) study reports the highest magnitude. The highest magnitude occurred because the study includes the largest sample size (1187 people). A large sample size certainly affects the result of the summary effect.

Another goal to be achieved in this study is to find out whether STEM education is effective in increasing student motivation in Asia. Figure 4 below illustrates the details of the data distribution from 14 previous researchers. The studies measure student motivation distributed across many topics, including science, mathematics, technology, and engineering.

The illustration of Fig. 4 , designated by the forest plot, are normally distributed ( p > .05). However, Cohen’s d value is spread from the smallest (− 0.08) to the largest d value (1.58). Furthermore, the figure indicates the summary effect value is 0.49 [0.32, 0.65 of 95% CI]. The summary effect value of .49 in the Sawilowsky classification is categorized as a medium effect. Therefore, the STEM enactment is Asia has a great impact on students’ motivation as well as two others (academic learning achievement and higher-order thinking skills).

Moderator variable of STEM enactment’s learning outcomes effectiveness

In addition to knowing the extent to which STEM enactment in Asia affects the students’ learning outcome that includes academic learning achievement, higher-order thinking skills, and motivation, this study also answers whether there are specific factors behind that effectiveness. In particular, this section addresses the research question about under what conditions and for what learning outcomes are STEM activities more effective in Asian students. Several potential variable moderators, such as approach or learning model, research design, learning orientation, and duration of instruction, were analyzed to address the research question.

As shown in Table 2 , several moderator variables reveal identical results in terms of student academic learning achievement. STEM enactment has a significant effect on the approach or learning model variable ( p = .037). The presence of an approach or learning model contributes better to the effectiveness of STEM enactment. Other moderator variables that also show significant results are learning orientation ( p = .039). STEM enactment, which tends to be culturally centric, gives a different effect compared to what is only universal oriented. Also, the last moderator variable that addresses significant results is the duration of instruction ( p = .016). In this variable, a longer time provides better effectiveness in terms of student academic learning achievement.

Heterogeneous results in higher-order thinking skills, especially in terms of the potential moderator variable, are shown in Table 3 . The factor, the duration of instruction, shows a significant result ( p = .046). Furthermore, the variable duration of instruction shows that time (long duration) has a crucial role in increasing the higher-order thinking skills of students in STEM enactment. Unlike the case for the duration of instruction, the other two factors (approach or learning model and learning orientation) do not address any significant differences ( p > .05). This condition proves that whether STEM is carried out, with or without another approach or learning model, and whether learning orientation tends to be cultural centric or universal oriented, the higher-order thinking skills of students have relatively the same effectiveness.

The results that are quite different concerning the potential moderator variables affecting the effectiveness of STEM enactment are shown in Table 4 . In Table 4 , the table shows that no moderator variables have the potential to differ rather significantly in the motivation of students in Asia. The three moderator variables, namely approach or learning model, learning orientation, and duration of instruction, show identical results that there is no significant difference ( p > .05). These results mean that whether STEM enactment is accompanied or not by other learning approaches, cultural centric or universal oriented, or done with short or long periods, the effect on students’ motivation tends to be the same.

The overview of STEM enactment in Asia

As a portrait of STEM enactment in Asia, this current study tends to focus on the three variables, namely region, subject, and education level. We found that Eastern Asia was the most contributed to STEM researches, especially those related to the impact on student learning outcomes. On the other hand, the difference evinces that STEM education is significantly effective in Southeast Asia, as evidenced by its impact on the learning outcome higher than that in other regions. The different effects among regions are mostly due to an interaction of some factors, such as the differences regarding the number of published studies and the differences in students’ learning outcomes baseline (Saraç, 2018 ; Yildirim, 2016 ). For instance, the result showed that students’ motivation and HOTS were proven higher than students’ academic learning achievement, which is mostly found in the studies on Southeast Asia (Lestari, Astuti, & Darsono 2018 ; Lestari, Sarwi, & Sumarti, 2018 ; Ismayani, 2016 ; Soros, Ponkham, & Ekkapim, 2018 ; Surya, Abdurrahman, & Wahyudi, 2018 ; Tungsombatsanti, Ponkham, & Somtoa, 2018 ). The baseline of Southeast Asia learning outcome is lower than in other regions due to the low quality of educational practice (OECD, 2018 ). Thus, this study suggests that those students with a lower baseline of higher-order thinking skills will benefit the most from the STEM enactments. In terms of education level, the result showed that most studies were conducted at the secondary education level. The condition of most studies conducted in STEM education from the secondary education level is in line with the resulting study from Saraç ( 2018 ). The only difference from Sarac’s study is that the reviewed subjects came from all over the world and did not focus distinctively on the Asian region. However, in terms of effect size, there was no significant effect appearing in this variable.

Furthermore, STEM education applications on mathematical topics or subjects are small in the number when compared to topics or subjects of science and engineering. This case is in line with the results of research from Saraç ( 2018 ). Sarac has found that the application of STEM education related to the learning outcome is still very limited in mathematics-related topics. The situation reflects that STEM education research on the other focuses, such as students’ attitudes (besides focusing on the learning outcome), is also lacking. This condition is because quite challenging to associate mathematics-related topics and STEM education. Wahono and Chang ( 2019a ) revealed that, when utilizing the STEM education approach, teachers felt challenged in connecting subject matter topics. The characteristic of mathematics, which is fundamentally theoretical and abstract (Acar, Tertemiz, & Tasdemir, 2018 ; Sabag & Trotskovsky, 2013 ), represents a stark contrast to the characteristics of STEM education, which involves activity that is more physical. Thus, it represents a critical reason why STEM enactment of the mathematical topic has a small number. However, there is still a tremendous opportunity to apply STEM education to mathematical-related topics. Examining students’ learning outcomes through particular STEM activities in mathematics is one of the worth for next future research. As evidenced in this study, we found only eight studies in Asia related to mathematics and learning outcomes.

Impacts of STEM enactment on Asian students’ learning outcomes

The results of the meta-analysis in this study suggest that the outline of STEM education of students’ learning outcomes in Asian countries differs among variables. The results showed the effect of STEM enactment by order; those are effect sizes on students’ HOTS at a large level (1.02), meanwhile the academic learning achievement and motivation at a moderate level (0.64 and 0.49). This result is advantageous because HOTS generated more of an effect in Asia when compared to students’ academic learning achievement. As Martín-Páez et al. ( 2019 ) and Chang, Ku, Yu, Wu, and Kuo ( 2015 ) stated that, in general, STEM education has the potential to increase students’ interest and higher-order thinking skills. The more substantial effect of students’ HOTS and interest could be due to the nature of the learning tools and processes of STEM education, which are based on eastern cultures and emphasize hands-on activities (Hassan & Jamaludin, 2010 ). The characteristics of STEM education (real-world problem and problem-solving) represent excellent potential for increasing students’ HOTS. Higher-order thinking skills such as problem-solving, critical thinking, and creative thinking are the leading targets in STEM learning in Asia (Barak & Assal, 2018 ; Lee et al., 2019). Therefore, HOTS is a decisive asset for Asian students in coping with global competition and industrial revolution 4.0.

Moreover, the result of academic learning achievement showed that the highest value of effect size (1.86) is in the Majid and Majid ( 2018 ) study. Based on an advanced analysis (a sample case), the study indicated that the researchers deeply embraced the Asian cultural characteristics of education. The study was devoted to several learning topics, particularly about chemical properties, atomic theory, and periodic tables. This Majid and Majid study also provides an example of the application of augmented reality, which is a topic familiar to students in their daily life, namely, to identify halal products. The result showed that the highest effect size value of students’ motivation is in the study of Ugras ( 2018 ). Based on further analysis, this study indicated that the learning process was influenced by the habits that are commonly faced in that particular place (Turkey/Asia). Most of the themes carried out in the learning process using STEM, such as how to build a strong house to withstand an earthquake or other often-encountered themes from daily life by Asian students. Furthermore, the themes or topics (culture and real-world problems) are the central themes in STEM learning. Such learning conditions certainly could encourage students’ enthusiasm and motivation in learning.

Moreover, a large variation has found naturally in the effect size of the Asian student learning outcomes. This condition is logically influenced by several factors such as learning instruction quality (McElhaney et al., 2015 ) and how effective the learning instruction, in this case, STEM enactment, fits into the Asian culture and characteristics (Hassan & Jamaludin, 2010 ). Indeed, a fit and comfortable the instruction to the learner characteristics (i.e., much grappled to cultural values) has strongly supported gaining a better impact on the STEM enactment outcomes. Furthermore, this moderate effect indicates that STEM education is quite promising to prepare students to face unpredictable global competition in the future. However, of course, there are still numerous efforts required to maximize the impact of implementing STEM education in the Asian region, including trying to find the hidden factor behinds the effectiveness of STEM enactment in terms of students’ learning outcomes.

Potential factors contributing to STEM enactment

Therefore, another exciting result to discuss is the role of the moderator variables on the effectiveness of student learning outcomes. Based on the analysis of the academic learning achievement of learning outcomes, better results would be obtained if the STEM enactment is accompanied by an approach, learning model, or other methods. This result is in line with the research from Lee, Capraro, and Bicer ( 2019 ). They (Lee et al.) investigated the role of companion another approach or learning model, in increasing the effectiveness of STEM lessons in the classroom. Lee et al. found that STEM combined with another approach or method (e.g., project-based learning or 6E learning model) would be more effective when compared to STEM lessons without other combinations.

Furthermore, the integration of STEM enactment with another approach or learning model provides better direction and control in the achievement of learning objectives (Mustafa et al., 2016 ). Besides, the results of the present study also show that STEM enactment, which tends to be culture centric, was more effective than universal oriented. This result is probably because culture-centric learning is more in line with most of the characteristics of Asian students who tend to rote learning, curriculum orientation and exam orientation (Di, 2017 ; Hassan & Jamaludin, 2010 ; Lin, 2006 ; Thang, 2004 ; Tytler et al., 2017 ). Therefore, the characteristics are more helpful in terms of increasing students’ academic learning achievement. In addition, the duration of the instruction factor also shows one of the potential factors in influencing the student’s effectiveness in academic learning achievement. Longer times of STEM enactment show to be more effective than shorter times; this result makes sense because, with sufficient time, students could better absorb and gradually improve their academic learning achievement (Çevik, 2018 ; Sarican & Akgunduz, 2018 ).

On the other hand, different conditions were found at higher-order thinking skills and motivation for learning outcomes. The results of both learning outcomes show that only the duration of instruction is significant, especially at the higher-order thinking of learning outcomes. This result means that a long time has the potential to be more effective in increasing higher-order thinking skills for Asian students. Lestari et al. (2018) and Lin, Hsiao, Chang, Chien, and Wu ( 2018 ) stated that time played a vital role in honing students’ higher-order thinking skills such as problem-solving and creative thinking of a STEM education field. However, the duration of the instruction factor is not significantly different from the motivation of learning outcomes. Whether STEM enactment is done in a short or over a long period, student motivation is equally effective. The same conditions are shown in other factors such as approach or learning model and learning orientation. Furthermore, this condition indicates that whether there are other approaches involved in STEM enactment, and whether it is culture centric or universal oriented, STEM enactment will provide relatively the equivalent effectiveness, especially in higher-order thinking skills and student motivation. That is, higher-order thinking skills and motivation are very closely tied to its STEM enactment, not from the supporting factors. This reason is reinforced by the opinion of Chiang and Lee ( 2016 ) and Ugras ( 2018 ), which states that STEM lessons have a robust character to increase learning motivation and higher-order thinking skills of students.

Conclusion and practical implications

The results of this study indicate a propitious effect of implementing STEM education on students’ learning outcomes in Asia. The effect is evident in the students’ learning achievement, higher-order thinking skills, and motivation. We have also concluded that STEM education in Asia leads to a higher effect on students’ higher-order thinking skills, students’ learning achievement, and finally, motivation. Furthermore, STEM education constitutes the most promising teaching and learning innovation, especially to prepare students honing higher-order thinking skills as well as to attract students’ interest in learning, which is crucial in adapting to the competitive era.

Likewise, based on the results of this study, when implementing STEM teaching and learning within a classroom, several factors must be considered; first, teachers may combine STEM lessons with any teaching approach or learning model. For instance, the teachers can combine STEM teaching with the 6E learning model or project-based learning approach. The combination would give a strong direction for a teacher in realizing the lesson goal. Another suggestion is to involve the local culture in STEM lessons. Such involvement is crucial to academic performance and essential to culturally responsive pedagogy. Local culture can be in the form of the main lesson topics, enrichment material, the way of teaching and learning process, or even the use of localized languages and properties. Lastly, when applying STEM lessons, calculating the amount of time needed, then utilizing a sufficient amount of time toward application is fundamental. The study suggests more than 2 h, spread over two or more class periods, will assist students’ academic learning achievement and higher-order thinking skills. Indeed, these three factors are significant in maximizing STEM effectiveness in Asian student learning outcomes.

While the authors strongly recommend educators, and researchers, apply STEM education as a regular part of learning in Asian countries, a concern is that this study only involves 54 selected studies. We believe there are still other studies that are also related to STEM education and the effectiveness of students’ learning outcomes that were not identified. These limitations can be caused by several things, such as the language used in the title and abstracts written in languages other than English. Another limitation is that this study is more focused on the meta-analysis method that evaluates quantitative research, so we cannot ascertain whether the learning outcome obtained so far has anything to do with teacher attitudes and knowledge of STEM education or not. Also, concerning to calculation of effect size on the potential moderator variables, this current research is still a limited number of studies. A power analysis indicated that the sample size showed relatively weak results to obtain significant and substantial effects for the targeted variables. A larger number of studies are needed to verify result analysis as well as to continue future research. Nevertheless, we believe this research is a comprehensive, valid, and reliable starting point in providing up-to-date information about the conditions of STEM enactment in Asia.

Potential future research based on the results, discussion, and limitations of this study includes investigating Asian teachers’ perceptions (based on their philosophy and belief) and current knowledge concerning STEM education as well as how to apply the approach in different fields. This study serves as an inspiration for researchers to develop or modify STEM lessons, originating from western countries, into diversified STEM types and variances that comply with the cultural background and geographical conditions of each country. Moreover, an attempt to develop, implement, or modify STEM-related curriculum is also a promising future research opportunity.

Availability of data and materials

Not applicable.

Abbreviations

Higher-order thinking skills

Science, technology, engineering, mathematics

STEM-project-based learning

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Acknowledgements

The authors would like to express the gratefulness to Terrence from the Science Education Center, NTNU, who have helped in the English editing process. We also would like to say thank you, for having received funding from the Ph.D. Degree Training of the 4 in 1 project of University of Jember, Ministry of Research Technology and Higher Education Indonesia, and Islamic Development Bank (IsDB).

This research is supported in part by the Ministry of Science and Technology (MOST), Taiwan, R.O.C., under the grant number MOST 106-2511-S-003-050-MY3, “STEM for 2TV (science, technology, engineering, and mathematics for Taiwan, Thailand, and Vietnam): A Joint Adventure in Science Education Research and Practice; The “Institute for Research Excellence in Learning Sciences” of National Taiwan Normal University (NTNU) from the Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan; and National Taiwan Normal University Subsidy for Talent Promotion Program.

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All authors contributed to the paper. Data curation, B-W; formal analysis, B-W; funding acquisition, CY-C; investigation, B-W; methodology, B-W, PL-L, and CY-C; project administration, CY-C; resources, CY-C; supervision, CY-C; validation, B-W and PL-L; and writing—original draft, B-W. Finally, CY-C, acted as a corresponding author. The authors read and approved the final manuscript.

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Wahono, B., Lin, PL. & Chang, CY. Evidence of STEM enactment effectiveness in Asian student learning outcomes. IJ STEM Ed 7 , 36 (2020). https://doi.org/10.1186/s40594-020-00236-1

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DOI : https://doi.org/10.1186/s40594-020-00236-1

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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.

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STEM as the most preferred strand of Senior High School Student's

2020, STEM as the most preferred strand of Senior High School Student's

Related Papers

Kieran Bentley

Participatory Educational Research

Danilo V . Rogayan Jr. , Clarisse Yimyr De Guzman

This qualitative descriptive research explored the perspectives of STEM (science, technology, engineering, and mathematics) senior high school students in a public secondary school in Zambales, Philippines on their reasons why they enrolled in STEM and their intent to pursue relevant career. A total of 20 Grade 12 students were purposively selected as participants of the research. The participants were interviewed using a validated structured interview guide. The recorded interviews were individually transcribed to arrive at an extended text. The extended texts were reviewed to generate themes and significant statements. The paper found out that senior high school students are generally interested in the field related to biology. The alignment to the preferred course in college is the primary reason of the participants for enrolling in STEM. Almost all the students wanted to pursue STEM-related careers after their university graduation. Further, personal aspiration is the main reason for the participants to pursue STEM-related professions. The study recommends that senior high schools may design various activities during the career week. These activities may include possible career paths in STEM-related courses, students' career and motivation, and their career aptitude. Teachers may also infuse innovative pedagogies for better STEM instruction. For the students to have more interest in science, it is recommended that STEM teachers undergo retooling or pursue advanced studies. Senior high schools may conduct career guidance seminars for the students to guide them on what strands they should take. The Department of Education (DepEd) may support the implementation of different programs regarding students’ career preparation. This program will help the students to be more aware on what career path they wanted to pursue, and to avoid pressures from peers. Schools may advocate a collaborative, authentic and goal-oriented learning environment with respect to the demand of Industrial Revolution 4.0.

Clifford Anderson

This study uses data collected at two National Summer Transportation Institute (NSTI) programs in Connecticut and Mississippi to investigate high school students’ perceptions and preferences about education in science, technology, engineering and mathematics (STEM). Family background has a significant impact on a high school student's interest in STEM, as shown during the student recruitment stage and by the analysis of the students' college education plans prepared upon graduation from the two NSTI programs. The building exercise and competition instrument is the most effective among the few examined, while passive learning is not what young people prefer when briefly introduced in the two NSTI programs.

STEM is a curriculum which is based on the idea of education the students in four specific disciplines -science, technology, engineering and mathematics, in an approach which it is based on real-life applications.

Eurasia journal of mathematics, science and technology education

Hersh C. Waxman

This study was grounded in the social cognitive career theoretical framework (Lent, Brown, & Hackett, 1994). The purpose of this four-year longitudinal study was to examine the factors that may have contributed to students’ motivation to develop STEM interest during secondary school years. The participants in our study were 9th- 11th grade high school students from a large K-12 college preparatory charter school system, Harmony Public Schools (HPS) in Texas. We utilized descriptive statistics and logistic regression analyses to carry out the study. The results revealed that three-year survey takers’ STEM major interest seemed to decrease steadily each year. Although there was a significant gender gap between males and females in STEM selection in 9th and 10th grade, this difference was not significant at the end of 11th grade. White and Asian students were significantly more likely to be interested in STEM careers. We also found that students who were most likely to choose a STEM ma...

Steve Alsop

Paul Canlas

Canadian Public Policy

Mitchell Steffler

Zahra Hazari

Alana Unfried , Latricia Townsend

The national economy is in need of more engineers and skilled workers in science, technology, and mathematics (STEM) fields who also possess competencies in critical-thinking, communication, and collaboration – also known as 21st century skills. In response to this need, educational organizations across the country are implementing innovative STEM education programs designed in part to increase student attitudes toward STEM subjects and careers. This paper describes how a team of researchers at The Friday Institute for Educational Innovation at North Carolina State University developed the Upper Elementary School and Middle/High School Student Attitudes toward STEM (S-STEM) Surveys to measure those attitudes. The surveys each consist of four, validated constructs which use Likert-scale items to measure student attitudes toward science, mathematics, engineering and technology, 21st century skills. The surveys also contain a comprehensive section measuring student interest in STEM car...

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Qualitative research in STEM : studies of equity, access, and innovation

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Contents Introduction Sherry Marx
*"I am an innovator:" Quahn's Counter-narrative of Becoming in STEM
Angela Calabrese Barton, Myunghwan Shin, and LaQuahn Johnson
*"I come because I make toy.": Examining Nodes of Criticality in an Afterschool Science & Engineering (SE) Club with Refugee Youth
Edna Tan and Beverly Faircloth
* Sociocultural Analysis of Engineering Design: Latino High School Students' Funds of Knowledge and Implications for Culturally Responsive Engineering Education
Joel Alejandro Mejia
* Bruised But Not Broken: African American Women Persistence in Engineering Degree Programs in Spite of Stereotype Threat
Sherry Marx
* Examining Academic Integrity in the Postmodern: Undergraduates' Use of Solutions to Complete Textbook-based Engineering Coursework
Angela Minichiello
* Engineering Dropouts: A Qualitative Examination of Why Undergraduates Leave Engineering
Matthew Meyer and Sherry Marx
* nitacimowinis: A research story in Indigenous Science Education
* From Ambivalences toward Self-Efficacy: Bilingual Teacher Candidates' Shifting Sense of Knowing as Conocimiento with STEM
Anita Bright and G. Sue Kasun
* Examining the Non-Rational in Science Classrooms: Girls, Sustainability, and Science Education
Kim Haverkos
* Seven Types of Subitizing Activity Characterizing Young Children's Mental Activity
Beth L. MacDonald and Jesse L. M. Wilkins
* Orienting Students to One Another and to the Mathematics During Discussions
Elham Kazemi and Adrian Cunard List of Contributors Index.
(source: Nielsen Book Data)

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STEM STRAND RESEARCH TITLES
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(DOC) BASIS OF GRADE 12 STUDENTS ON CHOOSING THE ACADEMIC STRAND STEM A
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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.
200+ 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.
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.
Best 151+ Quantitative Research Topics for STEM Students
Chemistry. 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.
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.
189+ Innovative Qualitative Research Topics for STEM Students
Theory: Building or refining theories. Innovation: Finding research gaps. Collaboration: Enhancing findings through teamwork. Impact: Influencing policy and practice. These points highlight the key challenges and opportunities in STEM qualitative research. Must Read: 79+ Best Research Topics in Psychology for College Students.
10 Catchy Research Title For Stem Students
10 Catchy Research Title For Stem Students. 10 Catchy Research Title For. Stem. Students. : Harnessing Energy at the Molecular Scale" - Nanotech's energy revolution. Colonization: Engineering Challenges and Solutions" - STEM for interplanetary life. Computing: Unlocking Unprecedented Computational Power" - Quantum leaps in STEM.
11 STEM Research Topics for High School Students
Scholar Launch has compiled a list of 11 compelling research ideas tailored for STEM 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 ...
STEM Research Topics: 200+ Great Choices
July 17, 2024. 10 minutes. Table of Contents. STEM stands for Science, Technology, Engineering, and Math. It is essential for learning and discovery, helping us understand the world, solve problems, and think critically. STEM research goes beyond classroom learning, allowing us to explore specific areas in greater detail.
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 ...
Research Titles for STEM Strand Student
Here are some Research Titles and Topics for S.T.E.M. (STEM) Strand Students. Please take note that some of these titles are subject for revision if your tea...
Home
Overview. The Journal for STEM Education Research is an interdisciplinary research journal that aims to promote STEM education as a distinct field. Offers a platform for interdisciplinary research on a broad spectrum of topics in STEM education. Publishes integrative reviews and syntheses of literature relevant to STEM education and research.
Q: Can you give a research title for the STEM strand?
3 Basic tips on writing a good research paper title. How to write an effective title and abstract and choose appropriate keywords. One tip we can give right away is that you should first have a working (rough) title when you start the paper and then refine/finalize it once you've completed the paper (or the first draft). Hope that helps.
Stem Strand in The Philippines: an Analysis
In this study, a descriptive research design was used in order to describe and analyze gathered data regarding the trends in the enrolment ... year. Also, the STEM strand is 19,366 higher than the enrollment rate of ABM, with 416,345 enrollees. For the year 2019-2020, the . SJIF Impact Factor (2024): 8.675| ISI I.F. Value: 1.241 ...
Pursuing STEM Careers: Perspectives of Senior High School Students
Abstract and Figures. This qualitative descriptive research explored the perspectives of STEM (science, technology, engineering, and mathematics) senior high school students in a public secondary ...
Research and trends in STEM education: a systematic analysis of
Taking publicly funded projects in STEM education as a special lens, we aimed to learn about research and trends in STEM education. We identified a total of 127 projects funded by the Institute of Education Sciences (IES) of the US Department of Education from 2003 to 2019. Both the number of funded projects in STEM education and their funding amounts were high, although there were ...
Evidence of STEM enactment effectiveness in Asian student learning
This study used a systematic review and meta-analysis as a method to investigate whether STEM enactment in Asia effectively enhances students' learning outcomes. Verifiable examples of science, technology, engineering, and mathematics (STEM) education, effectively being applied in Asia, are presented in this study. The study involved 4768 students from 54 studies. Learning outcomes focused ...
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 ...
PDF The Effect of Stem Education on Academic Performance: A Meta-Analysis Study
STEM education is applied to raise individuals having 21st-century skills based on the integration of science, technology, engineering, and mathematics. This paper aims to present the overall effect of STEM education on students' academic achievement by analyzing 64 research findings obtained from 56 quantitative studies published
(PDF) The effectiveness of science, technology, engineering and
Learning with the STEM approach integrates science, technology, engineering, and mathematics learning to help 21st century skills by focusing on solving real problems related to everyday life.
STEM as the most preferred strand of Senior High School Student's
AMA COLLEGES SAN FERNANDO LA UNION Senior High School Department S.Y 2016-2017 STEM as the most preferred strand of Senior High School Student's Jacel Beth Suero Christian Kyle Fabro THESIS ABSTRACT Title: "STEM as the most preferred strand of Grade 11 student's" Course: Science and Technology, Engineering and Mathematics - STEM School: AMA COLLEGES This study is about students who ...
Qualitative research in STEM : studies of equity, access, and
Publisher's summary. Qualitative Research in STEM examines the groundbreaking potential of qualitative research methods to address issues of social justice, equity, and sustainability in STEM. A collection of empirical studies conducted by prominent STEM researchers, this book examines the experiences and challenges faced by traditionally ...
(PDF) Challenges in STEM Learning: A Case of Filipino ...
Vol.7, No. 2, 2021, p. 232-244 p-ISSN 2477-1422 e-ISSN 2477-2038. 232. Challenges in STEM Learning: A Case of Filipino High School Students. (Received 8 May 2021; Revised 30 November 2021 ...

55 Brilliant Research Topics For STEM Students

List of Research Topics For STEM Students

Final Words About Research Topics For STEM Students

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200 Quantitative Research Title for Stem Students

Biology and Life Sciences

Mathematics

Computer Science

Engineering

Environmental Science

Astronomy and Space Sciences

Health Sciences

Materials Science

Earth Sciences

Social Sciences and Economics

Robotics and Artificial Intelligence

Energy and Sustainability

Neuroscience and Psychology

Mechanical Engineering

Biomedical Engineering

Civil and Environmental Engineering

Chemical Engineering

Electrical and Electronic Engineering

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Best 151+ Quantitative Research Topics for STEM Students

What is Quantitative Research in STEM?

Importance of Quantitative Research Topics for STEM Students

1. Empirical Evidence

2. Data-Driven Decision-Making

3. Innovation

4. Problem Solving

5. Interdisciplinary Applications

Quantitative Research Topics for STEM Students

Biology and Life Sciences

Engineering

Environmental Science

Computer Science

Mathematics

Earth Sciences

Health Sciences and Medicine

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189+ Good Quantitative Research Topics For STEM Students

What Is Quantitative Research

How To Choose Quantitative Research Topics For STEM

Step 1:- Identify Your Interests and Passions

Step 2:- Review Coursework and Textbooks

Step 3:- Consult with Professors and Advisors

Step 4:- Read Recent Literature

Step 5:- Narrow Down Your Focus

Step 6:- Consider Resources and Access

Step 7:- Think About Practicality

Step 8:- Define Your Research Question

Step 9:- Conduct a Literature Review

Step 10:- Consider the Impact

Step 11:- Brainstorm Research Methods

Step 12:- Seek Feedback

Step 13:- Assess Ethical Considerations

Step 14:- Finalize Your Research Topic

Step 15:- Stay Open to Adjustments

Quantitative Research Topics In Physics and Astronomy

Quantitative Research Topics In Biology and Life Sciences

Engineering and Technology Quantitative Research Topics

Quantitative Research Topics In Mathematics and Statistics

Experimental Quantitative Research Topics In Science and Earth Sciences

Chemistry and Materials Science Quantitative Research Topics

Computer Science and Information Technology Topics

Good Quantitative Research Topics Students In Medicine and Healthcare

Agriculture and Food Sciences Topics

Social Sciences with Quantitative Approaches

Environmental Engineering Quantitative Research Topics

Quantitative Research Topics Robotics and Automation

Quantitative Research Topics Materials Engineering

Nuclear Engineering Quantitative Research Topics

Quantitative Research Topics In Biomedical Engineering

Good Quantitative Research Topics Chemical Engineering

Best Quantitative Research Topics In Renewable Energy

Brilliant Quantitative Research Topics In Astronomy and Space Sciences

Quantitative Research Topics In Psychology and Cognitive Science

Geology and Geological Engineering Quantitative Research Topics