research problems for stem students

161+ Exciting Qualitative Research Topics For STEM Students

Are you doing Qualitative research? Looking for the best qualitative research topics for stem students? It is a most interesting and good field for research. Qualitative research allows STEM (Science, Technology, Engineering, and Mathematics) students to delve deeper into complex issues, explore human behavior, and understand the intricacies of the world around them.

In this article, we’ll provide you with an extensive list of 161+ qualitative research topics tailored to STEM students. We’ll also explore how to find and choose good qualitative research topics, and why these topics are particularly beneficial for students, including those in high school.

Also Like To Read: 171+ Brilliant Quantitative Research Topics For STEM Students

Table of Contents

What Are Qualitative Research Topics for STEM Students

Qualitative research topics for stem students are questions or issues that necessitate an in-depth exploration of people’s experiences, beliefs, and behaviors. STEM students can use this approach to investigate societal impacts, ethical dilemmas, and user experiences related to scientific advancements and innovations.

Unlike quantitative research, which focuses on numerical data and statistical analysis, qualitative research delves into the ‘whys’ and ‘hows’ of a particular phenomenon.

How to Find and Choose Good Qualitative Research Topics

Selecting qualitative research topics for stem students is a crucial step in the research process. Here are some tips to help you find and choose a suitable topic:

Passion and Interest: Start by considering your personal interests and passions. What topics within STEM excite you? Research becomes more engaging when you’re genuinely interested in the subject.
Relevance: Choose qualitative research topics for stem students. Look for gaps in the existing knowledge or unanswered questions.
Literature Review: Conduct a thorough literature review to identify the latest trends and areas where qualitative research is lacking. This can guide you in selecting a topic that contributes to the field.
Feasibility: Ensure that your chosen topic is feasible within the resources and time constraints available to you. Some research topics may require extensive resources and funding.
Ethical Considerations: Be aware of ethical concerns related to your qualitative research topics for stem students, especially when dealing with human subjects or sensitive issues.

Here are the most exciting and very interesting Qualitative Research Topics For STEM Students, high school students, nursing students, college students, etc.

Biology Qualitative Research Topics

Impact of Ecosystem Restoration on Biodiversity
Ethical Considerations in Human Gene Editing
Public Perceptions of Biotechnology in Agriculture
Coping Mechanisms and Stress Responses in Marine Biologists
Cultural Perspectives on Traditional Herbal Medicine
Community Attitudes Toward Wildlife Conservation Efforts
Ethical Issues in Animal Testing and Research
Indigenous Knowledge and Ethnobotany
Psychological Well-being of Conservation Biologists
Attitudes Toward Endangered Species Protection

Chemistry Qualitative Research Topics For STEM Students

Adoption of Green Chemistry Practices in the Pharmaceutical Industry
Public Perception of Chemical Safety in Household Products
Strategies for Improving Chemistry Education
Art Conservation and Chemical Analysis
Consumer Attitudes Toward Organic Chemistry in Everyday Life
Ethical Considerations in Chemical Waste Disposal
The Role of Chemistry in Sustainable Agriculture
Perceptions of Nanomaterials and Their Applications
Chemistry-Related Career Aspirations in High School Students
Cultural Beliefs and Traditional Chemical Practices

Physics Qualitative Research Topics

Gender Bias in Physics Education and Career Progression
Philosophical Implications of Quantum Mechanics
Public Understanding of Renewable Energy Technologies
Influence of Science Fiction on Scientific Research
Perceptions of Dark Matter and Dark Energy in the Universe
Student Experiences in High School Physics Classes
Physics Outreach Programs and Their Impact on Communities
Cultural Variations in the Perception of Time and Space
Role of Physics in Environmental Conservation
Public Engagement with Science Through Astronomy Events

Engineering Qualitative Research Topics For STEM Students

Ethics in Artificial Intelligence and Robotics
Human-Centered Design in Engineering
Innovation and Sustainability in Civil Engineering
Public Perception of Self-Driving Cars
Engineering Solutions for Climate Change Mitigation
Experiences of Women in Male-Dominated Engineering Fields
Role of Engineers in Disaster Response and Recovery
Ethical Considerations in Technology Patents
Perceptions of Engineering Education and Career Prospects
Students Views on the Role of Engineers in Society

Computer Science Qualitative Research Topics

Gender Diversity in Tech Companies
Ethical Implications of AI-Powered Decision-Making
User Experience and Interface Design
Cybersecurity Awareness and Behaviors
Digital Privacy Concerns and Practices
Social Media Use and Mental Health in College Students
Gaming Culture and its Impact on Social Interactions
Student Attitudes Toward Coding and Programming
Online Learning Platforms and Student Satisfaction
Perceptions of Artificial Intelligence in Everyday Life

Mathematics Qualitative Research Topics For STEM Students

Gender Stereotypes in Mathematics Education
Cultural Variations in Problem-Solving Approaches
Perception of Math in Everyday Life
Math Anxiety and Coping Mechanisms
Historical Development of Mathematical Concepts
Attitudes Toward Mathematics Among Elementary School Students
Role of Mathematics in Solving Real-World Problems
Homeschooling Approaches to Teaching Mathematics
Effectiveness of Math Tutoring Programs
Math-Related Stereotypes in Society

Environmental Science Qualitative Research Topics

Local Communities’ Responses to Climate Change
Public Understanding of Conservation Practices
Sustainable Agriculture and Farmer Perspectives
Environmental Education and Behavior Change
Indigenous Ecological Knowledge and Biodiversity Conservation
Conservation Awareness and Behavior of Tourists
Climate Change Perceptions Among Youth
Perceptions of Water Scarcity and Resource Management
Environmental Activism and Youth Engagement
Community Responses to Environmental Disasters

Geology and Earth Sciences Qualitative Research Topics For STEM Students

Geologists’ Risk Perception and Decision-Making
Volcano Hazard Preparedness in At-Risk Communities
Public Attitudes Toward Geological Hazards
Environmental Consequences of Extractive Industries
Perceptions of Geological Time and Deep Earth Processes
Use of Geospatial Technology in Environmental Research
Role of Geology in Disaster Preparedness and Response
Geological Factors Influencing Urban Planning
Community Engagement in Geoscience Education
Climate Change Communication and Public Understanding

Astronomy and Space Science Qualitative Research Topics

The Role of Science Communication in Astronomy Education
Perceptions of Space Exploration and Colonization
UFO and Extraterrestrial Life Beliefs
Public Understanding of Black Holes and Neutron Stars
Space Tourism and Future Space Travel
Impact of Space Science Outreach Programs on Student Interest
Cultural Beliefs and Rituals Related to Celestial Events
Space Science in Indigenous Knowledge Systems
Public Engagement with Astronomical Phenomena
Space Exploration in Science Fiction and Popular Culture

Medicine and Health Sciences Qualitative Research Topics

Patient-Physician Communication and Trust
Ethical Considerations in Human Cloning and Genetic Modification
Public Attitudes Toward Vaccination
Coping Strategies for Healthcare Workers in Pandemics
Cultural Beliefs and Health Practices
Health Disparities Among Underserved Communities
Medical Decision-Making and Informed Consent
Mental Health Stigma and Help-Seeking Behavior
Wellness Practices and Health-Related Beliefs
Perceptions of Alternative and Complementary Medicine

Psychology Qualitative Research Topics

Perceptions of Body Image in Different Cultures
Workplace Stress and Coping Mechanisms
LGBTQ+ Youth Experiences and Well-Being
Cross-Cultural Differences in Parenting Styles and Outcomes
Perceptions of Psychotherapy and Counseling
Attitudes Toward Medication for Mental Health Conditions
Psychological Well-being of Older Adults
Role of Cultural and Social Factors in Psychological Well-being
Technology Use and Its Impact on Mental Health

Social Sciences Qualitative Research Topics

Political Polarization and Online Echo Chambers
Immigration and Acculturation Experiences
Educational Inequality and School Policy
Youth Engagement in Environmental Activism
Identity and Social Media in the Digital Age
Social Media and Its Influence on Political Beliefs
Family Dynamics and Conflict Resolution
Social Support and Coping Strategies in College Students
Perceptions of Cyberbullying Among Adolescents
Impact of Social Movements on Societal Change

Interesting Sociology Qualitative Research Topics For STEM Students

Perceptions of Racial Inequality and Discrimination
Aging and Quality of Life in Elderly Populations
Gender Roles and Expectations in Relationships
Online Communities and Social Support
Cultural Practices and Beliefs Related to Marriage
Family Dynamics and Coping Mechanisms
Perceptions of Community Safety and Policing
Attitudes Toward Social Welfare Programs
Influence of Media on Perceptions of Social Issues
Youth Perspectives on Education and Career Aspirations

Anthropology Qualitative Research Topics

Traditional Knowledge and Biodiversity Conservation
Cultural Variation in Parenting Practices
Indigenous Language Revitalization Efforts
Social Impacts of Tourism on Indigenous Communities
Rituals and Ceremonies in Different Cultural Contexts
Food and Identity in Cultural Practices
Traditional Healing and Healthcare Practices
Indigenous Rights and Land Conservation
Ethnographic Studies of Marginalized Communities
Cultural Practices Surrounding Death and Mourning

Economics and Business Qualitative Research Topics

Small Business Resilience in Times of Crisis
Workplace Diversity and Inclusion
Corporate Social Responsibility Perceptions
International Trade and Cultural Perceptions
Consumer Behavior and Decision-Making in E-Commerce
Business Ethics and Ethical Decision-Making
Innovation and Entrepreneurship in Startups
Perceptions of Economic Inequality and Wealth Distribution
Impact of Economic Policies on Communities
Role of Economic Education in Financial Literacy

Good Education Qualitative Research Topics For STEM Students

Homeschooling Experiences and Outcomes
Teacher Burnout and Coping Strategies
Inclusive Education and Special Needs Integration
Student Perspectives on Online Learning
High-Stakes Testing and Its Impact on Students
Multilingual Education and Bilingualism
Perceptions of Educational Technology in Classrooms
School Climate and Student Well-being
Teacher-Student Relationships and Their Effects on Learning
Cultural Diversity in Education and Inclusion

Environmental Engineering Qualitative Research Topics

Sustainable Transportation and Community Preferences
Ethical Considerations in Waste Reduction and Recycling
Public Attitudes Toward Renewable Energy Projects
Environmental Impact Assessment and Community Engagement
Sustainable Urban Planning and Neighborhood Perceptions
Water Quality and Conservation Practices in Residential Areas
Green Building Practices and User Experiences
Community Resilience in the Face of Climate Change
Role of Environmental Engineers in Disaster Preparedness

Why Qualitative Research Topics Are Good for STEM Students

Deeper Understanding: Qualitative research encourages STEM students to explore complex issues from a human perspective. This deepens their understanding of the broader impact of scientific discoveries and technological advancements.
Critical Thinking: Qualitative research fosters critical thinking skills by requiring students to analyze and interpret data, consider diverse viewpoints, and draw nuanced conclusions.
Real-World Relevance: Many qualitative research topics have real-world applications. Students can address problems, inform policy, and contribute to society by investigating issues that matter.
Interdisciplinary Learning: Qualitative research often transcends traditional STEM boundaries, allowing students to draw on insights from psychology, sociology, anthropology, and other fields.
Preparation for Future Careers: Qualitative research skills are valuable in various STEM careers, as they enable students to communicate complex ideas and understand the human and social aspects of their work.

Qualitative Research Topics for High School STEM Students

High school STEM students can benefit from qualitative research by honing their critical thinking and problem-solving skills. Here are some qualitative research topics suitable for high school students:

Perceptions of STEM Education: Investigate students’ and teachers’ perceptions of STEM education and its effectiveness.
Environmental Awareness: Examine the factors influencing high school students’ environmental awareness and eco-friendly behaviors.
Digital Learning in the Classroom: Explore the impact of technology on learning experiences and student engagement.
STEM Gender Gap: Analyze the reasons behind the gender gap in STEM fields and potential strategies for closing it.
Science Communication: Study how high school students perceive and engage with popular science communication channels, like YouTube and podcasts.
Impact of Extracurricular STEM Activities: Investigate how participation in STEM clubs and competitions influences students’ interest and performance in science and technology.

In essence, these are the best qualitative research topics for STEM students in the Philippines and are usable for other countries students too. Qualitative research topics offer STEM students a unique opportunity to explore the multifaceted aspects of their fields, develop essential skills, and contribute to meaningful discoveries. With the right topic selection, a strong research design, and ethical considerations, STEM students can easily get the best knowledge on exciting qualitative research that benefits both their career growth. So, choose a topic that resonates with your interests and get best job in your interest field.

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+ Experimental Quantitative Research Topics For STEM Students In 2023

STEM means Science, Technology, Engineering, and Math, which is not the only stuff we learn in school. It is like a treasure chest of skills that help students become great problem solvers, ready to tackle the real world’s challenges.

In this blog, we are here to explore the world of Research Topics for STEM Students. We will break down what STEM really means and why it is so important for students. In addition, we will give you the lowdown on how to pick a fascinating research topic. We will explain a list of 200+ Experimental Quantitative Research Topics For STEM Students.

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

What Is STEM?

Table of Contents

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

Why STEM Research Is Important?

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

STEM research leads to new discoveries and solutions.
It helps find cures for diseases.
STEM technology makes life easier.
Engineers build things that improve our lives.
Mathematics helps us understand and solve complex problems.

How to Choose a Topic for STEM Research Paper

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

Step 1: Identify Your Interests

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

Step 2: Research Existing Topics

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

Step 3: Consider Real-World Problems

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

Step 4: Talk to Teachers and Mentors

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

Step 5: Narrow Down Your Topic

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

Here we will discuss 200+ Experimental Quantitative Research Topics For STEM Students:

Qualitative Research Topics for STEM Students:

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

Exploring the experiences of female STEM students in overcoming gender bias in academia.
Understanding the perceptions of teachers regarding the integration of technology in STEM education.
Investigating the motivations and challenges of STEM educators in underprivileged schools.
Exploring the attitudes and beliefs of parents towards STEM education for their children.
Analyzing the impact of collaborative learning on student engagement in STEM subjects.
Investigating the experiences of STEM professionals in bridging the gap between academia and industry.
Understanding the cultural factors influencing STEM career choices among minority students.
Exploring the role of mentorship in the career development of STEM graduates.
Analyzing the perceptions of students towards the ethics of emerging STEM technologies like AI and CRISPR.
Investigating the emotional well-being and stress levels of STEM students during their academic journey.

Easy Experimental Research Topics for STEM Students:

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

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

Research Topics for STEM Students in the Philippines:

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

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

Frontend Project Ideas
Business Intelligence Projects For Beginners

Good Research Topics for STEM Students:

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

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

Unique Research Topics for STEM Students:

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

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

Experimental Research Topics for STEM Students in the Philippines

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

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

Capstone Research Topics for STEM Students in the Philippines:

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

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

Experimental Quantitative Research Topics for STEM Students:

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

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

Descriptive Research Topics for STEM Students

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

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

Research Topics for STEM Students in the Pandemic:

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

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

Research Topics for STEM Students Middle School

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

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

Technology Research Topics for STEM Students

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

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

Scientific Research Topics for STEM Students

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

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

Interesting Research Topics for STEM Students:

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

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

Practical Research Topics for STEM Students

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

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

Experimental Research Topics for STEM Students About Plants

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

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

Qualitative Research Topics for STEM Students in the Philippines

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

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

Science Research Topics for STEM Students

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

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

Correlational Research Topics for STEM Students

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

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

Quantitative Research Topics for STEM Students in the Philippines

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

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

Things That Must Keep In Mind While Writing Quantitative Research Title

Here are few things that must be keep in mind while writing quantitative research tile:

1. Be Clear and Precise

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

2. Use Important Words

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

3. Avoid Confusing Words

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

4. Show Your Research Approach

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

5. Match Your Title with Your Research Questions

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

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

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February 25, 2021 | Kevin Noonan - College of Agriculture, Health, and Natural Resources

Researchers study challenges underrepresented STEM students face during COVID-19

This article originally appeared on CAHNR Newsroom. By Kim Colavito Markesich. In July 2020, Professor Sherry Pagoto and Associate Professor Molly Waring of the Department of Allied Health Sciences in the College of Agriculture, Health and Natural Resources were awarded a National Science Foundation grant to study the effects of the COVID-19 pandemic on underrepresented […]

Molly Waring

This article originally appeared on CAHNR Newsroom.

By Kim Colavito Markesich .

In July 2020, Professor Sherry Pagoto and Associate Professor Molly Waring of the Department of Allied Health Sciences in the College of Agriculture, Health and Natural Resources were awarded a National Science Foundation grant to study the effects of the COVID-19 pandemic on underrepresented STEM (science, technology, engineering and mathematics) students. This pandemic is estimated to affect at least two cohorts of STEM students in an academic field that is already considered rigorous.

“We were concerned about the impact of COVID on STEM students, and we wanted to investigate what those impacts were and if there were differential based factors such as gender, race and ethnicity or socioeconomic status,” Waring says. “We wanted to understand where there might be negative impacts that are affecting certain groups of students more than others, with the idea that we can then try to counteract some of these negative impacts. Science works best when all voices are represented and we want to retain our current cohort of diverse students.”

In collaboration with Nate Brown of Pennsylvania State University and with assistance from members in the Math Alliance , a national organization of faculty in mathematics and statistical majors, the team recruited fifty-nine students from across the United States to participate in focus groups during summer 2020. The students were equally split male and female, with half the students meeting criteria for low socioeconomic status and equal representation across racial and ethnic groups.

For students majoring in STEM fields, remote learning can be particularly difficult as learning is enhanced with hands-on or laboratory experiences. Additionally, many students that rely on employment to support their education have been affected by job losses during the pandemic. There have also been fewer opportunities for research experiences and internships as many labs were forced to shut down.

In the focus groups, some students expressed concern that they would not be adequately prepared for subsequent semesters in STEM courses, as not all universities were prepared for remote learning and not all students were able to learn remotely.

“Moving forward, we encourage universities to develop a detailed plan in case of another emergency that would require them to switch to remote instruction,” Waring says. “We need effective strategies for remote learning and ways to connect to our students. And there are also some positives that we have learned from this pandemic, such as having faculty be more flexible. I hope we can retain some of these lessons and support those bright students of all backgrounds.”

Students were asked which instructor strategies, tools and technologies were most helpful. Hybrid learning which included both synchronous and asynchronous classes was preferred, with many students preferring live remote lectures that were also recorded and posted, allowing students with interruptions in their home environment to review later. Other tools such as discussion boards, study groups, lecture notes or slides were mentioned as well as communication platforms and streaming/video conferencing platforms.

Ineffective strategies included, increased workload relative to pre-shutdown, prerecorded lectures that did not provide the opportunity to ask questions, lack of a communication strategy, tool or technology, and little guidance on technological strategies, large files that could not be downloaded, tests that didn’t allow students to skip difficult questions and return later, long-form or outdated lecture recordings, poor quality recordings, excessive assignments such as on discussion boards, and vague communication from instructors.

Students were sensitive to feeling that instructors cared about them. Positive instructor behavior included leniency and or flexibility with respect to course policies or assessments such as allotting more time for assignments, as well as instructor responsiveness and accessibility and words of encouragement. Students appreciated instructors checking in with them and one-on-one opportunities.

Some negative experiences included instructors replacing exams with class projects that required more time, online videos that exceeded the time of regular classes, issues with responsiveness or ability to contact instructors. In addition, many students found watching video lectures more difficult than in-class instruction and needed more breaks, rewinding what they didn’t absorb. They had difficulty with focus and not being able to ask questions. Finally, students felt that some instructors were not prepared for emergency remote instruction.

“One thing that has been challenging from the faculty perspective of this is many faculty members had not received training in effective remote learning, especially last spring when many instructors had only a couple weeks’ notice to adapt their courses to be taught remotely,” Waring says. “I certainly understand the students’ perspective of their wide range of experience with remote learning.” Waring also notes the broad range of resources provided by the UConn Center for Excellence in Teaching and Learning (CETL) to support course instructors during the pandemic.

She says, “CETL has provided a wealth of trainings and individual support for faculty looking to increase their teaching effectiveness while connecting with students remotely.”

Students participating in the focus groups also shared their concerns about the fall 2020 semester, including both concerns about returning to campus and about learning remotely from home. The most common concern for students was being infected with COVID-19 and spreading it to family members. They were also worried about noncompliance to COVID guidelines by many students on campus. Additional student concerns included apprehension over instructional quality during remote learning, impacts on social interaction, lack of hands-on experiential learning, and struggles with remote learning such as difficulty focusing, inadequate technology/internet access, and family home environment.

In terms of social interaction with their peers, most students did not find that social media entirely replaced face-to-face contact but was an addition to their overall social experience. The absence of social togetherness has led to a feeling of isolation during the pandemic.

“People have become creative at finding ways to connect during the pandemic,” says Waring. “But many college students are in a life stage where social interaction is about being with your peers and making friends and romantic connections, and the lack of in-person activities has been very hard for many undergraduate students.”

Waring and team developed a survey based on insights provided by the focus groups. Then, in December 2020 and January 2021, their team recruited more than 1,000 undergraduate students from over 100 colleges and universities to complete this survey. While they are currently analyzing these data, Waring shared some of their preliminary findings.

“We expected the pandemic to decrease some students’ sense of belonging in STEM or erode their confidence and motivation to succeed in STEM. While we did see that happening for many students, we were a little surprised that for some students remote learning increased their sense of belonging, confidence and motivation to succeed in STEM. We’re interested in looking at what factors affected these students to help current and future students succeed in STEM.”

“The COVID-19 pandemic has brought many challenges in terms of public health, economics, and education, but I have been really inspired by how faculty, students and universities have risen to the challenge to continue to engage in meaningful intellectual thought and research,” Waring asserts. “I am impressed by this generation of undergraduate students that have persisted through this difficult period and I am looking forward to seeing them take the world by storm and see the good they do throughout their lives and careers.”

The research in this article was supported by a RAPID grant, Proposal no. 2028341, from the National Science Foundation.

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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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Undergraduate Research Experiences for STEM Students: Successes, Challenges, and Opportunities (2017)

Chapter: 9 conclusions and recommendations, 9 conclusions and recommendations.

Practitioners designing or improving undergraduate research experiences (UREs) can build on the experiences of colleagues and learn from the increasingly robust literature about UREs and the considerable body of evidence about how students learn. The questions practitioners ask themselves during the design process should include questions about the goals of the campus, program, faculty, and students. Other factors to consider when designing a URE include the issues raised in the conceptual framework for learning and instruction, the available resources, how the program or experience will be evaluated or studied, and how to design the program from the outset to incorporate these considerations, as well as how to build in opportunities to improve the experience over time in light of new evidence. (Some of these topics are addressed in Chapter 8 .)

Colleges and universities that offer or wish to offer UREs to their students should undertake baseline evaluations of their current offerings and create plans to develop a culture of improvement in which faculty are supported in their efforts to continuously refine UREs based on the evidence currently available and evidence that they and others generate in the future. While much of the evidence to date is descriptive, it forms a body of knowledge that can be used to identify research questions about UREs, both those designed around the apprenticeship model and those designed using the more recent course-based undergraduate research experience (CURE) model. Internships and other avenues by which undergraduates do research provide many of the same sorts of experiences but are not well studied. In any case, it is clear that students value these experiences; that many faculty do as well; and that they contribute to broadening participation in science,

technology, engineering, and mathematics (STEM) education and careers. The findings from the research literature reported in Chapter 4 provide guidance to those designing both opportunities to improve practical and academic skills and opportunities for students to “try out” a professional role of interest.

Little research has been done that provides answers to mechanistic questions about how UREs work. Additional studies are needed to know which features of UREs are most important for positive outcomes with which students and to gain information about other questions of this type. This additional research is needed to better understand and compare different strategies for UREs designed for a diversity of students, mentors, and institutions. Therefore, the committee recommends steps that could increase the quantity and quality of evidence available in the future and makes recommendations for how faculty, departments, and institutions might approach decisions about UREs using currently available information. Multiple detailed recommendations about the kinds of research that might be useful are provided in the research agenda in Chapter 7 .

In addition to the specific research recommended in Chapter 7 , in this chapter the committee provides a series of interrelated conclusions and recommendations related to UREs for the STEM disciplines and intended to highlight the issues of primary importance to administrators, URE program designers, mentors to URE students, funders of UREs, those leading the departments and institutions offering UREs, and those conducting research about UREs. These conclusions and recommendations are based on the expert views of the committee and informed by their review of the available research, the papers commissioned for this report, and input from presenters during committee meetings. Table 9-1 defines categories of these URE “actors,” gives examples of specific roles included in each category, specifies key URE actions for which that category is responsible, and lists the conclusions and recommendations the committee views as most relevant to that actor category.

RESEARCH ON URES

Conclusion 1: The current and emerging landscape of what constitutes UREs is diverse and complex. Students can engage in STEM-based undergraduate research in many different ways, across a variety of settings, and along a continuum that extends and expands upon learning opportunities in other educational settings. The following characteristics define UREs. Due to the variation in the types of UREs, not all experiences include all of the following characteristics in the same way; experiences vary in how much a particular characteristic is emphasized.

TABLE 9-1 Audiences for Committee’s Conclusions and Recommendations

They engage students in research practices including the ability to argue from evidence.
They aim to generate novel information with an emphasis on discovery and innovation or to determine whether recent preliminary results can be replicated.
They focus on significant, relevant problems of interest to STEM researchers and, in some cases, a broader community (e.g., civic engagement).
They emphasize and expect collaboration and teamwork.
They involve iterative refinement of experimental design, experimental questions, or data obtained.
They allow students to master specific research techniques.
They help students engage in reflection about the problems being investigated and the work being undertaken to address those problems.
They require communication of results, either through publication or presentations in various STEM venues.
They are structured and guided by a mentor, with students assuming increasing ownership of some aspects of the project over time.

UREs are generally designed to add value to STEM offerings by promoting an understanding of the ways that knowledge is generated in STEM fields and to extend student learning beyond what happens in the small group work of an inquiry-based course. UREs add value by enabling students to understand and contribute to the research questions that are driving the field for one or more STEM topics or to grapple with design challenges of interest to professionals. They help students understand what it means to be a STEM researcher in a way that would be difficult to convey in a lecture course or even in an inquiry-based learning setting. As participants in a URE, students can learn by engaging in planning, experimentation, evaluation, interpretation, and communication of data and other results in light of what is already known about the question of interest. They can pose relevant questions that can be solved only through investigative or design efforts—individually or in teams—and attempt to answer these questions despite the challenges, setbacks, and ambiguity of the process and the results obtained.

The diversity of UREs reflects the reality that different STEM disciplines operate from varying traditions, expectations, and constraints (e.g., lab safety issues) in providing opportunities for undergraduates to engage in research. In addition, individual institutions and departments have cultures that promote research participation to various degrees and at different stages in students’ academic careers. Some programs emphasize design and problem solving in addition to discovery. UREs in different disciplines can

take many forms (e.g., apprentice-style, course-based, internships, project-based), but the definitional characteristics described above are similar across different STEM fields.

Furthermore, students in today’s university landscape may have opportunities to engage with many different types of UREs throughout their education, including involvement in a formal program (which could include mentoring, tutoring, research, and seminars about research), an apprentice-style URE under the guidance of an individual or team of faculty members, an internship, or enrolling in one or more CUREs or in a consortium- or project-based program.

Conclusion 2: Research on the efficacy of UREs is still in the early stages of development compared with other interventions to improve undergraduate STEM education.

The types of UREs are diverse, and their goals are even more diverse. Questions and methodologies used to investigate the roles and effectiveness of UREs in achieving those goals are similarly diverse.
Most of the studies of UREs to date are descriptive case studies or use correlational designs. Many of these studies report positive outcomes from engagement in a URE.
Only a small number of studies have employed research designs that can support inferences about causation. Most of these studies find evidence for a causal relationship between URE participation and subsequent persistence in STEM. More studies are needed to provide evidence that participation in UREs is a causal factor in a range of desired student outcomes.

Taking the entire body of evidence into account, the committee concludes that the published peer-reviewed literature to date suggests that participation in a URE is beneficial for students .

As discussed in the report’s Introduction (see Chapter 1 ) and in the research agenda (see Chapter 7 ), the committee considered descriptive, causal, and mechanistic questions in our reading of the literature on UREs. Scientific approaches to answering descriptive, causal, and mechanistic questions require deciding what to look for, determining how to examine it, and knowing appropriate ways to score or quantify the effect.

Descriptive questions ask what is happening without making claims as to why it is happening—that is, without making claims as to whether the research experience caused these changes. A descriptive statement about UREs only claims that certain changes occurred during or after the time the students were engaged in undergraduate research. Descriptive studies

cannot determine whether any benefits observed were caused by participation in the URE.

Causal questions seek to discover whether a specific intervention leads to a specific outcome, other things being equal. To address such questions, causal evidence can be generated from a comparison of carefully selected groups that do and do not experience UREs. The groups can be made roughly equivalent by random assignment (ensuring that URE and non-URE groups are the same on average as the sample size increases) or by controlling for an exhaustive set of characteristics and experiences that might render the groups different prior to the URE. Other quasi-experimental strategies can also be used. Simply comparing students who enroll in a URE with students who do not is not adequate for determining causality because there may be selection bias. For example, students already interested in STEM are more likely to seek out such opportunities and more likely to be selected for such programs. Instead the investigator would have to compare future enrollment patterns (or other measures) between closely matched students, some of whom enrolled in a URE and some of whom did not. Controlling for selection bias to enable an inference about causation can pose significant challenges.

Questions of mechanism or of process also can be explored to understand why a causal intervention leads to the observed effect. Perhaps the URE enhances a student’s confidence in her ability to succeed in her chosen field or deepens her commitment to the field by exposing her to the joy of discovery. Through these pathways that act on the participant’s purposive behavior, the URE enhances the likelihood that she persists in STEM. The question for the researcher then becomes what research design would provide support for this hypothesis of mechanism over other candidate explanations for why the URE is a causal factor in STEM persistence.

The committee has examined the literature and finds a rich descriptive foundation for testable hypotheses about the effects of UREs on student outcomes. These studies are encouraging; a few of them have generated evidence that a URE can be a positive causal factor in the progression and persistence of STEM students. The weight of the evidence has been descriptive; it relies primarily on self-reports of short-term gains by students who chose to participate in UREs and does not include direct measures of changes in the students’ knowledge, skills, or other measures of success across comparable groups of students who did and did not participate in UREs.

While acknowledging the scarcity of strong causal evidence on the benefits of UREs, the committee takes seriously the weight of the descriptive evidence. Many of the published studies of UREs show that students who participate report a range of benefits, such as increased understanding of the research process, encouragement to persist in STEM, and support that helps them sustain their identity as researchers and continue with their

plans to enroll in a graduate program in STEM (see Chapter 4 ). These are effective starting points for causal studies.

Conclusion 3: Studies focused on students from historically underrepresented groups indicate that participation in UREs improves their persistence in STEM and helps to validate their disciplinary identity.

Various UREs have been specifically designed to increase the number of historically underrepresented students who go on to become STEM majors and ultimately STEM professionals. While many UREs offer one or more supplemental opportunities to support students’ academic or social success, such as mentoring, tutoring, summer bridge programs, career or graduate school workshops, and research-oriented seminars, those designed for underrepresented students appear to emphasize such features as integral and integrated components of the program. In particular, studies of undergraduate research programs targeting underrepresented minority students have begun to document positive outcomes such as degree completion and persistence in interest in STEM careers ( Byars-Winston et al., 2015 ; Chemers et al., 2011 ; Jones et al., 2010 ; Nagda et al., 1998 ; Schultz et al., 2011 ). Most of these studies collected data on apprentice-style UREs, in which the undergraduate becomes a functioning member of a research group along with the graduate students, postdoctoral fellows, and mentor.

Recommendation 1: Researchers with expertise in education research should conduct well-designed studies in collaboration with URE program directors to improve the evidence base about the processes and effects of UREs. This research should address how the various components of UREs may benefit students. It should also include additional causal evidence for the individual and additive effects of outcomes from student participation in different types of UREs. Not all UREs need be designed to undertake this type of research, but it would be very useful to have some UREs that are designed to facilitate these efforts to improve the evidence base .

As the focus on UREs has grown, so have questions about their implementation. Many articles have been published describing specific UREs (see Chapter 2 ). Large amounts of research have also been undertaken to explore more generally how students learn, and the resulting body of evidence has led to the development and adoption of “active learning” strategies and experiences. If a student in a URE has an opportunity to, for example, analyze new data or to reformulate a hypothesis in light of the student’s analysis, this activity fits into the category that is described as active learning. Surveys of student participants and unpublished evaluations pro-

vide additional information about UREs but do not establish causation or determine the mechanism(s). Consequently, little is currently known about the mechanisms of precisely how UREs work and which aspects of UREs are most powerful. Important components that have been reported include student ownership of the URE project, time to tackle a question iteratively, and opportunities to report and defend one’s conclusions ( Hanauer and Dolan, 2014 ; Thiry et al., 2011 ).

There are many unanswered questions and opportunities for further research into the role and mechanism of UREs. Attention to research design as UREs are planned is important; more carefully designed studies are needed to understand the ways that UREs influence a student’s education and to evaluate the outcomes that have been reported for URE participants. Appropriate studies, which include matched samples or similar controls, would facilitate research on the ways that UREs benefit students, enabling both education researchers and implementers of UREs to determine optimal features for program design and giving the community a more robust understanding of how UREs work.

See the research agenda ( Chapter 7 ) for specific recommendations about research topics and approaches.

Recommendation 2: Funders should provide appropriate resources to support the design, implementation, and analysis of some URE programs that are specifically designed to enable detailed research establishing the effects on participant outcomes and on other variables of interest such as the consequences for mentors or institutions.

Not all UREs need to be the subject of extensive study. In many cases, a straightforward evaluation is adequate to determine whether the URE is meeting its goals. However, to achieve more widespread improvement in both the types and quality of the UREs offered in the future, additional evidence about the possible causal effects and mechanisms of action of UREs needs to be systematically collected and disseminated. This includes a better understanding of the implementation differences for a variety of institutions (e.g., community colleges, primarily undergraduate institutions, research universities) to ensure that the desired outcomes can translate across settings. Increasing the evidence about precisely how UREs work and which aspects of UREs are most powerful will require careful attention to study design during planning for the UREs.

Not all UREs need to be designed to achieve this goal; many can provide opportunities to students by relying on pre-existing knowledge and iterative improvement as that knowledge base grows. However, for the knowledge base to grow, funders must provide resources for some URE designers and social science researchers to undertake thoughtful and well-planned studies

on causal and mechanistic issues. This will maximize the chances for the creation and dissemination of information that can lead to the development of sustainable and effective UREs. These studies can result from a partnership formed as the URE is designed and funded, or evaluators and social scientists could identify promising and/or effective existing programs and then raise funds on their own to support the study of those programs to answer the questions of interest. In deciding upon the UREs that are chosen for these extensive studies, it will be important to consider whether, collectively, they are representative of UREs in general. For example, large and small UREs at large and small schools targeted at both introductory and advanced students and topics should be studied.

CONSTRUCTION OF URES

Conclusion 4: The committee was unable to find evidence that URE designers are taking full advantage of the information available in the education literature on strategies for designing, implementing, and evaluating learning experiences. STEM faculty members do not generally receive training in interpreting or conducting education research. Partnerships between those with expertise in education research and those with expertise in implementing UREs are one way to strengthen the application of evidence on what works in planning and implementing UREs.

As discussed in Chapters 3 and 4 , there is an extensive body of literature on pedagogy and how people learn; helping STEM faculty to access the existing literature and incorporate those concepts as they design UREs could improve student experiences. New studies that specifically focus on UREs may provide more targeted information that could be used to design, implement, sustain, or scale up UREs and facilitate iterative improvements. Information about the features of UREs that elicit particular outcomes or best serve certain populations of students should be considered when implementing a new instantiation of an existing model of a URE or improving upon an existing URE model.

Conclusion 5: Evaluations of UREs are often conducted to inform program providers and funders; however, they may not be accessible to others. While these evaluations are not designed to be research studies and often have small sample sizes, they may contain information that could be useful to those initiating new URE programs and those refining UREs. Increasing access to these evaluations and to the accumulated experience of the program providers may enable URE designers and implementers to build upon knowledge gained from earlier UREs.

As discussed in Chapter 1 , the committee searched for evaluations of URE programs in several different ways but was not able to locate many published evaluations to study. Although some evaluations were found in the literature, the committee could not determine a way to systematically examine the program evaluations that have been prepared. The National Science Foundation and other funders generally require grant recipients to submit evaluation data, but that information is not currently aggregated and shared publicly, even for programs that are using a common evaluation tool. 1

Therefore, while program evaluation likely serves a useful role in providing descriptive data about a program for the institutions and funders supporting the program, much of the summative evaluation work that has been done to date adds relatively little to the broader knowledge base and overall conversations around undergraduate research. Some of the challenges of evaluation include budget and sample size constraints.

Similarly, it is difficult for designers of UREs to benefit systematically from the work of others who have designed and run UREs in the past because of the lack of an easy and consistent mechanism for collecting, analyzing, and sharing data. If these evaluations were more accessible they might be beneficial to others designing and evaluating UREs by helping them to gather ideas and inspiration from the experiences of others. A few such stories are provided in this report, and others can be found among the many resources offered by the Council on Undergraduate Research 2 and on other websites such as CUREnet. 3

Recommendation 3: Designers of UREs should base their design decisions on sound evidence. Consultations with education and social science researchers may be helpful as designers analyze the literature and make decisions on the creation or improvement of UREs. Professional development materials should be created and made available to faculty. Educational and disciplinary societies should consider how they can provide resources and connections to those working on UREs.

Faculty and other organizers of UREs can use the expanding body of scholarship as they design or improve the programs and experiences offered to their students. URE designers will need to make decisions about how to adapt approaches reported in the literature to make the programs they develop more suitable to their own expertise, student population(s), and available resources. Disciplinary societies and other national groups, such as those focused on improving pedagogy, can play important roles in

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1 Personal knowledge of Janet Branchaw, member of the Committee on Strengthening Research Experiences for Undergraduate STEM Students.

2 See www.cur.org [November 2016].

3 See ( curenet.cns.utexas.edu ) [November 2016].

bringing these issues to the forefront through events at their national and regional meetings and through publications in their journals and newsletters. They can develop repositories for various kinds of resources appropriate for their members who are designing and implementing UREs. The ability to travel to conferences and to access and discuss resources created by other individuals and groups is a crucial aspect of support (see Recommendations 7 and 8 for further discussion).

See Chapter 8 for specific questions to consider when one is designing or implementing UREs.

CURRENT OFFERINGS

Conclusion 6: Data at the institutional, state, or national levels on the number and type of UREs offered, or who participates in UREs overall or at specific types of institutions, have not been collected systematically. Although the committee found that some individual institutions track at least some of this type of information, we were unable to determine how common it is to do so or what specific information is most often gathered.

There is no one central database or repository that catalogs UREs at institutions of higher education, the nature of the research experiences they provide, or the relevant demographics (student, departmental, and institutional). The lack of comprehensive data makes it difficult to know how many students participate in UREs; where UREs are offered; and if there are gaps in access to UREs across different institutional types, disciplines, or groups of students. One of the challenges of describing the undergraduate research landscape is that students do not have to be enrolled in a formal program to have a research experience. Informal experiences, for example a work-study job, are typically not well documented. Another challenge is that some students participate in CUREs or other research experiences (such as internships) that are not necessarily labeled as such. Institutional administrators may be unaware of CUREs that are already part of their curriculum. (For example, establishment of CUREs may be under the purview of a faculty curriculum committee and may not be recognized as a distinct program.) Student participation in UREs may occur at their home institution or elsewhere during the summer. Therefore, it is very difficult for a science department, and likely any other STEM department, to know what percentage of their graduating majors have had a research experience, let alone to gather such information on students who left the major. 4

4 This point was made by Marco Molinaro, University of California, Davis, in a presentation to the Committee on Strengthening Research Experience for Undergraduate STEM Students, September 16, 2015.

Conclusion 7: While data are lacking on the precise number of students engaged in UREs, there is some evidence of a recent growth in course-based undergraduate research experiences (CUREs), which engage a cohort of students in a research project as part of a formal academic experience.

There has been an increase in the number of grants and the dollar amount spent on CUREs over the past decade (see Chapter 3 ). CUREs can be particularly useful in scaling UREs to reach a much larger population of students ( Bangera and Brownell, 2014 ). By using a familiar mechanism—enrollment in a course—a CURE can provide a more comfortable route for students unfamiliar with research to gain their first experience. CUREs also can provide such experiences to students with diverse backgrounds, especially if an institution or department mandates participation sometime during a student’s matriculation. Establishing CUREs may be more cost-effective at schools with little on-site research activity. However, designing a CURE is a new and time-consuming challenge for many faculty members. Connecting to nationally organized research networks can provide faculty with helpful resources for the development of a CURE based around their own research or a local community need, or these networks can link interested faculty to an ongoing collaborative project. Collaborative projects can provide shared curriculum, faculty professional development and community, and other advantages when starting or expanding a URE program. See the discussion in the report from a convocation on Integrating Discovery-based Research into the Undergraduate Curriculum ( National Academies of Sciences, Engineering, and Medicine, 2015 ).

Recommendation 4: Institutions should collect data on student participation in UREs to inform their planning and to look for opportunities to improve quality and access.

Better tracking of student participation could lead to better assessment of outcomes and improved quality of experience. Such metrics could be useful for both prospective students and campus planners. An integrated institutional system for research opportunities could facilitate the creation of tiered research experiences that allow students to progress in skills and responsibility and create support structures for students, providing, for example, seminars in communications, safety, and ethics for undergraduate researchers. Institutions could also use these data to measure the impact of UREs on student outcomes, such as student success rates in introductory courses, retention in STEM degree programs, and completion of STEM degrees.

While individual institutions may choose to collect additional information depending on their goals and resources, relevant student demographics

and the following design elements would provide baseline data. At a minimum, such data should include

Type of URE;
Each student’s discipline;
Duration of the experience;
Hours spent per week;
When the student began the URE (e.g., first year, capstone);
Compensation status (e.g., paid, unpaid, credit); and
Location and format (e.g., on home campus, on another campus, internship, co-op).

National aggregation of some of the student participation variables collected by various campuses might be considered by funders. The existing Integrated Postsecondary Education Data System database, organized by the National Center for Education Statistics at the U.S. Department of Education, may be a suitable repository for certain aspects of this information.

Recommendation 5: Administrators and faculty at all types of colleges and universities should continually and holistically evaluate the range of UREs that they offer. As part of this process, institutions should:

Consider how best to leverage available resources (including off-campus experiences available to students and current or potential networks or partnerships that the institution may form) when offering UREs so that they align with their institution’s mission and priorities;
Consider whether current UREs are both accessible and welcoming to students from various subpopulations across campus (e.g., historically underrepresented students, first generation college students, those with disabilities, non-STEM majors, prospective kindergarten-through-12th-grade teachers); and
Gather and analyze data on the types of UREs offered and the students who participate, making this information widely available to the campus community and using it to make evidence-based decisions about improving opportunities for URE participation. This may entail devising or implementing systems for tracking relevant data (see Conclusion 4 ).

Resources available for starting, maintaining, and expanding UREs vary from campus to campus. At some campuses, UREs are a central focus and many resources are devoted to them. At other institutions—for example, many community colleges—UREs are seen as extra, and new resources may be required to ensure availability of courses and facilities. Resource-

constrained institutions may need to focus more on ensuring that students are aware of potential UREs that already exist on campus and elsewhere in near proximity to campus. All institutional discussions about UREs must consider both the financial resources and physical resources (e.g., laboratories, field stations, engineering design studios) required, while remembering that faculty time is a crucial resource. The incentives and disincentives for faculty to spend time on UREs are significant. Those institutions with an explicit mission to promote undergraduate research may provide more recognition and rewards to departments and faculty than those with another focus. The culture of the institution with respect to innovation in pedagogy and support for faculty development also can have a major influence on the extent to which UREs are introduced or improved.

Access to UREs may vary across campus and by department, and participation in UREs may vary across student groups. It is important for campuses to consider the factors that may facilitate or discourage students from participation in UREs. Inconsistent procedures or a faculty preference for students with high grades or previous research experience may limit options for some student populations.

UREs often grow based on the initiative of individual faculty members and other personnel, and an institution may not have complete or even rudimentary knowledge of all of the opportunities available or whether there are gaps or inconsistencies in its offerings. A uniform method for tracking the UREs available on a given campus would be useful to students and would provide a starting point for analyzing the options. Tracking might consist of notations in course listings and, where feasible, on student transcripts. Analysis might consider the types of UREs offered, the resources available to each type of URE, and variations within or between various disciplines and programs. Attention to whether all students or groups of students have appropriate access to UREs would foster consideration of how to best allocate resources and programming on individual campuses, in order to focus resources and opportunities where they are most needed.

Conclusion 8: The quality of mentoring can make a substantial difference in a student’s experiences with research. However, professional development in how to be a good mentor is not available to many faculty or other prospective mentors (e.g., graduate students, postdoctoral fellows).

Engagement in quality mentored research experiences has been linked to self-reported gains in research skills and productivity as well as retention in STEM (see Chapter 5 ). Quality mentoring in UREs has been shown

to increase persistence in STEM for historically underrepresented students ( Hernandez et al., 2016 ). In addition, poor mentoring during UREs has been shown to decrease retention of students ( Hernandez et al., 2016 ).

More general research on good mentoring in the STEM environment has been positively associated with self-reported gains in identity as a STEM researcher, a sense of belonging, and confidence to function as a STEM researcher ( Byars-Winston et al., 2015 ; Chemers et al., 2011 ; Pfund et al., 2016 ; Thiry et al., 2011 ). The frequency and quality of mentee-mentor interactions has been associated with students’ reports of persistence in STEM, with mentoring directly or indirectly improving both grades and persistence in college. For students from historically underrepresented ethnic/racial groups, quality mentoring has been associated with self-reported enhanced recruitment into graduate school and research-related career pathways ( Byars-Winston et al., 2015 ). Therefore, it is important to ensure that faculty and mentors receive the proper development of mentoring skills.

Recommendation 6: Administrators and faculty at colleges and universities should ensure that all who mentor undergraduates in research experiences (this includes faculty, instructors, postdoctoral fellows, graduate students, and undergraduates serving as peer mentors) have access to appropriate professional development opportunities to help them grow and succeed in this role.

Although many organizations recognize effective mentors (e.g., the National Science Foundation’s Presidential Awards for Excellence in Science, Mathematics, and Engineering Mentoring), there currently are no standard criteria for selecting, evaluating, or recognizing mentors specifically for UREs. In addition, there are no requirements that mentors meet some minimum level of competency before engaging in mentoring or participate in professional development to obtain a baseline of knowledge and skills in mentoring, including cultural competence in mentoring diverse groups of students. Traditionally, the only experience required for being a mentor is having been mentored, regardless of whether the experience was negative or positive ( Handelsman et al., 2005 ; Pfund et al., 2015 ). Explicit consideration of how the relationships are formed, supported, and evaluated can improve mentor-mentee relationships. To ensure that the mentors associated with a URE are prepared appropriately, thereby increasing the chances of a positive experience for both mentors and mentees, all prospective mentors should prepare for their role. Available resources include the Entering Mentoring course (see Pfund et al., 2015 ) and the book Successful STEM Mentoring Initiative for Underrepresented Students ( Packard, 2016 ).

A person who is an ineffective mentor for one student might be inspiring for another, and the setting in which the mentoring takes place (e.g., a CURE or apprentice-style URE, a laboratory or field-research environment) may also influence mentor effectiveness. Thus, there should be some mechanism for monitoring such relationships during the URE, or there should be opportunity for a student who is unhappy with the relationship to seek other mentors. Indeed, cultivating a team of mentors with different experiences and expertise may be the best strategy for any student. A parallel volume to the Entering Mentoring curriculum mentioned above, Entering Research Facilitator’s Manual ( Branchaw et al., 2010 ), is designed to help students with their research mentor-mentee relationships and to coach them on building teams of mentors to guide them. As mentioned in Chapter 5 , the Entering Research curriculum also contains information designed to support a group of students as they go through their first apprentice-style research experience, each working in separate research groups and also meeting together as a cohort focused on learning about research.

PRIORITIES FOR THE FUTURE

Conclusion 9: The unique assets, resources, priorities, and constraints of the department and institution, in addition to those of individual mentors, impact the goals and structures of UREs. Schools across the country are showing considerable creativity in using unique resources, repurposing current assets, and leveraging student enthusiasm to increase research opportunities for their students.

Given current calls for UREs and the growing conversation about their benefits, an increasing number of two- and four-year colleges and universities are increasing their efforts to support undergraduate research. Departments, institutions, and individual faculty members influence the precise nature of UREs in multiple ways and at multiple levels. The physical resources available, including laboratories, field stations, and engineering design studios and testing facilities, make a difference, as does the ability to access resources in the surrounding community (including other parts of the campus). Institutions with an explicit mission to promote undergraduate research may provide more time, resources (e.g., financial, support personnel, space, equipment), and recognition and rewards to departments and faculty in support of UREs than do institutions without that mission. The culture of the institution with respect to innovation in pedagogy and support for faculty development also affects the extent to which UREs are introduced or improved.

Development of UREs requires significant time and effort. Whether or not faculty attempt to implement UREs can depend on whether departmental

or institutional reward and recognition systems compensate for or even recognize the time required to initiate and implement them. The availability of national consortia can help to alleviate many of the time and logistical problems but not those obstacles associated with recognition and resources.

It will be harder for faculty to find the time to develop UREs at institutions where they are required to teach many courses per semester, although in some circumstances faculty can teach CUREs that also advance their own research ( Shortlidge et al., 2016 ). Faculty at community colleges generally have the heaviest teaching expectations, little or no expectations or incentives to maintain a research program, limited access to lab or design space or to scientific and engineering journals, and few resources to undertake any kind of a research program. These constraints may limit the extent to which UREs can be offered to the approximately 40 percent of U.S. undergraduates who are enrolled in the nation’s community colleges (which collectively also serve the highest percentage of the nation’s underrepresented students). 5

Recommendation 7: Administrators and faculty at all types of colleges and universities should work together within and, where feasible, across institutions to create a culture that supports the development of evidence-based, iterative, and continuous refinement of UREs, in an effort to improve student learning outcomes and overall academic success. This should include the development, evaluation, and revision of policies and practices designed to create a culture supportive of the participation of faculty and other mentors in effective UREs. Policies should consider pedagogy, professional development, cross-cultural awareness, hiring practices, compensation, promotion (incentives, rewards), and the tenure process.

Colleges and universities that would like to expand or improve the UREs offered to their students should consider the campus culture and climate and the incentives that affect faculty choices. Those campuses that cultivate an environment supportive of the iterative and continuous refinement of UREs and that offer incentives for evaluation and evidence-based improvement of UREs seem more likely to sustain successful programs. Faculty and others who develop and implement UREs need support to be able to evaluate their courses or programs and to analyze evidence to make decisions about URE design. This kind of support may be fostered by expanding the mission of on-campus centers for learning and teaching to focus more on UREs or by providing incentives for URE developers from the natural sciences and engineering to collaborate with colleagues in the social sciences or colleges of education with expertise in designing studies

5 See http://nces.ed.gov/programs/coe/indicator_cha.asp [November 2016].

involving human subjects. Supporting closer communication between URE developers and the members of the campus Institutional Review Board may help projects to move forward more seamlessly. Interdepartmental and intercampus connections (especially those between two- and four-year institutions) can be valuable for linking faculty with the appropriate resources, colleagues, and diverse student populations. Faculty who have been active in professional development on how students learn in the classroom may have valuable experiences and expertise to share.

The refinement or expansion of UREs should build on evidence from data on student participation, pedagogy, and outcomes, which are integral components of the original design. As UREs are validated and refined, institutions should make efforts to facilitate connections among different departments and disciplines, including the creation of multidisciplinary UREs. Student engagement in learning in general, and with UREs more specifically, depends largely on the culture of the department and the institution and on whether students see their surroundings as inclusive and energetic places to learn and thrive. A study that examined the relationship between campus missions and the five benchmarks for effective educational practice (measured by the National Survey of Student Engagement) showed that different programs, policies, and approaches may work better, depending on the institution’s mission ( Kezar and Kinzie, 2006 ).

The Council on Undergraduate Research (2012) document Characteristics of Excellence in Undergraduate Research outlines several best practices for UREs based on the apprenticeship model (see Chapter 8 ). That document is not the result of a detailed analysis of the evidence but is based on the extensive experiences and expertise of the council’s members. It suggests that undergraduate research should be a normal part of the undergraduate experience regardless of the type of institution. It also identifies changes necessary to include UREs as part of the curriculum and culture changes necessary to support curricular reform, co-curricular activities, and modifications to the incentives and rewards for faculty to engage with undergraduate research. In addition, professional development opportunities specifically designed to help improve the pedagogical and mentoring skills of instructional staff in using evidence-based practices can be important for a supportive learning culture.

Recommendation 8: Administrators and faculty at all types of colleges and universities should work to develop strong and sustainable partnerships within and between institutions and with educational and professional societies for the purpose of sharing resources to facilitate the creation of sustainable URE programs.

Networks of faculty, institutions, regionally and nationally coordinated URE initiatives, professional societies, and funders should be strengthened

to facilitate the exchange of evidence and experience related to UREs. These networks could build on the existing work of professional societies that assist faculty with pedagogy. They can help provide a venue for considering the policy context and larger implications of increasing the number, size, and scope of UREs. Such networks also can provide a more robust infrastructure, to improve the sustainability and expansion of URE opportunities. The sharing of human, financial, scientific, and technical resources can strengthen the broad implementation of effective, high-quality, and more cost-efficient UREs. It may be especially important for community colleges and minority-serving institutions to engage in partnerships in order to expand the opportunities for undergraduates (both transfer and technical students) to participate in diverse UREs (see discussion in National Academies of Sciences, Engineering, and Medicine, 2015 , and Elgin et al., 2016 ). Consortia can facilitate the sharing of resources across disciplines and departments within the same institution or at different institutions, organizations, and agencies. Consortia that employ research methodologies in common can share curriculum, research data collected, and common assessment tools, lessening the time burden for individual faculty and providing a large pool of students from which to assess the efficacy of individual programs.

Changes in the funding climate can have substantial impacts on the types of programs that exist, iterative refinement of programs, and whether and how programs might be expanded to broaden participation by more undergraduates. For those institutions that have not yet established URE programs or are at the beginning phases of establishing one, mechanisms for achieving success and sustainability may include increased institutional ownership of programs of undergraduate research, development of a broad range of programs of different types and funding structures, formation of undergraduate research offices or repurposing some of the responsibilities and activities of those which already exist, and engagement in community promotion and dissemination of student accomplishments (e.g., student symposia, support for undergraduate student travel to give presentations at professional meetings).

Over time, institutions must develop robust plans for ensuring the long-term sustained funding of high-quality UREs. Those plans should include assuming that more fiscal responsibility for sustaining such efforts will be borne by the home institution as external support for such efforts decreases and ultimately ends. Building UREs into the curriculum and structure of a department’s courses and other programs, and thus its funding model, can help with sustainability. Partnerships with nonprofit organizations and industry, as well as seeking funding from diverse agencies, can also facilitate programmatic sustainability, especially if the UREs they fund can also support the mission and programs of the funders (e.g., through research internships or through CUREs that focus on community-

based research questions and challenges). Partnerships among institutions also may have greater potential to study and evaluate student outcomes from URE participation across broader demographic groups and to reduce overall costs through the sharing of administrative or other resources (such as libraries, microscopes, etc.).

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Undergraduate research has a rich history, and many practicing researchers point to undergraduate research experiences (UREs) as crucial to their own career success. There are many ongoing efforts to improve undergraduate science, technology, engineering, and mathematics (STEM) education that focus on increasing the active engagement of students and decreasing traditional lecture-based teaching, and UREs have been proposed as a solution to these efforts and may be a key strategy for broadening participation in STEM. In light of the proposals questions have been asked about what is known about student participation in UREs, best practices in UREs design, and evidence of beneficial outcomes from UREs.

Undergraduate Research Experiences for STEM Students provides a comprehensive overview of and insights about the current and rapidly evolving types of UREs, in an effort to improve understanding of the complexity of UREs in terms of their content, their surrounding context, the diversity of the student participants, and the opportunities for learning provided by a research experience. This study analyzes UREs by considering them as part of a learning system that is shaped by forces related to national policy, institutional leadership, and departmental culture, as well as by the interactions among faculty, other mentors, and students. The report provides a set of questions to be considered by those implementing UREs as well as an agenda for future research that can help answer questions about how UREs work and which aspects of the experiences are most powerful.

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Strengthening Research Experiences for Undergraduate STEM Students

Undergraduate research has a rich history, and many practicing researchers point to undergraduate research experiences (UREs) as crucial to their own career success. There are many ongoing efforts to improve undergraduate science, technology, engineering, and mathematics (STEM) education that focus on increasing the active engagement of students and decreasing traditional lecture-based teaching. The study will explore what is known about student participation in UREs, best practices in UREs design, and evidence of beneficial outcomes from UREs.

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Undergraduate Research Experiences for STEM Students: Successes, Challenges, and Opportunities

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An ad hoc committee will synthesize the broad range of literature on models for providing undergraduate students with authentic research experiences in STEM disciplines or professions. The committee will define what qualifies as “authentic undergraduate research experiences” and assess the quality of research available on various types of these research experiences. If possible and based on the strength of the literature, the committee will compare the effectiveness of different mechanisms and programs for providing undergraduate research experiences and provide best-practice examples of successful strategies for involving undergraduate research programs. The committee will review the empirical evidence of benefits across a range of outcomes associated with the multitude of educational, student, and institutional goals. It will critically assess the associated full costs involved in providing authentic research experiences within the context of undergraduate STEM education across all types of post-secondary institutions of higher learning and provide recommendations for research and practice. The committee will also discuss the needs of faculty and departmental administrators in order to successfully implement or improve and expand undergraduate research opportunities. The committee will develop a conceptual framework for designing and evaluating undergraduate research opportunities and create a research and development agenda to clarify what additional research is needed to robustly assess the quality and outcomes of undergraduate research experiences. The committee will balance the potential value added of making research or practice experiences more “authentic” with the potential additional investment of time, institutional capacity and financial support needed and suggest strategies for implementing undergraduate research experiences for various goals and outcomes, and for a variety of institutions with different types and levels of resources at their disposal.

Division of Behavioral and Social Sciences and Education
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Open access
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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Our Mission

Research-Based Practices for Engaging Students in STEM Learning

Innovative and effective practices at Cleveland’s MC2 STEM High School are driving learning and higher achievement for students in a district where every student qualifies for free or reduced-price meals.

The STEM School Movement

Science, technology, engineering, and math (STEM) specialty schools have existed in the United States for over 100 years, fueled in the 1950s by the Cold War space race and recently reinvigorated by concern over U.S. students’ modest performance in math and science as compared to their international peers (Means et al., 2008). This is troubling because, according to the National Research Council (2011), “more than half of the tremendous growth to per capita income in the 20th century can be accounted for by U.S. advances in science and technology.” In addition, businesses in the United States have voiced concern over the supply and availability of STEM workers and experts are concerned that the demand for STEM labor will only increase with time (U.S. Department of Commerce, 2011, 2012). Thus, the primary goal of the STEM school movement is to promote a future STEM workforce and maintain the U.S. position as a leader in innovation. There is also the need for citizens and consumers to be informed and engaged in everyday decisions that involve scientific arguments -- from policy debates that will have consequences for their health and safety to the products they consume and lifestyle choices they make.

One STEM school that is helping its students develop an array of skills to succeed in college and the workforce is MC 2 STEM High School (MC 2 STEM) in Cleveland, Ohio. Cleveland Metropolitan School District is one of the most economically disadvantaged school districts in the nation, with a free or reduced-price lunch rate of 100 percent. In 2011, just six out of ten students from the school district graduated high school on time. But at MC 2 STEM, which opened its doors in 2008, 95 percent of the first class graduated high school within four years. Students who have attended MC 2 STEM have not only graduated high school, they have also achieved the school’s requirements for mastery of every state standard. An integration of several research-based practices helps to promote student success and a caring environment at this small school:

interdisciplinary project-based learning with real-world application
challenging goals with multiple opportunities to show and develop learning
community partnerships that provide tutors, mentors, internships, and service learning experiences.

Preliminary research on successful STEM schools indicates that cultivating partnerships with industry, higher education, nonprofits, museums, and research centers is important for engaging students in STEM learning through internships, mentorships, interdisciplinary project-based learning, and early college experiences (Means, 2008; National Research Council, 2011). MC 2 STEM is part of the Ohio STEM Learning Network , a network of ten STEM schools, developed with support from the Bill and Melinda Gates Foundation and in collaboration with the State of Ohio and various other partners. The Ohio STEM Learning Network is designed around five common principles . As a part of this network, MC 2 STEM is an inclusive STEM school that accepts students via lottery, as opposed to competitive selection, and is committed to the idea that STEM talent is something that can be developed, rather than something innate that must be identified (Means, 2008).

Interdisciplinary Project-Based Learning with Real-World Application

Project-based learning (PBL) has been shown to improve students' understanding of science, as well as their problem-solving and collaboration skills, to a greater extent than traditional methods (Geier et al., 2008; Gordon, Rogers, Comfort, Gavula, and McGee, 2001; Kolodner et al., 2003; Lee, Buxton, Lewis, and LeRoy, 2006; Liu, Hsieh, Cho, and Schallert, 2006; Lynch, Kuipers, Pyke, and Szesze, 2005; Marx et al., 2004; Schneider, Krajcik, Marx, and Soloway, 2001). Students who learn science or technology through project-based learning also report that they find it more engaging than traditional instructional techniques (Geier et al., 2008; Yazzie-Mintz, 2010).

PBL is the biggest component at MC 2 STEM and is perhaps even more engaging to students because of its interdisciplinary content. Interdisciplinary curricula have been shown by several studies to support students’ engagement and learning (Taylor and Parsons, 2011), and specifically integrating science with reading comprehension and writing lessons has been shown by several studies to improve students’ understanding in both science and English language arts (Pearson, Moje, and Greenleaf, 2010).

MC 2 STEM's transdisciplinary capstone projects blend science, English language arts, social studies, fine arts, engineering, and math, and are designed to transcend in-school and out-of-school environments. Their projects more closely resemble the tasks and ambiguities inherent in real life and help to make schoolwork more relevant to students’ lives, as well as more transparently linked to the skills needed to succeed in the working world. For example, in the “Bridges" capstone (PDF) , students learn about the mathematical and engineering concepts necessary to construct bridges, as well as the symbolic meaning of bridges in literature, history, and social studies.

In accord with the recommendations of PBL scholars and practitioners, capstone projects at MC 2 STEM are designed by starting with the learning objectives -- in this case, the Common Core standards (e.g., Wiggins and McTighe, 2005; Buck Institute for Education, 2012). Instructors of different subjects work together to think of a larger thematic concept that covers the state standards, and then they break down the larger thematic concept into units that address each state standard. (See a process model and planning activities for designing these types of transdisciplinary projects.)

In addition to the Common Core state standards, career-readiness standards for engineering and technology are also incorporated into several of the capstone projects at MC 2 STEM. For example, all students complete a Sophomore General Electric Project (PDF) , which is designed with GE Lighting employees to address current industry needs. According to Principal Jeffrey McClellan, if instructors are having difficulty coming up with a unit for a particular benchmark, industry partners have been helpful in brainstorming and explaining how particular state standards are used in their work, which results in more realistic capstone units.

(See our Resources and Downloads for PBL design documents and other resources from MC 2 STEM for transdisciplinary PBL.)

Challenging Goals with Multiple Opportunities to Show and Develop Learning

The combination of high expectations and adequate supports has been shown by several meta-analyses to be one of the most impactful strategies for improving academic achievement (Hattie, 2009). In order for challenging goals to be effective, Hattie (2011) asserts that they must be presented in a situation that is structured so that students can achieve them, students must be committed to them, and students must receive frequent feedback so they can direct and evaluate their actions accordingly. (See a flow chart of the multiple opportunities that MC 2 STEM students have for mastering benchmarks.)

MC 2 STEM is a challenging learning environment that holds high expectations for all students, while also providing multiple forms of support for students to show and develop learning. The MC 2 STEM graduation requirements state that in order to earn high school credit, students must achieve mastery (PDF) (greater than or equal to 90 percent in grades 9 and 10, and greater than or equal to 70 percent in grades 11 and 12) on each and every state standard. In addition, students must participate in 60 hours of community and/or STEM service and complete a GE sophomore project as well as a senior project in which they address an original research question.

About half of MC 2 STEM students fulfill all mastery requirements in the first three years. If a student doesn’t master a benchmark during a specific capstone, they are not required to retake that course. Instead, the missing benchmark is noted on their grade-card and teachers work with the student to integrate those benchmarks into subsequent capstones. (The digital grade-cards (PDF) provide a real-time picture of student progress toward mastery, and the school uses the 21st Century Partnership for STEM Education’s online grade-card system, which is a proficiency-based assessment that gives access to the school’s parents and teachers.) About 40 percent of the state standards are assessed through capstone projects, and the rest of the standards are assessed through more traditional in-class methods such as quizzes and presentations. During most classes, students work in groups based on the particular benchmark activities or assessments that they are mastering, while the teacher and tutors walk around and provide assistance.

Ohio’s Credit Flexibility Plan has played an important role in redesigning the high school experience at MC 2 STEM to enable in-depth learning. Schools that adopt the program can award high school course credit for fulfilling the state’s learning objectives as an alternative to seat-time. (Read more about the policy.) Credit Flexibility supports the Post Secondary Enrollment Option Program provided by MC 2 STEM, which allows students to earn college and high school credits simultaneously. Students also earn high school credit for internship experiences and typically up to two years of early college credit. Principal McClellan has a refrain at MC 2 STEM that reinforces high expectations, rather than the time students spend to achieve them: “Time is the variable. Knowledge is the constant.”

Students also participate in many extended-learning activities to support their learning, including summer learning at Case Western Reserve University and tutoring and mentorship programs. Students in grade nine meet with NASA employees four school days a year at NASA Glenn Research Center, and about one-third of freshmen work with NASA tutors after school for one hour, once or twice per week. Throughout the time they are working with the school, NASA tutors work with the same students so relationships can develop. Similarly, in grade ten, GE employees tutor students once or twice per week during lunch, and each tutor works with the same student for the entire time they are in the tutoring program. In addition, all sophomores spend two lunch periods per month with a GE mentor. Students report feeling cared about and supported at the school at a level that is above the district’s average, according to the district’s 2010 Conditions for Learning Survey.

The dropout-prevention research has also emphasized that “close mentoring and monitoring of students” is critical (Fairfax County Public Schools, 2011). According to McClellan, more often than not, simply asking a student why they haven’t been meeting expectations is the first step toward addressing the issue that is holding them back. MC 2 STEM is a small learning environment with approximately 300 students; however, the school’s design also incorporates frequent feedback into the curriculum and successfully increases its capacity for tutoring and mentoring through community partnerships with NASA, GE, and the Jewish Federation of Cleveland, as well as with interns and UTeach candidates from Cleveland State University. As described below, community partnerships also help to provide students with feedback from diverse stakeholders through internships and service-learning.

Community Partnerships That Provide Tutors, Mentors, Internships, and Service-Learning Experiences

Project-based learning helps to connect schoolwork with the work of professionals, and these connections are made further transparent through professional mentoring as well as internship and service-learning experiences. As MC 2 STEM students demonstrate mastery of state requirements, they earn the opportunity to participate in paid and unpaid internships (PDF) for high school credit. The principal determines internship readiness, with input from the guidance counselor and professional partners where appropriate. The potential employer interviews the student and decides if the student is hired for their internship. Currently over 50 percent of seniors and 40 percent of juniors are participating in paid internships, and about 90 percent of the class of 2012 participated in an internship prior to graduation. In addition to internships, all students are required to complete 40 hours of community service.

Research supports the potential benefits of internships or apprenticeships and community service for academic achievement and student engagement when these experiences are closely connected with curricular objectives (Bell, Blair, Crawford, and Lederman, 2003; Billig, 2007). Rigorous studies from the career-academy literature have also shown that integrating academic and work experiences can have positive impacts on students’ later earnings. Graduates of career-themed high schools that emphasized the connection between school and getting a good job earned 11 percent more per year, on average, than graduates of traditional high schools eight years after graduating (Stern et al., 2010). Similarly, the dropout-prevention literature emphasizes the importance of making school relevant to students’ lives and making sure that school is engaging and challenging. In a 2006 survey of students who dropped out of high school, 81 percent said that if schools provided opportunities for real-world learning , including internships and service-learning, it would have improved their chances of graduating high school (Bridgeland, Dilulio, and Morison, 2006). The study also found that clarifying the links between school and getting a job may convince more students to stay in school (Bridgeland et al., 2006).

Bibliography

Bell, R. L., Blair, L. M., Crawford, B. A., and Lederman, N. G. (2003). Just Do It? Impact of a Science Apprenticeship on High School Students’ Understandings of the Nature of Science and Scientific Inquiry. Journal of Research in Science Teaching, 40 (5), 487-509.

Billig, S. H. (2007). Unpacking What Works in Service-Learning Promising Research-Based Practices to Improve Student Outcomes. Growing to Greatness , p. 18-28. National Youth Leadership Council.

Bridgeland, J. M., Dilulio, J. J., and Morison, K. B. (2006). The Silent Epidemic: Perspectives of High School Dropouts.

Buck Institute for Education. (2009). Does PBL Work?

Fairfax County Public Schools. (2011). Bringing the Dropout Challenge into Focus. Fairfax County, VA: Department of Professional Learning and Accountability, Office of Program Evaluation.

Geier, R., Blumenfeld, P. C., Marx, R. W., Krajcik, J. S., Fishman, B., Soloway, E., et al. (2008). Standardized Test Outcomes for Students Engaged in Inquiry-Based Science Curricula in the Context of Urban Reform. Journal of Research in Science Teaching, 45 (8), 922–939.

Gordon, P. R., Rogers, A. M., Comfort, M., Gavula, N., and McGee, B. P. (2001). A Taste of Problem-Based Learning Increases Achievement of Urban Minority Middle-School Students. Educational Horizons, 79 (4), 171-175.

Hattie, J. A. C. (2009). Visible Learning: A Synthesis of Over 800 Meta-Analyses Relating to Achievement. New York: Routledge.

Kolodner, J. L., Camp, P. J., Crismond, D., Fasse, B., Gray, J., Holbrook, J., and Puntambekar, S. (2003). Problem-Based Learning Meets Case-Based Reasoning in the Middle-School Science Classroom: Putting Learning by Design into Practice. The Journal of the Learning Sciences, 12 (4), 495-547.

Lee, O., Buxton, C., Lewis, S., and LeRoy, K. (2006). Science Inquiry and Student Diversity: Enhanced Abilities and Continuing Difficulties After an Instructional Intervention. Journal of Research in Science Teaching, 43 (7), 607-636.

Liu, M., Hsieh, P., Cho, Y. J., and Schallert, D. L. (2006). Middle School Students’ Self-efficacy, Attitudes, and Achievement in a Computer-Enhanced Problem-Based Learning Environment. Journal of Interactive Learning Research, 17 (3), 225-242.

Lynch, S., Kuipers, J., Pyke, C., and Szesze, M. (2005). Examining the Effects of a Highly Rated Science Curriculum Unit on Diverse Students: Results from a Planning Grant. Journal of Research in Science Teaching, 42 (8), 912–946.

Marx, R. W., Blumenfeld, P. C., Krajcik, J. S., Fishman, B., Soloway, E., Geier, R., et al. (2004). Inquiry-Based Science in the Middle Grades: Assessment of Learning in Urban Systemic Reform. Journal of Research in Science Teaching, 41 (10), 1063–1080.

Means, B., Confrey, J., House, A., and Bhanot, R. (2008). STEM High Schools Specialized Science Technology Engineering and Mathematics Secondary Schools in the U.S. SRI Project P17858.

National Research Council - Committee on Highly Successful Science Programs for K-12 Science Education, Board on Science Education and Board on Testing and Assessment, Division of Behavioral and Social Sciences and Education. (2011). Successful K-12 STEM Education: Identifying Effective Approaches in Science, Technology, Engineering, and Mathematics. Washington, DC: The National Academies Press.

Pearson, P. D., Moje, E., and Greenleaf, C. (2010). Literacy and Science: Each in Service of the Other. Science , 328, 459-463.

Schneider, R. M., Krajcik, J., Marx, R. W., and Soloway, E. (2002). Performance of Students in Project Based Science Classrooms on a National Measure of Science Achievement. Journal of Research in Science Teaching, 38 (7), 410-422.

Stern, D., Dayton, C. and Raby, M. (2010). Career Academies: A Proven Strategy to Prepare High School Students for College and Careers. Berkeley, CA: University of California at Berkeley, Career Academy Support Network.

Taylor, L. and Parsons, J. (2011). Improving Student Engagement. Current Issues in Education, 14 (1).

U.S. Department of Commerce, Economics and Statistics Administration. (2011). STEM: Good Jobs Now and for the Future. (ESA Issue Brief #03-11.)

U.S. Department of Commerce. (2012). The Competitiveness and Innovative Capacity of the United States.

Wiggins, G. and McTighe, J. (2005). Understanding by Design. Expanded 2nd Ed. Alexandria, VA: Association for Supervision and Curriculum Development.

Yazzie-Mintz, E. (2010). Charting the Path from Engagement to Achievement: A Report on the 2009 High School Survey of Student Engagement.

Mc2 Stem High School

Per pupil expenditures, free / reduced lunch, demographics:.

12% individualized education programs 2% English-language learners

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189+ Experimental Quantitative Research Topics For STEM Students

Are you looking for incredible experimental quantitative research topics for STEM students? Then you are in the right place. Here, we’ll explore the fantastic experimental research topics for STEM students and others you want to learn. That will help you to increase your knowledge in your field.

Experimental quantitative research plays a pivotal role in STEM. These students explore a broad range of multidisciplinary experimental quantitative research subjects. STEM students take on challenges that push the boundaries of knowledge, whether by studying the complexities of ecological systems, creating novel technologies, delving into the workings of the human brain, or investigating the subtleties of subatomic particles.

Before jumping to our main topic, experimental quantitative research topics for STEM students. Let’s learn about what STEM is.

What Is STEM?

STEM is an acronym that stands for Science, Technology, Engineering, and Mathematics. It is an interdisciplinary approach to learning and problem-solving that combines these four main areas. Scientists, technicians, engineers, and mathematicians collaborate to address challenging real-world challenges and generate novel solutions in the STEM fields.

Let’s know about how to do experimental research. Before starting the experimental quantitative research topics for STEM students.

How To Do Experimental Research

Here are 8 key points on how to do experimental research effectively.

1. Clear Research Focus

Begin by defining a clear and focused research question. A well-defined question provides a purpose and direction for your experiment, guiding your choices in variables and methodology.

2. Thorough Literature Review

Conduct a comprehensive literature review to understand the existing knowledge in your field. This step helps you identify gaps in research and ensures your experiment contributes meaningfully to the scientific community.

3. Precise Variable Definition

Carefully define the variables you will manipulate (independent variable) and measure (dependent variable). Precise definitions are crucial for the validity of your experiment, ensuring you measure what you intend to study.

Also read: 199+ Quantitative Research Topics For STEM Students to Try Now

4. Randomization and Control

Use randomization to assign participants randomly to experimental and control groups. Control all other variables that might influence the outcome, creating a controlled environment. This minimizes biases and enhances the reliability of your results.

5. Standardized Procedures

Develop standardized procedures for conducting the experiment. Consistency in methods across participants and groups is essential to ensure that any observed effects are due to the manipulated variables and not external factors.

6. Accurate Data Collection

Employ accurate and reliable methods to collect data. Be meticulous in recording observations and measurements. Utilize appropriate tools and technologies to minimize errors and enhance the precision of your data.

7. Thorough Data Analysis

Use appropriate statistical techniques to analyze the collected data. Statistical analysis helps you identify patterns, relationships, and significant differences between groups. Proper analysis is key to drawing valid conclusions from your experiment.

8. Clear Communication of Results

Effectively communicate your research findings through clear and concise writing. Present your results, methods, and conclusions in a structured manner, adhering to the standards of scientific reporting. Transparent communication ensures that others can understand, evaluate, and build upon your research.

By following these 8 points, you can conduct experimental research in a systematic, reliable, and impactful manner, leading to valuable contributions to your field of study. Now, let’s move to the main topic, experimental quantitative research topics for STEM students.

Experimental Quantitative Research Topics For STEM Students

Certainly, there are more than 189+ experimental quantitative research topics for STEM students, categorized into different fields:

Biology and Life Sciences

Effects of Different Fertilizers on Plant Growth
Impact of Light Intensity on Photosynthesis
Influence of Temperature on Enzyme Activity
Relationship Between Diet and Animal Behavior
Efficacy of Antibiotics on Bacterial Cultures
Effects of Microplastics on Aquatic Ecosystems
Impact of pH Levels on Microbial Growth
The Role of Genetics in Disease Susceptibility
Influence of Pollution on Soil Microbes
The Effect of Radiation on Cellular DNA

Chemistry and Chemical Engineering

Kinetics of Chemical Reactions at Various Temperatures
Efficiency of Various Catalysts in Chemical Processes
Influence of pH on Chemical Equilibrium
Study of Electrochemical Cells and Voltage
Impact of Different Solvents on Reaction Rates
Properties of Various Polymers in Material Science
Effects of Different Oxidizing Agents on Reactions
The Relationship Between Pressure and Gas Behavior
The Influence of Concentration on Reaction Rate
The Efficacy of Water Purification Methods

Physics and Engineering

The Impact of Different Materials on Magnet Strength
Efficiency of Wind Turbines at Different Wind Speeds
Influence of Friction on Motion and Speed
Relationship Between Light Wavelengths and Energy
Effects of Different Insulation Materials on Heat Transfer
Impact of Material Properties on Bridge Strength
Efficiency of Solar Panels in Different Light Conditions
Influence of Temperature on Electrical Conductivity
Study of Fluid Dynamics in Various Geometries
The Role of Geometric Shapes in Sound Resonance

Environmental Science

Effects of Land Use on Local Climate Patterns
Influence of Air Pollution on Plant Health
Impact of Climate Change on Ocean Acidification
The Relationship Between Soil Erosion and Agricultural Productivity
Efficacy of Biodegradable Materials in Reducing Plastic Pollution
Study of Water Quality Parameters in Urban vs. Rural Areas
Effects of Renewable Energy Sources on Carbon Footprint
Influence of Pesticides on Honeybee Population Decline
Impact of Soil Contaminants on Groundwater Quality
The Role of Algae in Wastewater Treatment

Computer Science and Technology

Effects of Algorithm Complexity on Execution Time
Influence of Data Structures on Software Performance
Impact of Different Programming Languages on Code Efficiency
The Relationship Between Internet Speed and User Experience
Efficacy of Different Machine Learning Models in Data Analysis
Effects of Cybersecurity Measures on Network Vulnerabilities
Influence of Mobile App Features on User Engagement
Impact of Virtual Reality in Education on Learning Outcomes
The Use of Nanomaterials in Data Storage Devices
The Role of Artificial Intelligence in Natural Language Processing

Mathematics and Statistics

Effects of Teaching Methods on Math Skill Acquisition
Influence of Classroom Size on Student Performance
Impact of Tutoring Programs on Math Proficiency
The Relationship Between Homework and Test Scores
Efficacy of Different Teaching Strategies in Probability Education
Effects of Math Anxiety on Test Performance
Influence of Gender on Mathematical Problem-Solving
Impact of Early Math Education on Later Achievement
The Role of Game-Based Learning in Mathematics
The Use of Data Visualization in Statistical Analysis

Medicine and Healthcare

Effects of Medication on Heart Rate Variability
Influence of Different Therapies on Pain Management
Impact of Sleep Duration on Cognitive Performance
The Relationship Between Diet and Weight Loss
Efficacy of Telemedicine in Remote Healthcare Delivery
Effects of Telehealth on Patient Engagement
Influence of Lifestyle on Blood Pressure
Impact of Exercise on Stress Reduction
The Role of Telemedicine in Mental Health Support
The Use of Wearable Health Devices in Disease Monitoring

Materials Science and Nanotechnology

Effects of Nanomaterials on Solar Cell Efficiency
Influence of Nanoparticles on Drug Delivery
Impact of Nanotechnology on Water Filtration
The Relationship Between Nanomaterial Size and Strength
Efficacy of Nanoparticles in Targeted Cancer Therapy
Effects of Nanotechnology on Wearable Electronics
Influence of Nanomaterials in Energy Storage
Impact of Nanomaterials on Sensor Technologies
The Role of Nanomaterials in Environmental Remediation
The Use of Nanotechnology in Biomedical Imaging

Astronomy and Space Science

Effects of Stellar Types on Planetary Formation
Influence of Dark Matter on Galactic Dynamics
Impact of Solar Activity on Earth’s Climate
The Relationship Between Asteroids and Space Weather
Efficacy of Space Telescopes in Exoplanet Discovery
Effects of Cosmic Radiation on Space Travelers
Influence of Gravitational Waves on Black Hole Research
Impact of Satellite Data on Weather Prediction
The Role of Telescopes in Exoplanet Characterization
The Use of Space Probes in Solar System Exploration

Geology and Earth Sciences

Effects of Plate Tectonics on Earthquakes
Influence of Rock Types on Coastal Erosion
Impact of Soil Composition on Landslide Risk
The Relationship Between Geothermal Activity and Volcanic Eruptions
Efficacy of Geological Maps in Hazard Prediction
Effects of Climate Change on Glacier Movement
Influence of Seismic Waves on Building Resilience
Impact of Mineral Properties on Geological Exploration
The Role of Ground-Penetrating Radar in Archaeological Surveys
The Use of LiDAR in Topographic Mapping

Social Sciences

Effects of Social Media Use on Mental Health
Influence of Parenting Styles on Child Behavior
Impact of Education Levels on Income Disparities
The Relationship Between Income and Job Satisfaction
Efficacy of Diversity Training in Workplace Inclusion
Effects of Media Violence on Aggressive Behavior
Influence of Music on Stress Reduction
Impact of Family Structure on Child Development
The Role of Gender Stereotypes in Career Choices
The Use of Virtual Reality in Empathy Training

Economics and Finance

Effects of Fiscal Policy Changes on Economic Growth
Influence of Interest Rates on Investment Decisions
Impact of Inflation on Consumer Spending
The Relationship Between Stock Market Volatility and Investor Behavior
Efficacy of Financial Education on Saving Habits
Effects of Tax Policies on Small Business Growth
Influence of Exchange Rates on International Trade
Impact of Government Regulation on Industry Profitability
The Role of Behavioral Economics in Decision-Making
The Use of Cryptocurrencies in Global Transactions

Environmental Engineering

Effects of Wetland Restoration on Water Quality
Influence of Green Building Techniques on Energy Efficiency
Impact of Renewable Energy Integration on Grid Stability
The Relationship Between Land Use Planning and Flood Resilience
Efficacy of Environmental Impact Assessments in Construction
Effects of Water Treatment Methods on Contaminant Removal
Influence of Erosion Control Measures on Coastal Preservation
Impact of Watershed Management on Aquatic Ecosystem Health
The Role of Stormwater Management in Urban Sustainability
The Use of Biodegradable Materials in Waste Reduction

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Robotics and Automation

Effects of Different Algorithms on Robot Navigation
Influence of Sensor Technologies on Autonomous Vehicles
Impact of Machine Learning on Robotic Object Recognition
The Relationship Between Human-Robot Interaction and User Satisfaction
Efficacy of Robot-Assisted Surgery in Medical Procedures
Effects of Robotics on Disaster Response and Recovery
Influence of Automation on Manufacturing Efficiency
Impact of AI in Autonomous Drones for Environmental Monitoring
The Role of Robotics in Space Exploration
The Use of AI in Predictive Maintenance for Industrial Equipment

Agricultural Sciences

Effects of Crop Rotation on Soil Nutrient Levels
Influence of Pest Control Methods on Crop Yields
Impact of Irrigation Techniques on Water Conservation
The Relationship Between Genetic Modification and Crop Resilience
Efficacy of Precision Agriculture in Resource Optimization
Effects of Soil Microbes on Plant Health
Influence of Organic Farming on Soil Biodiversity
Impact of Sustainable Practices on Farming Profitability
The Role of Drought-Resistant Crops in Food Security
The Use of Drones in Precision Farming

Energy Engineering

Effects of Different Energy Storage Systems on Grid Reliability
Influence of Renewable Energy Integration on Energy Independence
Impact of Building Insulation on Energy Efficiency
The Relationship Between Energy-Efficient Appliances and Household Savings
Efficacy of Smart Grid Technologies in Energy Management
Effects of Solar Thermal Systems on Water Heating
Influence of Geothermal Heat Pumps on HVAC Efficiency
Impact of Hydropower on Renewable Energy Portfolios
The Role of Energy-Efficient Lighting in Green Building
The Use of Biofuels in Reducing Carbon Emissions

Telecommunications and Networking

Effects of Network Topologies on Data Transmission Speed
Influence of Encryption Protocols on Data Security
Impact of 5G Technology on Mobile Network Performance
The Relationship Between Network Load and Bandwidth Allocation
Efficacy of Network Redundancy in Data Backup
Effects of Internet Traffic on Quality of Service
Influence of Routing Algorithms on Packet Delivery
Impact of Firewall Configurations on Network Protection
The Role of Network Virtualization in Scalability
The Use of IoT Devices in Smart Home Connectivity

Materials Engineering

Effects of Heat Treatment on Material Strength
Influence of Alloy Composition on Metal Durability
Impact of Coating Materials on Corrosion Resistance
The Relationship Between Material Properties and Wear Resistance
Efficacy of Composite Materials in Structural Applications
Effects of Surface Treatments on Material Hardness
Influence of Polymers in Biodegradable Packaging
Impact of Nanomaterials on Lightweight Materials
The Role of Smart Materials in Shape Memory Applications
The Use of Superconductors in Energy Transmission

Renewable Energy Technologies

Effects of Wind Turbine Blade Design on Energy Efficiency
Influence of Solar Panel Orientation on Energy Output
Impact of Biofuel Feedstock on Bioenergy Production
The Relationship Between Geothermal Heat Extraction and Sustainability
Efficacy of Tidal Energy Systems in Marine Environments
Effects of Concentrated Solar Power on Thermal Storage
Influence of Energy-Efficient Lighting in Building Sustainability
Impact of Biomass Gasification on Bioenergy Generation
The Role of Ocean Thermal Energy Conversion in Renewable Energy
The Use of Piezoelectric Materials in Energy Harvesting

Urban Planning and Architecture

Effects of Urban Green Spaces on Air Quality
Influence of Building Design on Indoor Air Quality
Impact of Transportation Systems on Urban Accessibility
The Relationship Between Noise Pollution and Building Acoustics
Efficacy of Low-Impact Development in Urban Stormwater Management
Effects of Smart Cities Technologies on Energy Efficiency
Influence of Green Building Materials on Sustainable Construction
Impact of Walkability in Urban Planning and Health
The Role of Urban Farms in Food Security
The Use of Building Automation Systems in Energy Management

Psychology and Behavioral Science

Effects of Stress Management Techniques on Well-Being
Influence of Cognitive Behavioral Therapy on Anxiety Reduction
Impact of Behavioral Interventions on Autism Spectrum Disorder
The Relationship Between Color Psychology and Retail Sales
Efficacy of Mindfulness Meditation in Stress Reduction
Effects of Music Therapy on Dementia Patients’ Behavior
Influence of Social Media Use on Self-Esteem
Impact of Positive Psychology on Employee Well-Being
The Impact of Video Games on Cognitive Skills

Here, we discussed the list of incredible experimental quantitative research topics for STEM students.

Some Experimental Research Topics For High School Students

Above, we discussed the list of experimental quantitative research topics for STEM students. Now, let’s discuss some experimental research topics suitable for high school students.

Exploring Alternative Energy Sources
Investigating the Effects of Climate Change on Local Ecosystems
Testing the Impact of Different Fertilizers on Plant Growth
Studying the Genetics of Inherited Traits
Measuring the Impact of Music on Concentration and Productivity
Examining the Relationship Between Exercise and Academic Performance
Investigating the Effects of Different Cooking Methods on Food Nutrient Levels
Testing the Efficiency of Water Filtration Methods
Studying the Behavior of Insects in Various Environments
Exploring the Chemistry of Food Preservation
Investigating the Physics of Simple Machines
Testing the Effect of Light on Plant Growth
Studying the Impact of Color on Human Mood and Perception
Measuring the Effect of Different Cleaning Products on Bacterial Growth
Investigating the Physics of Projectile Motion

These research topics cover a wide range of disciplines, allowing high school students to engage in exciting and educational experiments while nurturing their scientific curiosity and passion.

6 Mistakes To Avoid While Choosing an Experimental Research Topic

Selecting the right experimental research topic is an essential step to scoring in academic life. However, some common mistakes can hinder your research progress. Let’s explore six pitfalls to avoid:

1. Lack of Personal Interest

Choosing a topic solely based on its popularity or perceived prestige can lead to a lack of personal connection—your emotional investment matters. Select a subject that genuinely intrigues and excites you, as your enthusiasm will be your driving force throughout the research journey.

2. Overambitious Goals

Setting unrealistic expectations can lead to frustration and burnout. Remember, you’re not expected to solve the world’s most complex problems with a single experiment. Start with manageable, well-defined objectives that align with your resources and timeframe.

3. Ignoring Your Skill Level

Overestimating your skills can be disheartening. Choose a topic that matches your current knowledge and expertise. Gradual growth is emotionally rewarding, and as you gain proficiency, you can tackle more complex challenges.

4. Neglecting Resources

Research can be emotionally draining if you lack the necessary resources, be it equipment, materials, or mentorship. Before diving in, ensure you have access to the tools and guidance required for your chosen topic.

5. Failure to Consider the Bigger Picture

Focusing solely on your topic’s microcosm may lead to a lack of context. Remember to examine how your research fits into the larger scientific landscape. This perspective can be emotionally fulfilling, knowing that your work contributes to a broader understanding.

Also read: 21+ Best Paying Jobs In Computer Software Prepackaged Software

6. Ignoring Ethical and Emotional Implications

Some topics may have ethical considerations or evoke emotional responses. Be aware of the potential emotional toll and moral dilemmas that your research may entail. Ensure that you’re emotionally prepared to address these issues responsibly.

Here, we discussed the mistakes to avoid while choosing the experimental research topics.

In this blog, we discussed the experimental quantitative research topics for STEM students, how to do research, what is STEM, some research topics for high school, and mistakes that should be avoided while choosing the experimental research topics.

In conclusion, an experimental research topic is valuable for STEM students to increase their practical knowledge. Each research topic we choose in this blog will definitely help you to achieve your academic goals. Experimental quantitative research gives STEM students concrete insights to deepen their scientific understanding.

STEM students, addressing what STEM is and why research matters in this field. The key takeaway is to choose a topic that resonates with your passion and aligns with your goals, ensuring a successful journey in STEM research. Choose the best Experimental Quantitative Research Topics For STEM students today!

Frequently Asked Questions

Q1. why is experimental quantitative research important for stem students .

It is important because it fosters critical thinking, problem-solving skills, and hands-on learning. It allows STEM students to explore real-world questions, make evidence-based discoveries, and contribute to advancements in their chosen fields.

Q2. What Skills Will I Develop Through Experimental Research?

STEM students will develop skills in critical thinking, data analysis, problem-solving, project management, and effective communication. These skills are valuable in both academia and the workplace.

Q3. What are the Key Elements of a Good Research Question?

A good research question should be specific, clear, measurable, and relevant. It should also be focused on testing a hypothesis or addressing a knowledge gap in your field.

People also looked at

Original research article, teachers’ perceptions of the barriers to stem teaching in qatar’s secondary schools: a structural equation modeling analysis.

1 Educational Research Center, College of Education, Qatar University, Doha, Qatar
2 Qatar University Young Scientists Center (QUYSC), Qatar University, Doha, Qatar

Introduction: Educators play a pivotal role in shaping students’ academic achievements, particularly in STEM (science, technology, engineering, and mathematics) fields. The instructional techniques employed by teachers significantly impact students’ decisions to pursue or persist in STEM disciplines. This research aims to explore the challenges faced by high school STEM teachers in Qatar in delivering effective STEM instruction.

Methods: Data was collected through a survey administered to 290 high school STEM teachers across thirty-nine schools in Qatar. The survey targeted teachers in the 11th and 12th grades. Structural Equation Modeling (SEM) was utilized to analyze the data and examine teachers’ perceived barriers to effective STEM instruction.

Results: The findings revealed various barriers hindering STEM instruction. These barriers were categorized into school-related, student-related, technology-related, and teaching-related factors. All the hypothesized teaching barriers [i.e., (student-related: β = –0.243, p < 0.001); (school-related: β = –0.122, p < 0.001), (technologyrelated: β = –0.123, p = 0.040); and (instruction-related: β = –0.112, p < 0.018)] were negatively related to teachers’ STEM teaching. Among the various obstacles, it appears that the most formidable challenges for high school STEM teachers are related to students (β = –0.243, p < 0.001).

Discussion: Understanding these barriers is crucial for informing educational policies and developing strategies to enhance STEM learning in Qatar’s high schools. Addressing these barriers is essential to provide adequate resources, professional development opportunities, and support systems. By addressing these challenges, Qatar can foster a conducive environment for effective STEM instruction, thereby nurturing a future generation of STEM professionals.

1 Introduction

Science, technology, engineering, and mathematics (STEM) education has garnered increased attention in the past decade, prompting calls for a heightened emphasis particularly on the quality of STEM teaching ( Btool and Koc, 2017 ). The STEM education approach advocates for a novel teaching and learning methodology, emphasizing hands-on inquiry and open-ended exploration ( Waters and Orange, 2022 ). This approach facilitates the development of 21st-century quintessential skills, such as problem-solving, creative thinking, collaborative teamwork, and technology literacy, catering to students with diverse interests, abilities, and experiences ( Ichsan et al., 2023 ). In light of the many global challenges and potential threats, the knowledge/skills pertaining to STEM are crucial for comprehending and addressing these pressing issues. This underscores the significance of STEM as a driver of prosperity and sustainable development for present and future generations ( AlMuraie et al., 2021 ).

In this regard, teachers are key figures in driving STEM initiatives globally, with a particular emphasis on those instructing science subjects ( Oliveros Ruiz et al., 2014 ). Numerous studies underscore the significance of science education across various academic levels ( Kola, 2013 ; Oliveros Ruiz et al., 2014 ). Researchers contend that the primary objective of science education is to equip individuals with the skills required to become scientists and technologists, crucial for advancing research and innovation ( Ichsan et al., 2023 ). This preparation serves as the cornerstone for the economic prosperity and well-being of emerging economies and contributes to the overall development of nations.

In the unique context of Qatar, the past few years have witnessed concerted efforts to shift from an economy that is reliant on gas and oil resource wealth to one centered on knowledge and innovation, as outlined in the Qatar National Vision 2030 ( Tan et al., 2014 ). Underlying this transformation is an earnest and compelling call for action to cultivate national expertise ( Ben Hassen, 2021 ). Indeed, there is a pressing demand for professionals in STEM fields in Qatar, a concern voiced repeatedly by educators, government officials, and industry stakeholders ( Cherif et al., 2016 , 2021 ). Despite the increasing demand for STEM professionals in Qatar, the number of Qatari citizens possessing the education and training necessary to support the vital industries of their country’s economy remains alarmingly low. This disconnect between education and the job market in Qatar has led to a significant proportion of unskilled and semi-skilled citizens being employed in the public sector ( Babar et al., 2019 ). Consequently, the private sector has had to rely on foreign workers to bridge the gap in STEM professions. With a scarcity of young individuals pursuing STEM careers, Qatar’s dependence on expatriate labor in these fields is set to persist.

Adding to the challenges of a foreign-dominated labor force in Qatar is the fact that many highly educated Qatari citizens hold degrees in non-STEM disciplines. Furthermore, there is clear evidence that a significant number of Qataris, particularly males, do not aspire to pursue higher education ( Sellami et al., 2017 ), which has serious implications for efforts to develop a sustainable local STEM workforce ( Al-Misnad, 2012 ). Interestingly, there is a dearth of documented research exploring these issues related to the shortage of skilled professionals in Qatar and the broader Gulf Cooperation Council (GCC) region ( Al-Misnad, 2012 ; Sellami et al., 2017 ; Babar et al., 2019 ). Despite notable progress in terms of equitable access to formal education, enrollment rates, and literacy rates in Qatar, critics argue that the country’s education system still falls short in producing highly skilled graduates who can contribute effectively to the nation’s development and prosperity ( Ben Hassen, 2021 ). This dependence on highly skilled foreign professionals further compounds the issue. To enhance the capabilities of its skilled workforce, Qatar must make concerted efforts to increase the enrollment of both men and women in disciplines aligned with the knowledge economy, on par with developing nations.

In light of the preceding background information, STEM teaching is pivotal to Qatar’s economic prosperity. While the country’s national development strategy underscores the importance of STEM education for progress and development, the practical implementation of STEM teaching faces numerous challenges, especially in developing countries such as Qatar and the larger GCC region ( Cherif et al., 2016 ). Accordingly, this study aims to explore teachers’ perceptions of salient barriers to STEM teaching in Qatar. The uniqueness of this present study lies in providing research-based insights into these obstacles from an Arab Middle Eastern perspective.

This paper is structured as follows. The section below offers a review of the relevant literature that has addressed the main challenges that impede STEM teaching. This is followed by a statement of the theoretical framework guiding this study as well as a description of the problem statement and the research questions. The next section details the research methods employed in our study, including a description of participants, instruments, and data analysis. A presentation of the study’s results is provided next, in turn, followed by a discussion and interpretation of these results. The paper concludes with some important recommendations for policy and practice.

2 Review of literature

In view of the growing demand for professionals possessing the critical skills and knowledge that are essential for economic growth and development, the responsibility lies with educational institutions to prepare students equipped with vital STEM skill sets ( AlMuraie et al., 2021 ). Improving students’ STEM-related capabilities requires schools to enhance their STEM education offerings and reconfigure their instructional methods. Central to such educational reforms is the imperative to incorporate teachers as a vital element ( Antonova et al., 2022 ).

Serving as essential catalysts in the educational journey, teachers play a central role in providing STEM education ( Kim, 2021 ). They possess the capacity to profoundly influence students’ academic performance in STEM subjects and, in the long run, shape their interest in and enthusiasm for pursuing STEM fields of study and eventual careers ( Blazar and Kraft, 2017 ). Students’ learning experiences, encompassing both theoretical classroom knowledge and hands-on practical experience, are pivotal factors in augmenting their proficiency in STEM-related skills and knowledge ( Romlie et al., 2021 ; Rohendi et al., 2023 ). When coupled with the guidance of dedicated teachers and access to high-quality STEM programs and curricula, these experiences create an optimal environment for nurturing students’ innate talents and capabilities within the realm of STEM disciplines ( MacFarlane, 2021 ).

The existing body of literature sheds light on the intricate interplay of several factors — broadly the individual (personal) and environmental (contextual)—that can either facilitate or impede STEM teaching ( Nugent et al., 2015 ; Sellami et al., 2017 ). For instance, researchers have proposed a range of social (i.e., contextual, school environment-related, family/peer/teachers support, etc.), individual (student-related, teachers-related in terms of knowledge, interest, self-efficacy, etc.), and instructional (curriculum, student-related, teacher-related, etc.), factors that contribute to the creation of favorable conditions for effective STEM teaching ( Nugent et al., 2015 ; Margot and Kettler, 2019 ; Wahono and Chang, 2019 ; Dong et al., 2020 ; Hamad et al., 2022 ; Karkouti et al., 2022 ). One of the studies exemplifies the comprehensive review of teachers’ perspectives on STEM education and has pinpointed six primary barriers that pose challenges to STEM teaching ( Margot and Kettler, 2019 ). These barriers are closely tied to the curriculum, pedagogical approaches, assessment methods, teacher support, student factors, and structural systems within the educational landscape ( Margot and Kettler, 2019 ). As outlined in the literature, these barriers, encompass various facets, such as teachers’ beliefs, knowledge, and comprehension of STEM, as well as difficulties in applying STEM concepts to specific topics, and challenges in establishing connections between different STEM subjects, etc. ( Wahono and Chang, 2019 ; Dong et al., 2020 ). Additional obstacles comprise inadequate teacher preparation, limited opportunities for professional development, a shortage of qualified STEM teachers, insufficient integration of cross-disciplinary content, low levels of student motivation, curriculum changes, inadequate resources and facilities, and assessments that may not effectively align with STEM education objectives ( Hamad et al., 2022 ; Karkouti et al., 2022 ). Ongoing discussions on STEM education highlight obstacles that impede the implementation of effective interdisciplinary teaching methods. At the same time, contemporary dialogues and arguments concerning STEM education underscore the hindrances that obstruct the successful adoption of interdisciplinary STEM teaching approaches.

From a more extensive viewpoint, various obstacles may hinder STEM teaching, encompassing issues related to instruction, students, technology, school, etc. ( Al-Misnad, 2012 ; Sellami et al., 2017 ; Babar et al., 2019 ). Drawing from insights into existing literature, this present study seeks to explore the connections among impediments associated with students, technology, schools, and instruction as perceived by STEM teachers (refer to Figure 1 ).

Figure 1. Barriers to STEM teaching.

3 Theoretical framework

The conceptual foundation of this study is based on similar research, which delved into the perceptions of high school teachers regarding the obstacles to teaching STEM in Qatar, including student-related, technology-related, school-related, and instruction-related barriers in teaching STEM ( Sellami et al., 2022 ). The study employed descriptive statistics and logistic regression models to understand how teachers perceived these barriers. However, our current study distinguishes itself by using SEM to investigate the path coefficients and uncover the significant relationships between the investigated constructs.

The theoretical framework underpinning this study ( Bandura, 1989 ) and Attribution Theory ( Bandura, 1997 ; Weiner, 2010 ). In this research, the social cognitive theory (SCT) serves as a valuable theoretical framework, offering insights into the barriers impeding STEM teaching by considering both individual factors (related to students and teachers) and environmental factors (associated with the context or school). In contrast, AT, a well-established research paradigm in social psychology, offers insights into understanding why specific behaviors or events occur and how individuals contribute to these occurrences. In this research, Atribution theory which focuses on how individuals explain the causes of events, can be applied to understand the barriers to STEM teaching. The theory can provide insights into how teachers attribute the challenges and successes in STEM education, shedding light on the factors impacting their STEM teaching.

The use of SCT focuses on what aspects of STEM were perceived as barriers whereas AT highlights how individuals attribute STEM teaching barriers. Therefore, guided by the existing literature, our study postulates that high school STEM teachers in Qatar should confront challenges that impact their teaching processes. These challenges are examined through the lenses of SCT and AT, which consider the interplay between individual beliefs and environmental factors in shaping STEM education.

3.1 Problem statement and research questions

As discussed, one of the key components of Qatar’s educational reform is to improve the standards of education by enhancing the quality of schoolteachers ( Nasser, 2017 ). In this respect, this study is important as it intends to investigate salient barriers to STEM education from a teacher’s perspective. Therefore, this study will extend knowledge related to the challenges that thwart STEM education. As such, this research aligns with Qatar National Vision-2030, which highlights Qatar’s need to transform into a knowledge-based economy. Based on the preceding deliberations, this study employs SEM to facilitate a comprehensive exploration of teachers’ perspectives on key obstacles to STEM education. After undergoing a critical literature review, this study put forth four hypotheses, as is shown in Figure 2 below:

Figure 2. Hypothesized model.

H1: Student-related barriers negatively influence STEM teaching in higher education.

H2: Technology-related barriers negatively influence STEM teaching in higher education.

H3: School-related barriers negatively influence STEM teaching in higher education.

H4: Instruction-related barriers negatively influence STEM teaching in higher education.

4 Research methods

An exploratory quantitative research approach was adopted to examine teachers’ perceptions of the main impediments to STEM education. This research design involved a review of the relevant literature on STEM-teaching barriers ( Al-Misnad, 2012 ; Nugent et al., 2015 ; Sellami et al., 2017 ; Babar et al., 2019 ), where themes were identified to guide the creation of a quantitative instrument. This instrument is then employed to delve deeper into the research problem ( Creswell et al., 2011 ; Berman, 2017 ). A survey questionnaire was then developed to explore the barriers related to STEM teaching (i.e., student-related, technology-related, school environment-related, and teaching methods.

The survey was conducted both in person and virtually during the 2021 Spring Semester, spanning from March to April 2021. The survey administration involved physical questionnaires [paper-and-pencil interviewing (PAPI)] and computer-assisted personal interviews (CAPI). The latter involved gathering survey data through face-to-face interviews conducted by interviewers, using computers, smartphones, and tablets. This technique allowed the interviewers to input responses directly into these devices, enabling real-time data collection and reducing the need for manual data entry ( Blazar and Kraft, 2017 ).

For the purpose of this study, data was gathered from thirty-nine high schools randomly selected from across Qatar. These schools were a combination of both local government schools (56.4%) and private schools (43.6%) in Qatar. Following the approval process from Qatar University’s research ethics board (IRB), the research team contacted school board superintendents and teachers to secure their consent for data collection within their respective schools. After excluding teachers who did not complete the entire survey, a total of 290 STEM teachers participated in this research study. The study involved a nationwide survey and the sample was representative of the entire country. With the given number of completions, the maximum sampling error for a percentage in the teacher survey was approximately +/−2.4 percentage points. The computation of this sampling error accounts for design effects, encompassing influences from weighting, stratification, and clustering. One possible interpretation of sampling errors is that if the survey is repeated 100 times using the same procedure, the sampling errors would encompass the “true value” in 95 out of the 100 surveys. It is important to note that the calculation of sampling errors was feasible in this survey due to the sample being derived from a known probability-based sampling scheme set by the Ministry of Education.

Table 1 provides an overview of the teacher-related variables, showing their gender distribution (54.5% males and 45.5% females) and age groups, with the majority falling between the ages of 31 to 40 (40.1%). A significant portion of the participants had a bachelor’s degree (59.5%) and nearly most of the teachers were expatriates (96%). In terms of their teaching assignments, the largest group of teachers taught both grades 11 and 12 (45.8%), while 25.8% exclusively taught grade 11, and 24.7% exclusively taught grade 12.

Table 1. Teacher-related variables ( n = 290).

4.2 Survey instrument

The survey had three primary objectives: (a) Gathering fundamental background information, (b) Systematically documenting teaching approaches, and (c) Structurally documenting the key challenges encountered in effective STEM teaching. The implementation process involved three phases: (1) the development of the survey, (2) the testing of the survey through a pilot study, and (3) the administration of the survey.

Step 1: To develop the survey, we examined existing research on STEM teaching barriers ( Shadle et al., 2017 ; Sturtevant and Wheeler, 2019 ; Karkouti et al., 2022 ; Kayan-Fadlelmula et al., 2022 ; Sellami et al., 2022 ). The review of existing literature provided valuable insights into the specific target areas of the study. It helped us gain a better comprehension of how teachers perceive STEM teaching and the associated barriers. The survey employed a five-point Likert scale to assess close-ended items across five distinct constructs: i.e., (a) Student-related barriers, (b) technology-related barriers, (c) school-related barriers, (d) teaching-related barriers, and (e) implementation of STEM instruction. For each construct, teachers were presented with various response options tailored to the type of question. This included disagree-agree questions (ranging from 1 = strongly disagree to 6 = strongly agree); Frequency questions (ranging from 1 = never to 5 = always); Percentage questions; Rating questions (ranging from 1 = very poor to 5 = very good), Emphasis questions (ranging from 1 = none to 5 = heavy), and significance questions (ranging from not important at all = 1 to very important = 5). These diverse set of question types allowed for a comprehensive assessment of teachers’ perceptions and experiences related to STEM education.

Step 2: During this phase, the survey that was designed was pilot-tested with two focus groups, one conducted in Arabic and the other in English. This step was crucial for refining the survey instrument. The discussions within these focus groups proved invaluable in addressing concerns related to the wording of the survey questions. This process enabled us to rephrase and clarify questions that were inadequately worded or potentially confusing. The insights gained from the focus group discussions helped ensure that the survey was clear, and concise, and effectively collected the necessary data to achieve these goals.

Step 3: The third phase of survey execution involved the distribution of questionnaires after the reception of signed consent forms from both teachers and school authorities. Teachers were given the option to respond to the survey in either English or Arabic. On average, it took participants between 13 and 17 min to complete the study.

4.3 Data measures

The survey constructs were carefully designed as quantitative measures to capture key factors essential for addressing the research questions of this study. These measures encompassed various constructs, including student-related, technology-related, and school-related teaching barriers, as well as teacher STEM pedagogy implementations. The rationale behind selecting these measures stemmed from prior analyses that highlighted the existence of numerous obstacles impeding effective STEM teaching, such as restrictive teaching hours, curriculum challenges, student-related conflicts, evaluation difficulties, and lack of teacher support ( Margot and Kettler, 2019 ; Dong et al., 2020 ; Hamad et al., 2022 ; Karkouti et al., 2022 ). Below are the details of the formulation of these measures:

4.3.1 Student-related teaching barrier

The student-related teaching barrier explored the extent to which the teaching methods of educators were influenced by issues related to students. These issues covered the following areas: a lack of necessary skills, a lack of requisite knowledge, inadequate sleep, classroom disruptions, and reduced interest. Teachers’ perceptions of student-related barriers were reverse coded due to negative statements and the codes “−2” and “1 was assigned to the responses “often” and “always”, respectively. Meanwhile, a value of “0” was assigned to “undecided” “1” and “2” for “rarely” and “never”, respectively. Technology-related teaching barrier: For this barrier, teachers were responsible for evaluating the degree to which technology-related challenges affected their teaching. These challenges included several factors, including insufficient computers, lack of internet speed or bandwidth, outdated or malfunctioning computers, lack of technical support, and insufficient interactive whiteboards. The responses provided by teachers were coded using the same methodology adopted for student-related barriers to represent technology-related barriers

4.3.2 School-related teaching barrier

Here, teachers were tasked with assessing the degree to which their teaching was influenced by various challenges within the school environment. These challenges were represented by a variety of factors, which include technical support, STEM training, and pedagogical assistance, curriculum and teaching hours, availability of instructional materials and supplies, adequacy of classroom facilities, the state of school computers, organization of school spaces, administrative and budgetary constraints, the overall school environment, and the level of support and interest from fellow teachers. Similar coding on a 5-point Likert scale has been followed.

4.3.3 Instruction-related teaching barrier

The fourth construct utilized in this analysis is referred to as a school-related teaching barrier. Teachers were asked to detail the extent to which their teaching was impacted by school-related challenges. These challenges included insufficient school laboratory resources, overcrowded classrooms, inefficient school time management, administrative limitations, budget constraints, and the pressure to prepare students for examinations. For consistency, a coding system similar to the other barriers was implemented, the 5-point Likert scale.

4.3.4 STEM teaching

The fifth and final construct is STEM teaching, where teachers were presented with a scale to indicate the degree to which they utilized pedagogical approaches. This scale covered a spectrum from ( Btool and Koc, 2017 ) 0–20% to ( Oliveros Ruiz et al., 2014 ) 81–100%. The pedagogical approaches under consideration include project- and problem-based methods, collaborative learning, and the flipped classroom model as examples. To streamline the analysis, the responses provided by teachers were translated into numerical values. Each specified percentage range was assigned a numerical code, ranging from 1 to 5, as follows: 0–20% corresponded to 1, 21–40% to 2, 41–60% to 3, 61–80% to 4, and 81–100% to 5.

4.4 Data analysis

The data analysis was conducted using the Statistical Package for the Social Sciences (SPSS) statistics software and SPSS AMOS (Analysis of Moment Structures), version 29.0.0.0. Initially, an Exploratory Factor Analysis (EFA) was employed to gain insights into data reliability, item quality, and construct validity. Five steps were involved in implementing factor analysis. (1) Data adequacy and evaluation: This step involved assessing the suitability of the data for factor analysis, (2) Construct extraction: Factors or constructs were extracted from the data, (3) Factor selection: criteria were applied to determine which factors should be retained/removed, (4) Rotation technique: A rotation approach was employed to optimize factor interpretability, (5) Results Analysis: The results of the factor analysis were analyzed and non-contributing factors were removed, resulting in the construction of a structural model containing significant constructs. For EFA, statistical indicators such as Kaiser Meyer Olkin’s value and Bartlett’s test of sphericity were computed to assess the appropriateness of the data for factor analysis.

To better understand how the different components (questions) overlap or differ in explaining the variance in their respective indicators, the study evaluated the construct validity of each component, specifically focusing on convergent validity and discriminant validity. Convergent validity was assessed using the average variance extracted (AVE), which represents the average of the squared loadings of the indicators associated with each component. Discriminant validity, on the other hand, was gauged using the heterotrait–monotrait ratio (HTMT) of correlations. HTMT compares the average correlations between indicators measuring different components to the average correlations among indicators measuring the same component.

Additionally, the survey model’s internal consistency reliability was evaluated using two tests: Cronbach’s Alpha and MacDonald’s Omega. These tests provide insights into the reliability and consistency of the survey’s measurement scales. Descriptive statistics were computed for the overall analysis of the data based on the data evaluations according to the paper’s scope. Finally, SEM was employed to address the stated hypotheses.

4.4.1 Goodness of fit measures for SEM

The study assessed various goodness-of-fit measures to evaluate the model’s fit in SEM. These measures included the chi-square divided by degrees of freedom (χ 2 /df), Tucker-Lewis Index (TLI), Comparative Fit Index (CFI), Root Mean Residual (RMR), and Root Mean Square Error of Approximation (RMSEA), Root Mean Square Residuals (RMSR), Normed Fit Index (NFI) ( Hair et al., 2012 ).

4.5 Validation of the instruments

To derive constructs that would adequately tackle the research questions in this study, factor analysis was utilized. This analysis encompassed principal component analysis and varimax rotation, with a minimum factor loading requirement of 0.50. The suitability of the data for factor analysis was verified by its significance, as indicated by the chi-squared test (χ2) = 5561.089, p < 0.001). To further confirm the adequacy of the sample, the Kaiser–Mayer–Olkin and Bartlett’s test of sphericity was employed. The Kaiser–Mayer–Olkin value, which stood at 0.919, indicated that the data was appropriate for factor analysis. To evaluate construct validity, convergent validity was determined by computing the AVE for all indicators within each construct. The AVE was calculated to be above 0.7, which is considered an acceptable value ( Fornell and Larcker, 1981 ).

Discriminant validity was evaluated using the HTMT ratio of correlations, and the resulting value was found to be 0.8, which is also considered an acceptable value. Moreover, to validate the internal consistency, Cronbach’s Alpha and MacDonald’s Omega were computed. All the values were within the acceptable range (>0.7) ( Cohen et al., 2002 ). At the same time, composite reliability (CR) was calculated, and all these values fell within the acceptable threshold (>0.6). The results of factor loadings and internal reliability are provided in Table 2 below. Finally, to evaluate the hypotheses, the study employs a SEM approach to analyze the relationship between the constructs concerning teachers’ barriers and STEM teaching.

Table 2. Results of confirmatory factor analysis and reliability tests ( n = 290).

The findings of this study provide valuable insights into the main obstacles encountered by STEM teachers in their teaching. These findings are presented and structured in alignment with the four research hypotheses of the study, and they should serve as a compelling call to action for educators, scholars, and policymakers, urging them to implement necessary reforms in the field within the context of Qatar. Before delving into the research hypotheses, it is essential to examine the descriptive analysis of teachers’ responses concerning the different teaching barriers, namely student-related, technology-related, school-related, and teaching-related. This step is crucial for gaining an understanding of which barrier presents the greatest challenge to teachers.

The results indicate that of the obstacles linked to students, the most significant challenge for teachers is the issue of “inadequate sleep among students” (mean = 3.35, S.D. = 1.08). In terms of technology-related hindrances, “insufficient internet bandwidth or speed” (mean = 2.60, S.D. = 1.24) is the foremost challenge. Concerning school-related factors, the greatest challenge arises from the “pressure to prepare students for exams” (mean = 2.69, S.D. = 1.29). Lastly, regarding barriers connected to instruction, the most prominent challenge is “teachers having an excessive number of teaching hours” (mean score of 3.34 and a standard deviation of 1.08).

5.1 Structural model and hypothesis testing

In our SEM, the construct “STEM teaching” was employed as a dependent observed variable while the other barriers (student-related, school-related, technology-related, and instruction-related) were considered as independent observed variables. We utilized the maximum-likelihood method for estimating the model’s parameters, and all analyses were based on the variance-covariance matrices. The Goodness-of-Fit model was established and found to be satisfactory ( Hair et al., 2012 ). The Goodness-of-Fit indices fell within the acceptable range, which includes criteria such as chi-squared divided by degrees of freedom (χ2 / DF) < 5, Goodness-of-Fit Index (GFI) > 0.9, Adjusted Goodness-of-Fit Index (AGFI) > 0.8, Comparative Fit Index (CFI) > 0.9, Root Mean Square Residuals (RMSR) < 0.1, Root Mean Square Error of Approximation (RMSEA) < 0.08, Normed Fit Index (NFI) > 0.9, and Parsimony Normed Fit Index (PNFI) > 0.6 (refer to Table 3 ). In summary, the structural model’s good fit has been verified, paving the way for further examination of the structural model.

Table 3. Measures of goodness-of-fit.

Figure 3 and Table 4 present the results of the SEM analysis. The findings indicate that all the teaching barriers [i.e., (student-related: β = −0.243, p < 0.001); (school-related: β = −0.122, p < 0.001), (technology-related: β = −0.123, p = 0.040); and (instruction-related: β = −0.112, p < 0.018)] were negatively related to teachers’ STEM teaching. These results illustrated that all the hypotheses formulated in the study have been supported ( Table 4 ). All the path coefficients established emerged as significant at 0.05 level. Among the various obstacles, it appears that the most formidable challenges for high school STEM teachers are related to students (β = −0.243, p < 0.001). Teachers reported several student-related barriers, including students lacking the necessary skills and knowledge, students not getting sufficient sleep, classroom disruptions caused by students, and a lack of student interest.

Figure 3. Diagrammatic representation of SEM approach, illustrating the correlation between teachers’ STEM teaching and associated barriers.

Table 4. Results from SEM.

6 Discussion

This study delves into the barriers that high school teachers in Qatar encounter in teaching STEM subjects. Our research examined a series of variables, including those related to students, technology, the school environment, and instructional factors from teachers’ perspectives. As was stated previously, the SCT and AT provided the theoretical foundation for exploring these factors ( Heffernan, 1988 ). The research findings presented below are interpreted through the lenses of SCT and AT, which serve as the theoretical models underpinning our study. AT aided in comprehending how teachers attribute challenges in STEM teaching to individual and contextual factors. On the other hand, SCT furnished a valuable framework for understanding what social and cognitive factors affected STEM teaching and – similar to AT – offered insights into personal and environmental barriers. Both models were useful in exploring the significant inter-relationships within the teaching context (i.e., STEM teaching and associated barriers).

The findings derived from the present study indicated that student-related teaching barriers are negatively correlated to STEM teaching. The results disclosed three specific barriers to STEM teaching as reported by teachers: students’ lack of the required skills (mean = 3.34), students’ lack of the required knowledge (mean = 3.34), and students not having enough sleep (mean = 3.45). These results are in alignment with recent research conducted by Tran and Moskovsky (2022) and Børte et al. (2023) . These studies have unveiled teaching barriers associated with students encountering challenges in solving STEM-related problems, displaying lower academic performance, and struggling to apply their knowledge to independent STEM-related tasks. Whether or not this could be an indication of declining interest among students in STEM learning is yet to be confirmed by future research. Further, empirical research is necessary to delve into the underlying causes and mechanisms that perpetuate these challenges.

Results suggest that technology-related teaching barriers are negatively correlated to STEM teaching. Teachers cited obstacles associated with the availability of technical resources and technical assistance/support. While teachers in Qatar emphasized the importance of having access to technology resources, they also reported that schools often lacked suitable or sufficient educational software ( Moyo, 2017 ). Additionally, teachers indicated they had limited access to information and communication technology (ICT) infrastructure due to a restricted curriculum ( Moyo, 2017 ). Alshaboul et al. (2022) report that teachers’ positive or negative beliefs also play a significant role in determining their access to electronic devices/technology in the classroom.

Discomfort and inconvenience in integrating/using technology in the classroom can be considered technology-related barriers to STEM teaching. Various factors may contribute to this, including insufficient skills, such as a lack of self-efficacy, and confidence, difficulties in classroom management, or appropriate online assessments, concerns about privacy, and a shortage of effective ICT-based training. According to Al-Thani et al. (2021) , there is a notable absence of professional development (PD) opportunities in Qatar, and the existing PD strategies lack clear direction, purpose, or progress. Findings from a study conducted by Said et al. (2023) , which involved 245 preparatory and secondary school teachers from 16 different schools in Qatar, highlight the pressing need for substantial PD to help teachers deliver STEM effectively. Teachers also emphasize the necessity for adequate PD to address pedagogical challenges associated with the adoption of new technology-enhanced teaching methods ( Said et al., 2023 ).

Teachers also expressed a desire for improved teacher training workshops that are held annually but repetitively ( Al-Thani et al., 2021 ). Certain studies advocated for validated models that assist teachers in overcoming technology-related barriers and enhancing effective pedagogical delivery. One such model is the mentoring model, which involves providing professional support from experienced teachers to newly hired teachers ( Abu-Tineh and Sadiq, 2018 ). Similarly, Said et al. (2023) focused on teachers’ PD using the Technological Pedagogical and Content Knowledge (TPACK) model. This model helps teachers effectively use/integrate technology during instruction. Another noteworthy model is PICRAT, which is student-centered, pedagogy-driven, tailored to specific contexts, and practical for teachers as it guides all considerations for effective technology use in classrooms ( Kimmons et al., 2020 ). In the PICRAT model, “PIC” stands for Passive, Interactive, Creative Learning, and it refers to how students engage with technology within a specific educational context or field. On the other hand, “RAT” stands for Replacement, Amplification, and Transformation, and it signifies the influence of technology on a teacher’s practices when it’s integrated into their teaching methods ( Kimmons et al., 2020 ). Although there are several PD models for effective technology integration and combating technology-related barriers, only the TPACK model and mentoring model have been reported in the context of Qatar.

The third variable that we investigated, namely school-related teaching barriers, was found to have a negative correlation with STEM teaching. Teachers reported various school-related challenges, including the pressure to prepare students for exams, constraints related to the budget and the administration when accessing adequate teaching materials, concerns about the school environment, dealing with overcrowded classrooms, and facing limitations with inadequate school laboratories. These results echo findings in a recent study that looked at the context of Qatar by Sellami et al. (2022) . While the influence of school-related variables and their connection with STEM in STEM Qatar is a largely understudied area, some recommendations to address the relevant challenges are proposed in this study. For instance, the issue of limited access to adequate teaching resources could potentially be resolved by enhancing school libraries through the expansion of library resources and the improvement of information technology facilities ( Gunasekera and Balasubramani, 2020 ).

To address the issue of the pressure teachers feel in preparing students for exams, potential remedies include stress management interventions, such as cognitive-behavioral-based and mindfulness-based interventions ( von Keyserlingk et al., 2020 ). Cognitive-behavioral-based interventions involve cognitive training and the practice of strategic behaviors, equipping teachers with both knowledge and skills to effectively manage work-related stress ( von Keyserlingk et al., 2020 ). On the other hand, mindfulness-based interventions emphasize cognitive and behavioral strategies that focus on the experience of feelings and thoughts, rather than the specific content of those thoughts. These strategies aim to promote awareness and acceptance without judgment, making them integral components of mindfulness-based approaches ( von Keyserlingk et al., 2020 ).

Instruction-related teaching barriers have also been identified as having a negative correlation with STEM teaching. Teachers reported several challenges, including inadequate training in STEM education and a lack of pedagogical models tailored for STEM teaching. They also highlighted issues related to the imposed school curricula, excessive teaching hours, and a shortage of teaching materials. Existing literature demonstrates a positive relationship between the pressure stemming from imposed curricula and the perceived stress among teachers ( Putwain and von der Embse, 2019 ; von Keyserlingk et al., 2020 ). Research has also shown a negative relationship between teachers’ self-efficacy and their perceived stress ( Putwain and von der Embse, 2019 ). In simple terms, when teachers possess a high level of self-efficacy in STEM, they tend to experience less stress in response to curriculum changes ( von Keyserlingk et al., 2020 ). This underscores the importance of implementing PD programs for teachers, specifically targeting STEM education, to enhance their self-efficacy and better equip them to handle curriculum changes with reduced stress. The literature has also shown that excessive teaching hours constitute a real challenge for teachers ( Ismail et al., 2019 ). Demonstrably, this challenge has been consistently cited as a significant factor that greatly impacts teachers’ motivation to teach STEM subjects contributes to increased stress levels, and leads to lower job satisfaction among teachers when they are teaching STEM ( von Keyserlingk et al., 2020 ).

A comprehensive systematic review that drew data from 25 articles spanning the globe also reinforces the importance of providing support to teachers to enhance their capacity to implement STEM education effectively ( Margot and Kettler, 2019 ). This support includes collaborations with colleagues, ensuring access to well-crafted curricula, receiving support from the school, drawing upon past experiences, and having access to impactful professional development opportunities ( Margot and Kettler, 2019 ). As a result of these study findings, there is a clear and compelling need for school management to offer robust support to teachers. This support should encompass the provision of PD programs geared toward enhancing their skills in STEM education, as well as implementing stress management interventions to help teachers effectively manage the stress associated with their teaching responsibilities ( Karkouti et al., 2022 ).

Conclusively, the study’s main limitations stem from its exclusive reliance on quantitative survey data, specifically from high school teachers in Qatar, looking at their perceptions of challenges to STEM teaching. To gain a more informed insight and understanding of the factors influencing technology integration, the study would benefit from also utilizing qualitative data. For instance, conducting focus group interviews, in-depth one-on-one discussions, and follow-up interviews would enable an in-depth exploration of the underlying reasons behind these barriers. Another limitation is that the study primarily focuses on high school teachers’ perspectives, overlooking those of educators in lower grade levels. Incorporating data from primary and preparatory teachers would broaden the study’s insights and offer a comparative viewpoint. It is worth noting that different results and conclusions might arise when considering teachers with diverse demographics. However, we believe that the study’s reliability is supported by robust statistical analysis, using a more stringent significance level (e.g., p < 0.01). Furthermore, it is important to acknowledge the need for a longitudinal analysis of teachers’ perceptions of barriers to STEM instruction. Because teachers’ beliefs and attitudes change and evolve, a longitudinal study would capture these shifts and changes, and provide valuable insights into long-term trends in STEM education.

7 Conclusion and recommendations

Teachers are the cornerstone of educational excellence and hold significant sway over students’ academic achievements in STEM. Specifically, the teaching methods utilized by teachers and their skillful application in the classroom play a pivotal role in influencing whether students choose to pursue and persist in STEM fields of study and future careers. Therefore, it is important to understand teachers’ experiences of teaching STEM and the challenges they encounter. Guided by SCT and AT, this study identified a range of factors impeding STEM teaching: school-related, student-related, technology-related, and teaching-related barriers.

This research intends to explore the experiences of high school STEM teachers in Qatar, focusing specifically on the barriers they face in teaching STEM. The research findings underscore the importance of barriers related to schools, students, technology, and teaching methods in the context of STEM teaching within the classroom. Additionally, the study highlighted that student-related barriers were the most prominent impediments affecting STEM instruction. We believe that these findings provide crucial insights that can inform the development of effective STEM learning practices in high schools in Qatar.

Overall, this study calls for investing in teachers’ knowledge and expertise and for the need to provide support for them in terms of emotional, informational, instrumentational, and appraisal aspects in Qatar. Emotional support entails sharing personal experiences, demonstrating empathy toward teachers, and implementing effective stress management strategies to assist them in coping with work-related stress. Informational support involves creating well-thought-out plans and recommending actions to facilitate problem-solving. Instrumental support encompasses offering tangible assistance, direct aid, and PD programs to enable teachers to reach their objectives. Equally significant is the concept of appraisal support, which nurtures an environment promoting self-evaluation, constructive feedback, and affirmation, all contributing to enhancing teachers’ motivation and overall well-being.

Data availability statement

The original contributions presented in this study are included in this article/supplementary material, further inquiries can be directed to the corresponding author.

Ethics statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of Qatar University (QU-IRB 1424-EA/20) on 1 March 2020. The participants provided written informed consent for participation in the study.

Authors contributions

AS: Methodology, Writing – review and editing, Conceptualization, Funding acquisition, Project administration. MS: Formal analysis, Methodology, Writing – original draft. JB: Formal analysis, Writing – review and editing. ZA: Methodology, Supervision, Writing – review and editing.

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The project was funded by the Qatar University (Reference: QUCG-SESRI-20/21-1). This research has been partially supported by Qatar University Exceptional Grant (Ref.: QU-ERC-23_24-1) entitled “Student interest and perseverance in STEM-related fields of study and Careers” from Qatar University.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords : teachers, teaching barriers, high school, STEM education, structural equation modeling (SEM)

Citation: Sellami A, Santhosh M, Bhadra J and Ahmad Z (2024) Teachers’ perceptions of the barriers to STEM teaching in Qatar’s secondary schools: a structural equation modeling analysis. Front. Educ. 9:1333669. doi: 10.3389/feduc.2024.1333669

Received: 05 November 2023; Accepted: 08 March 2024; Published: 04 April 2024.

Reviewed by:

Copyright © 2024 Sellami, Santhosh, Bhadra and Ahmad. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Zubair Ahmad, [email protected]

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Leaders weigh in on where we are and what’s next

The explosion of generative AI technology over the past year and a half is raising big questions about how these tools will impact higher education. Across Harvard, members of the community have been exploring how GenAI will change the ways we teach, learn, research, and work.

As part of this effort, the Office of the Provost has convened three working groups . They will discuss questions, share innovations, and evolve guidance and community resources. They are:

The Teaching and Learning Group , chaired by Bharat Anand , vice provost for advances in learning and the Henry R. Byers Professor of Business Administration at Harvard Business School. This group seeks to share resources, identify emerging best practices, guide policies, and support the development of tools to address common challenges among faculty and students.
The Research and Scholarship Group , chaired by John Shaw , vice provost for research, Harry C. Dudley Professor of Structural and Economic Geology in the Earth and Planetary Sciences Department, and professor of environmental science and engineering in the Paulson School of Engineering and Applied Science. It focuses on how to enable, and support the integrity of, scholarly activities with generative AI tools.
T he Administration and Operations Group , chaired by Klara Jelinkova , vice president and University chief information officer. It is charged with addressing information security, data privacy, procurement, and administration and organizational efficiencies.

Klara Jelinkova, Bharat Anand, and John Shaw.

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The Gazette spoke with Anand, Shaw, and Jelinkova to understand more about the work of these groups and what’s next in generative AI at Harvard.

When generative AI tools first emerged, we saw universities respond in a variety of ways — from encouraging experimentation to prohibiting their use. What was Harvard’s overall approach?

Shaw: From the outset, Harvard has embraced the prospective benefits that GenAI offers to teaching, research, and administration across the University, while being mindful of the potential pitfalls. As a University, our mission is to help enable discovery and innovation, so we had a mandate to actively engage. We set some initial, broad policies that helped guide us, and have worked directly with groups across the institution to provide tools and resources to inspire exploration.

Jelinkova: The rapid emergence of these tools meant the University needed to react quickly, to provide both tools for innovation and experimentation and guidelines to ensure their responsible use. We rapidly built an AI Sandbox to enable faculty, students, and staff to experiment with multiple large language models in a secure environment. We also worked with external vendors to acquire enterprise licenses for a variety of tools to meet many different use cases. Through working groups, we were able to learn, aggregate and collate use cases for AI in teaching, learning, administration, and research. This coordinated, collective, and strategic approach has put Harvard ahead of many peers in higher education.

Anand: Teaching and learning are fundamentally decentralized activities. So our approach was to ask: First, how can we ensure that local experimentation by faculty and staff is enabled as much as possible; and second, how can we ensure that it’s consistent with University policies on IP, copyright, and security? We also wanted to ensure that novel emerging practices were shared across Schools, rather than remaining siloed.

What do these tools mean for faculty, in terms of the challenges they pose or the opportunities they offer? Is there anything you’re particularly excited about?

Anand: Let’s start with some salient challenges. How do we first sift through the hype that’s accompanied GenAI? How can we make it easy for faculty to use GenAI tools in their classrooms without overburdening them with yet another technology? How can one address real concerns about GenAI’s impact?

While we’re still early in this journey, many compelling opportunities — and more importantly, some systematic ways of thinking about them — are emerging. Various Harvard faculty have leaned into experimenting with LLMs in their classrooms. Our team has now interviewed over 30 colleagues across Harvard and curated short videos that capture their learnings. I encourage everyone to view these materials on the new GenAI site; they are remarkable in their depth and breadth of insight.

Here’s a sample: While LLMs are commonly used for Q&A, our faculty have creatively used them for a broader variety of tasks, such as simulating tutors that guide learning by asking questions, simulating instructional designers to provide active learning tips, and simulating student voices to predict how a class discussion might flow, thus aiding in lesson preparation. Others demonstrate how more sophisticated prompts or “prompt engineering” are often necessary to yield more sophisticated LLM responses, and how LLMs can extend well beyond text-based responses to visuals, simulations, coding, and games. And several faculty show how LLMs can help overcome subtle yet important learning frictions like skill gaps in coding, language literacy, or math.

Do these tools offer students an opportunity to support or expand upon their learning?

Anand: Yes. GenAI represents a unique area of innovation where students and faculty are working together. Many colleagues are incorporating student feedback into the GenAI portions of their curriculum or making their own GenAI tools available to students. Since GenAI is new, the pedagogical path is not yet well defined; students have an opportunity to make their voices heard, as co-creators, on what they think the future of their learning should look like.

Beyond this, we’re starting to see other learning benefits. Importantly, GenAI can reach beyond a lecture hall. Thoughtful prompt engineering can turn even publicly available GenAI tools into tutorbots that generate interactive practice problems, act as expert conversational aids for material review, or increase TA teams’ capacity. That means both that the classroom is expanding and that more of it is in students’ hands. There’s also evidence that these bots field more questions than teaching teams can normally address and can be more comfortable and accessible for some students.

Of course, we need to identify and counter harmful patterns. There is a risk, in this early and enthusiastic period, of sparking over-reliance on GenAI. Students must critically evaluate how and where they use it, given its possibility of inaccurate or inappropriate responses, and should heed the areas where their style of cognition outperforms AI. One other thing to watch out for is user divide: Some students will graduate with vastly better prompt engineering skills than others, an inequality that will only magnify in the workforce.

What are the main questions your group has been tackling?

Anand: Our group divided its work into three subgroups focused on policy, tools, and resources. We’ve helped guide initial policies to ensure safe and responsible use; begun curating resources for faculty in a One Harvard repository ; and are exploring which tools the University should invest in or develop to ensure that educators and researchers can continue to advance their work.

In the fall, we focused on supporting and guiding HUIT’s development of the AI Sandbox. The Harvard Initiative for Learning and Teaching’s annual conference , which focused exclusively on GenAI, had its highest participation in 10 years. Recently, we’ve been working with the research group to inform the development of tools that promise broad, generalizable use for faculty (e.g., tutorbots).

What has your group focused on in discussions so far about generative AI tools’ use in research?

Shaw: Our group has some incredible strength in researchers who are at the cutting edge of GenAI development and applications, but also includes voices that help us understand the real barriers to faculty and students starting to use these tools in their own research and scholarship. Working with the other teams, we have focused on supporting development and use of the GenAI sandbox, examining IP and security issues, and learning from different groups across campus how they are using these tools to innovate.

Are there key areas of focus for your group in the coming months?

Shaw: We are focused on establishing programs — such as the new GenAI Milton Fund track — to help support innovation in the application of these tools across the wide range of scholarship on our campus. We are also working with the College to develop new programs to help support students who wish to engage with faculty on GenAI-enabled projects. We aim to find ways to convene students and scholars to share their experiences and build a stronger community of practitioners across campus.

What types of administration and operations questions are your group is exploring, and what type of opportunities do you see in this space?

Jelinkova: By using the group to share learnings from across Schools and units, we can better provide technologies to meet the community’s needs while ensuring the most responsible and sustainable use of the University’s financial resources. The connections within this group also inform the guidelines that we provide; by learning how generative AI is being used in different contexts, we can develop best practices and stay alert to emerging risks. There are new tools becoming available almost every day, and many exciting experiments and pilots happening across Harvard, so it’s important to regularly review and update the guidance we provide to our community.

Can you talk a bit about what has come out of these discussions, or other exciting things to come?

Jelinkova: Because this technology is rapidly evolving, we are continually tracking the release of new tools and working with our vendors as well as open-source efforts to ensure we are best supporting the University’s needs. We’re developing more guidance and hosting information sessions on helping people to understand the AI landscape and how to choose the right tool for their task. Beyond tools, we’re also working to build connections across Harvard to support collaboration, including a recently launched AI community of practice . We are capturing valuable findings from emerging technology pilot programs in HUIT , the EVP area , and across Schools. And we are now thinking about how those findings can inform guiding principles and best practices to better support staff.

While the GenAI groups are investigating these questions, Harvard faculty and scholars are also on the forefront of research in this space. Can you talk a bit about some of the interesting research happening across the University in AI more broadly ?

Shaw: Harvard has made deep investments in the development and application of AI across our campus, in our Schools, initiatives, and institutes — such as the Kempner Institute and Harvard Data Science Initiative. In addition, there is a critical role for us to play in examining and guiding the ethics of AI applications — and our strengths in the Safra and Berkman Klein centers, as examples, can be leading voices in this area.

What would be your advice for members of our community who are interested in learning more about generative AI tools?

Anand: I’d encourage our community to view the resources available on the new Generative AI @ Harvard website , to better understand how GenAI tools might benefit you.

There’s also no substitute for experimentation with these tools to learn what works, what does not, and how to tailor them for maximal benefit for your particular needs. And of course, please know and respect University policies around copyright and security.

We’re in the early stages of this journey at Harvard, but it’s exciting.

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In a study supported by a five-year, $2.4 million grant from the National Science Foundation, Luis Leyva , associate professor of mathematics education and STEM higher education at Vanderbilt Peabody College of education and human development , has made critical progress in research on racial equity for undergraduate Latin* students as mathematics learners and aspiring STEM majors. (Note: The term Latin* responds to (mis)use of Latinx as a gender-neutral term originally intended for explicit inclusion among gender nonconforming peoples of Latin American origin and descent. The asterisk in Latin∗ considers fluidity in gender identities across the Latin American diaspora.)

Leyva directs the P ower, R esistance & I dentity in S TE M Education (PRISM) Research Lab at Vanderbilt, which houses various research projects that build theory and inform practice about equitable educational opportunities in undergraduate STEM with specific attention to issues of intersectionality. Several projects focus on exploring racial and intersectional justice for undergraduate Latin* students as learners in mathematics classrooms and as aspiring STEM majors.

The most recent project is Transformative Inclusion in Postsecondary STEM (TIPS): Towards Justice . Now in its third year, TIPS examines educational practices across STEM departments at colleges and universities with a federal designation as Hispanic-Serving Institutions (HSIs). The project is a collaboration between Vanderbilt and Sonoma State University, an institution that recently received the HSI designation. Leyva serves as a co-principal investigator and directs educational research activities in TIPS.

Leyva and his team are engaged in a research-practice partnership with faculty in the Department of Mathematics & Statistics at Sonoma State. The partnership’s goals are to characterize and develop practices that enhance racial equity to better serve undergraduate Latin* students. The TIPS research has focused on practices of classroom instruction and student support, specifically in courses that are gateways to mathematics and other STEM majors (e.g., calculus, introduction to proofs).

Latin* students in gateway mathematics courses at Sonoma State and the faculty who teach the courses are participants in the TIPS research study. Leyva and his team have collected various types of data about participants’ perspectives and experiences regarding what it means for Latin* students to be served as mathematics learners at HSIs. These data include interviews, classroom observations, and journaling. Using an intersectional lens, the team seeks to understand how race, gender, and other dimensions of social identity shape differences in how Latin* students experience supportive practices in mathematics.

Leyva has disseminated insights from preliminary analyses of TIPS research data at national conferences and invited lectures across the country. Notably, Leyva has published three conference proceeding papers . He also delivered presentations at the Charles A. Dana Center at The University of Texas at Austin and the James L. Curtis Institute for Race & Belonging at Albion College, where he was the Hispanic Heritage Month speaker for the college’s “Dimensions of Diversity” Lecture Series in 2023. Leyva was featured on an episode of the ¿ Qué Pasa, HSIs? podcast , which highlights educational research, practices, and policies for the advancement of racial equity at HSIs. The TIPS research team has also shared project analyses during the Department of Mathematics & Statistics’ colloquium series at Sonoma State.

Findings from the TIPS project’s single-institution case study in gateway mathematics courses at Sonoma State will guide next steps in the research process. Leyva and his team plan to examine the role that practices of racial equity played in Latin* students’ persistence as STEM majors. The team will also examine variation in the development of these equitable practices across different STEM departments with unique disciplinary cultures as well as different types of HSIs (e.g., two-year colleges, research-intensive universities). These contributions aim to enhance HSIs’ institutional missions of providing culturally-responsive learning opportunities, particularly through the robust transformation of organizational and pedagogical practices for the advancement of racial equity and intersectional justice in STEM departments.

“I am excited about next steps in our collaborative work through the TIPS project and future research that promotes justice in undergraduate STEM across intersections of race, gender, sexuality, and other minoritized social differences,” Leyva said.

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Asia-Pacific STEM Teaching Practices pp 1–16 Cite as

Opportunities and Challenges of STEM Education

Ying-Shao Hsu 3 &
Su-Chi Fang 3
First Online: 13 November 2019

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14 Citations

In recent years, the ubiquitous calls for science, technology, engineering, and mathematics (STEM) education has increasingly encouraged educators and policymakers to promote STEM teaching and learning in classrooms. We reviewed research studies on integrated STEM in science education; most of the research findings showed a lack of concrete conclusions about the influence of integrated STEM. For instance, little is known about how and to what extent integrated STEM learning experiences may foster student creativity, support the development of higher order thinking skills, or impact their epistemological beliefs and views about science learning. Moreover, the review found only a few studies that looked into issues about the preparation of STEM teachers in their initial teacher education and professional development programs on integrated STEM. More research about the effectiveness of various teaching practices (e.g., instructional design, teaching strategies, etc.) is needed to help preservice and in-service teachers develop expertise for teaching integrated STEM.

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Ying-Shao Hsu is a visiting professor at University of Johannesburg, South Africa.

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References marked with an asterisk indicate the 26 studies included in the review

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Acknowledgments

This work was financially supported by the Institute for Research Excellence in Learning Sciences of National Taiwan Normal University from the Featured Areas Research Center Program within the framework of the Higher Education Sprout Project and Ministry of Science and Technology 107-2511-H-003-043-MY3 Project by the Ministry of Education in Taiwan.

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Hsu, YS., Fang, SC. (2019). Opportunities and Challenges of STEM Education. In: Hsu, YS., Yeh, YF. (eds) Asia-Pacific STEM Teaching Practices. Springer, Singapore. https://doi.org/10.1007/978-981-15-0768-7_1

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Igniting Innovation and Empowering Tomorrow's STEM Leaders

April 4, 2024 By Lauren Jenkins

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Two people posing for a photo with a person in a large, cartoonish robot costume at an indoor event.

More than 1,200 middle school and high school students from across Texas traveled to College Station from March 22-23, 2024, to showcase their science and engineering projects at the Texas Science and Engineering Fair (TXSEF) .

Students competed at regional science and engineering fairs from January to March before advancing to the state fair held at Texas A&M University. This year’s fair was held at the Texas A&M University Student Recreation Center with an awards ceremony at Rudder Auditorium. It was co-sponsored by the Texas Workforce Commission, ExxonMobil and Texas A&M Engineering.

"The Texas Science and Engineering Fair is a celebration of innovation and boundless creativity, of finalists as they proudly showcase their research skills and projects in science and engineering,” said Dr. Cindy Lawley, assistant vice chancellor for academic and outreach programs for Texas A&M Engineering. “We witness not only the culmination of their hard work but also the unwavering support from dedicated families and educators who are inspiring a new generation of thinkers and innovators poised to shape the future with their ingenuity and determination."

Night at the ZACH

To kick off the weekend, TXSEF participants and their families — nearly 6,000 people —descended upon the Zachry Engineering Education Complex (ZACH) to experience Night at the ZACH. Hosted inside and outside Zachry, Night at the ZACH features exhibitors showcasing their departments, organizations, current projects, and/or expertise with hands-on activities designed to get students pumped about engineering and science.

Night at the ZACH ignites inspiration, fostering connections that transcend disciplines and ignite a passion for pushing the boundaries of knowledge and possibility.

Crowd favorites included the Lockheed Martin F-35 Cockpit Demonstration Simulator; ExxonMobil’s robotic dog Sparky; NASA’s Exploration trailer; Dell Tech Rally Mobile; and photo opportunities with Reveille X, the First Lady of Aggieland.

"At Night at the ZACH, TXSEF finalists have the opportunity to engage with industry and academia, fueling their curiosity and igniting new avenues of exploration. Yet, beyond the excitement of discovery lies a moment of celebration — a celebration of their remarkable journey to the Texas Science and Engineering Fair,” said Shelly Tornquist, director of Spark! PK-12 Engineering Education Outreach. “Night at the ZACH ignites inspiration, fostering connections that transcend disciplines and ignite a passion for pushing the boundaries of knowledge and possibility."

In addition to student organizations like the Texas A&M Solar Racing Team and the Texas A&M Sounding Rocketry Team, Night at the ZACH welcomed senior capstone projects from the Department of Electrical & Computer Engineering. Students shared information about their projects, academic journeys, and experiences as engineering students.

Competition Day

On competition day, finalists presented their projects to over 350 judges with expertise in fields ranging from physical sciences to engineering to life sciences. Finalists competed as an individual or a team in either the junior division (middle school students) or senior division (high school students), where they presented on their project’s scientific basis, the interpretation and limitations of the results, and their conclusions.

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"TXSEF is more than just a culmination of months of hard work; it's a day where young minds converge, showcasing their ingenuity and dedication to solving the world's most pressing challenges,” Tornquist said. “As students present their research and projects, the atmosphere is electric with innovation and determination. Each presentation is not just a moment in time but a testament to the endless possibilities that STEM offers."

Several special awards and scholarships were awarded to select projects on the competition floor. These awards were supported by TXSEF sponsors and industry partners and recognized before the awards ceremony.

After a full day of judging, finalists and families made their way to Rudder Auditorium, filling it to capacity. The Spark! PK-12 Engineering Education Outreach robot Spark-E entertained the crowd with dancing and games.

In addition to first through third place awards in the 22 categories in both junior and senior divisions, best of state for both life sciences and physical sciences was awarded in both divisions, plus an honorable mention for each category.

Finalists from the senior division were selected to attend the Governor's Science and Technology Champions Academy and finalists from the junior division were selected to attend the Thermo Fisher Scientific Junior Innovators Challenge (JIC). Twelve (12) projects from the senior division advance to the Regeneron International Science and Engineering Fair (ISEF) held May 11-17, 2024, in Los Angeles, Calif.

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Engineering students among the winners at March 26 Auburn Student Research Symposium

Published: Apr 5, 2024 10:35 AM

By Joe McAdory

Sixty-four students, including five from the Samuel Ginn College of Engineering, earned awards for oral and poster presentations of their research and creative scholarship following the 2024 Auburn University Student Research Symposium held March 26 at the Melton Student Center. Awards were presented in an April 2 ceremony.

Roughly 450 graduate and undergraduate students from Auburn University and Auburn University at Montgomery participated in the annual event, which showcases a broad spectrum of student research and scholarship from a variety of disciplines.

“The Samuel Ginn College of Engineering provides the best student-centered engineering experience in America and part of that experience is research,” said Allan David, interim associate dean for research. “Whether it’s hands-on work in a laboratory, crafting ideas into visual elements for poster presentations, or delivering project summaries in-person before an audience, research remains the cornerstone of the academic process. It’s how we develop fresh ideas that evolve into solutions to everyday problems. The Auburn University Research Symposium is an opportunity each spring for students to not only showcase their ideas but also exchange them. Congratulations to all students involved for their hard work and we look forward to one day seeing the fruits of their labor.”

The university recognized the best oral and poster presentations university-wide at the graduate and undergraduate levels in STEM-related and human sciences, social sciences, creative arts, nursing and humanities-related disciplines. Top researchers from each college were also recognized.

Daniel Meadows, a graduate student in chemical engineering under the mentorship of Professor Virginia Davis, won second place among all graduate STEM entries for his oral presentation, “Selective extraction of ethylene vinyl alcohol (EVOH) from K-cup plastic waste.”

Engineering oral presentation winners were Tori Phillips, a graduate student in chemical engineering under the mentorship of Assistant Professor Jean-Francis Louf for the entry, “Connecting Plant Root Architecture and Water Transport Abilities Using a Transparent Soil,” and Erik Mulder, an undergraduate in aerospace engineering under the mentorship of Assistant Professor Davide Guzzetti, for the entry, “Analyzing Data-Driven CR3BP Representations for Immersive Astrodynamics Catalogs.”

Auburn Engineering’s poster presentation winners were Ashish Bhattarai, a graduate student in biosystems engineering , working with Presidential Graduate Research Fellow Sagar Kafle and under the mentorship of Professor Sushil Adhikari, for the entry, “Linear regression model to predict the feeding rate in a laboratory-scale gasifier,” and Emily Kimbrell, an undergraduate in computer science and software engineering for the presentation, “A centralized user interface to display satellite mega-constellations in a gamified system.”

“Not only is this an opportunity for students to present what they have learned through their research experiences to a broad audience, but the symposium empowers participants to share their thoughts, discoveries and creative work,” said Lorenzo Cremaschi, professor of mechanical engineering and Auburn University’s director of undergraduate research. “This year, the first-rate presentations provided a forum for cross-college networking. The conversations in the rooms were lively and vibrant. I thank all the presenters and judges who participated in the symposium, making it a truly engaging opportunity. I congratulate the award winners for their outstanding work during what is becoming a signature event for the University.”

A complete list of winners, along with titles of their projects, is available on the Student Research Symposium web site .

The annual Auburn University Student Research Symposium, held March 26 in the Melton Student Center, drew 450 entries.

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From coast to coast: first-generation college students present research at California conference

Students, alumni share value of experiential learning for STEM career exploration

By GRACE HOGGARTH '22 on April 4, 2024

Students stand on coastline in Monterey, California

Three TU students shared a unique experience when they presented their research to a national audience for the first time at the Western Society of Naturalists conference in Monterey, California in November.

Senior Jayden Steward ’24, and alumni Troy Stern ’23 and Yuridia Gonzales ’23 research began in professor Will Ryan’s lab researching the evolutionary ecology of marine invertebrates. While in the field, they studied the roles of the environment and landscape on the lifecycles and population structure of sea anemones and hydrozoans in the ocean.

They collected samples of invasive sea anemones in Delaware and then hermit crabs, which play host to a specific kind of colonial hydrozoan, in Virginia.

Their goal was to understand how complex habitats like salt marshes shape connections between populations of these invertebrates, which can only move as far as their hermit crab hosts can walk. Their research also aimed to determine how competition between the colonies living on the same shell influenced the traits of those that survived.

Students and professor stand on beach in Wachapreague, Virginia

During the conference, TU students presented their research during an afternoon poster session, sat in on panel discussions, listened to individual talks from guest speakers and took part in inclusive discussions for first-generation college students.

Steward and his peers also ventured to the Monterey Bay aquarium and the Pacific Grove monarch butterfly sanctuary and conducted tide pool observations at Asilomar Beach.

For Steward in particular, this professional opportunity offered several firsts: flying in an airplane and exploring the U.S. beyond the East Coast. The biology major found that this was also an opportunity for him to broaden his horizons and visualize what it could be like to work in environments outside of Maryland and explore new career paths.

“It’s really enhanced my academic experience at TU. It’s given me new outlets and even has me considering grad school,” Steward says. “It’s overwhelmingly had a positive impact on my life. Not many college students can say they went to California to present research. I’m really grateful for it.”

Experiential learning and networking opportunities are invaluable for young researchers, particularly first-generation college students, like Steward, Stern and Gonzales.

Alexei Kolesnikov, director of the Office of Undergraduate Research and Creative Inquiry (OURCI), attests, “There is proven value in engaging in research and attending conferences for students. After a conference, students return with a deeper sense of professional identity in their field, a broader view of career options and a more-focused understanding of how their research can lead to further opportunities. Networking during conferences helps students connect with professionals and peers, enhancing their academic and career prospects."

This was true for Ryan when he got involved with the Western Society of Naturalists during his undergraduate career. Years down the line, he is still actively involved and spoke at this year’s conference to share insight into the importance of inclusive, safe and accessible fieldwork for the transgender and broader LGBTQ+ communities.

Ryan wanted to use this opportunity and his research lab to pay it forward to his students and guide them through the hidden curriculum that most first-generation college students are unaware of when they begin their academic journey.

“What I really wanted for them was what this conference had done for me as an undergraduate. I was a first-generation student and didn’t really understand college, let alone academia or how to be a scientist,” says Ryan. “Taking that idealized experimental design and trying to implement it into the world gives you a much greater appreciation for how hard won all the knowledge we have is. Providing students with these opportunities to actually do the work and see the way their life would be if they chose this path is the most important thing.”

The research Steward and his peers participated in was funded by a grant from the Fisher College of Science and Mathematics (FCSM) Endowment. Travel to the conference was jointly funded by the Office of Undergraduate Research & Creative Inquiry (OURCI), the FCSM and the Department of Biology. Students can explore additional learning opportunities through programs like experiential and advanced learning and TU Research Enhancement Program (TUREP) courses .

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169+ Exciting Qualitative Research Topics For STEM Students
Qualitative research topics for stem students are questions or issues that necessitate an in-depth exploration of people's experiences, beliefs, and behaviors. STEM students can use this approach to investigate societal impacts, ethical dilemmas, and user experiences related to scientific advancements and innovations.
55 Brilliant Research Topics For STEM Students
The major challenge many STEM students face in research writing is choosing a topic for research. Here are some reliable STEM topics to guide your research. Services. ... How Covid-19 affects people with digestive problems; Survey Research Topics For STEM Students. Below are some survey topics for qualitative research for stem students.
200+ Experimental Quantitative Research Topics For Stem Students
Here are 10 practical research topics for STEM students: Developing an affordable and sustainable water purification system for rural communities. Designing a low-cost, energy-efficient home heating and cooling system. Investigating strategies for reducing food waste in the supply chain and households.
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 ...
Factors Influencing Student STEM Learning: Self-Efficacy and ...
Social, motivational, and instructional factors impact students' outcomes in STEM learning and their career paths. Based on prior research and expectancy-value theory, the study further explored how multiple factors affect students in the context of integrated STEM learning. High school STEM teachers participated in summer professional development and taught integrated STEM to students ...
Researchers study challenges underrepresented STEM students face during
The most common concern for students was being infected with COVID-19 and spreading it to family members. They were also worried about noncompliance to COVID guidelines by many students on campus. Additional student concerns included apprehension over instructional quality during remote learning, impacts on social interaction, lack of hands-on ...
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.
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 ...
Undergraduate Research Experiences for STEM Students
Undergraduate Research Experiences for STEM Students provides a comprehensive overview of and insights about the current and rapidly evolving types of UREs, in an effort to improve understanding of the complexity of UREs in terms of their content, their surrounding context, the diversity of the student participants, and the opportunities for ...
Summary
They focus on significant, relevant problems of interest to STEM researchers and in some cases a broader community (e.g., civic engagement). ... Undergraduate Research Experiences for STEM Students provides a comprehensive overview of and insights about the current and rapidly evolving types of UREs, in an effort to improve understanding of the ...
Undergraduate Research Experiences for STEM Students: Successes
technology, engineering, and mathematics (STEM) education and careers. The findings from the research literature reported in Chapter 4 provide guidance to those designing both opportunities to improve practical and academic skills and opportunities for students to "try out" a professional role of interest.. Little research has been done that provides answers to mechanistic questions about ...
11 STEM Research Topics for High School Students
Engaging in research at an early stage not only hones critical thinking and problem-solving skills but also gives them a competitive edge in college application. 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.
Strengthening Research Experiences for Undergraduate STEM Students
There are many ongoing efforts to improve undergraduate science, technology, engineering, and mathematics (STEM) education that focus on increasing the active engagement of students and decreasing traditional lecture-based teaching. The study will explore what is known about student participation in UREs, best practices in UREs design, and ...
Evidence of STEM enactment effectiveness in Asian student learning
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).
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 ...
55 Brilliant Research Topics For STEM Students (2024)
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 fou...
Increasing access and opportunity in STEM crucial, say experts
Long cited the U.S. Bureau of Labor Statistics, which shows employment in STEM occupations has grown 79 percent in the past three decades. In addition, STEM jobs are projected to grow an additional 11 percent from 2020 to 2030. In Massachusetts alone, "40 percent of all employment revolves around innovation industries, such as clean energy ...
Trends and Hot Topics of STEM and STEM Education: a Co-word ...
This study explored research trends in science, technology, engineering, and mathematics (STEM) education. Descriptive analysis and co-word analysis were used to examine articles published in Social Science Citation Index journals from 2011 to 2020. From a search of the Web of Science database, a total of 761 articles were selected as target samples for analysis. A growing number of STEM ...
STEM Problem Solving: Inquiry, Concepts, and Reasoning
Further, existing research (for example, Gale et al., 2000) around STEM education focussed largely on description of students' learning experiences with insufficient attention given to the connections between disciplinary conceptual knowledge and inquiry processes that students use to arrive at solutions to problems. Clarity in the role of ...
Research-Based Practices for Engaging Students in STEM Learning
The MC 2 STEM graduation requirements state that in order to earn high school credit, students must achieve mastery (PDF) (greater than or equal to 90 percent in grades 9 and 10, and greater than or equal to 70 percent in grades 11 and 12) on each and every state standard. In addition, students must participate in 60 hours of community and/or ...
189+ Experimental Quantitative Research Topics For STEM Students
Here are 8 key points on how to do experimental research effectively. 1. Clear Research Focus. Begin by defining a clear and focused research question. A well-defined question provides a purpose and direction for your experiment, guiding your choices in variables and methodology. 2.
Frontiers
3 Theoretical framework. The conceptual foundation of this study is based on similar research, which delved into the perceptions of high school teachers regarding the obstacles to teaching STEM in Qatar, including student-related, technology-related, school-related, and instruction-related barriers in teaching STEM (Sellami et al., 2022).The study employed descriptive statistics and logistic ...
Exploring potential benefits, pitfalls of generative AI
This group seeks to share resources, identify emerging best practices, guide policies, and support the development of tools to address common challenges among faculty and students. The Research and Scholarship Group, chaired by John Shaw, vice provost for research, Harry C. Dudley Professor of Structural and Economic Geology in the Earth and ...
A common problem of STEM students
A common problem of STEM students. Fear of failing and not having the right answer is a common problem of STEM students. Especially if your class is their first STEM experience. In most other courses, students are expected to have the "right" answer. If they are paying attention and working hard, they should be able to get a "good ...
Leyva advances research on Hispanic-Serving Institutions with $2.4M
The TIPS research has focused on practices of classroom instruction and student support, specifically in courses that are gateways to mathematics and other STEM majors (e.g., calculus ...
STEM Students' Golden Opportunity
STEM (Science, Engineering, Technology and Math) students at Mt. SAC have a golden opportunity. The college received a five-year, $1 million grant from the National Science Foundation's (NSF) Advanced Technological Equation Program (ATE), and Mt. SAC plans to support 80 students through the first four years of the project. So far in the first three years, 54 students have been assisted in ...
Opportunities and Challenges of STEM Education
STEM education aims to help students develop their problem-solving competencies and computational thinking (e.g., English, 2017) through the use of science, technology, engineering, and mathematics and their associated practices to solve a real-world problem (e.g., Schnittka et al., 2016).During STEM learning, students act as an autonomous learner to self-regulate their problem-solving process ...
Igniting Innovation and Empowering Tomorrow's STEM Leaders
It was co-sponsored by the Texas Workforce Commission, ExxonMobil and Texas A&M Engineering. "The Texas Science and Engineering Fair is a celebration of innovation and boundless creativity, of finalists as they proudly showcase their research skills and projects in science and engineering," said Dr. Cindy Lawley, assistant vice chancellor for ...
Engineering students among the winners at March 26 Auburn Student
Sixty-four students, including five from the Samuel Ginn College of Engineering, earned awards for oral and poster presentations of their research and creative scholarship following the 2024 Auburn University Student Research Symposium held March 26 at the Melton Student Center. Awards were presented in an April 2 ceremony.
From coast to coast: first-generation college students present research
Not many college students can say they went to California to present research. I'm really grateful for it." Experiential learning and networking opportunities are invaluable for young researchers, particularly first-generation college students, like Steward, Stern and Gonzales.

161+ Exciting Qualitative Research Topics For STEM Students

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200+ Experimental Quantitative Research Topics For STEM Students In 2023

What Is STEM?

Why STEM Research Is Important?

How to Choose a Topic for STEM Research Paper

Step 1: Identify Your Interests

Step 2: Research Existing Topics

Step 3: Consider Real-World Problems

Step 4: Talk to Teachers and Mentors

Step 5: Narrow Down Your Topic

Qualitative Research Topics for STEM Students:

Easy Experimental Research Topics for STEM Students:

Research Topics for STEM Students in the Philippines:

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Research Topics for STEM Students in the Pandemic:

Research Topics for STEM Students Middle School

Technology Research Topics for STEM Students

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Experimental Research Topics for STEM Students About Plants

Qualitative Research Topics for STEM Students in the Philippines

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Quantitative Research Topics for STEM Students in the Philippines

Things That Must Keep In Mind While Writing Quantitative Research Title

1. Be Clear and Precise

2. Use Important Words

3. Avoid Confusing Words

4. Show Your Research Approach

5. Match Your Title with Your Research Questions

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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