161+ Exciting Qualitative Research Topics 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:

How to Find and Choose Good Qualitative Research Topics

  • 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.

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250+ Amazing Qualitative Research Topics for STEM Students

Students often focus on numbers and experiments in science, technology, engineering, and math (STEM). However, there’s one more side to explore that is similarly significant: subjective examination.

Qualitative research helps STEM students understand people’s thoughts, feelings, and experiences related to science and technology. Dissimilar to quantitative exploration, which manages numbers, subjective review examines the more profound implications behind things.

For STEM students, qualitative research has many benefits. It helps them think critically, understand others better, and see how science affects society. Through this blog series, we’ll investigate different research topics for STEM students, such as the moral side of biotechnology and the jobs of people in design.

Also Read :  270+ Best Physics Research Topics For High School Students. 

In this day and age, where science and society meet, we want assorted points of view. By embracing qualitative research, STEM students can turn out to be better-adjusted specialists prepared to handle the difficulties. Go along with us as we find new bits of knowledge and extend our seeing together.

Table of Contents

What Are Qualitative Research Topics

Qualitative research in STEM (Science, Technology, Engineering, and Mathematics) examines many different areas. It helps us understand how people interact with science and technology. These research topics explore how people feel and think about different scientific fields. They also examine ethical issues, how society is affected, and how people are at the center of STEM subjects.

How Do I Choose The Right Qualitative Research Topics for STEM Students?

qualitative research topics for senior high school students stem

Choosing the right qualitative research topics for STEM students involves considering several key factors to ensure the research is meaningful, relevant, and feasible. Here are some tips to help you select appropriate topics:

1. Interest and Passion

Urge understudies to pick subjects that interest them and line up with their interests in STEM fields. Exploring a topic they find captivating will inspire them all through the exploration cycle.

2. Relevance to Current Issues

Select subjects addressing recent concerns, difficulties, or patterns in the selected STEM discipline. This guarantees that the exploration adds to existing information and resolves genuine issues.

3. Feasibility

Think about the assets, time, and aptitude expected to direct the examination. Guarantee that the picked subject is plausible inside the limitations of the understudy’s abilities, accessible assets, and period.

4. Scope and Manageability

Pick subjects that are sufficiently wide and thin in scope. The examination question should be focused on being sensible in the accessible time and assets yet expansive enough to consider significant investigation and investigation.

5. Originality and Innovation

Urge understudies to investigate exceptional or inventive examination points that still can’t be widely contemplated. Unique exploration propels information and permits understudies to affect their field significantly.

6. Interdisciplinary Connections

Consider interdisciplinary themes that span different STEM teaches or converge with fields like sociologies, humanities, or ecological examinations. Interdisciplinary exploration encourages joint effort and offers a comprehensive comprehension of intricate issues.

7. Ethical Considerations

Guarantee that the picked subject complies with moral rules and standards for the STEM discipline. Address expected moral worries about human subjects, creature government assistance, natural effects, or information protection.

List of Qualitative Research Topics for STEM Students

Here is a comprehensive list of qualitative research topics for STEM students.

Biology Research Topics for STEM Students

  • The Impact of Climate Change on Wildlife in [Specific Region].
  • Understanding How Nature Can Bounce Back in [Specific Habitat].
  • What People Think About Changing Genes in Farming.
  • Looking at What’s Right or Wrong in Testing Animals for Medicine.
  • Learning About Tiny Creatures Living in Soil.
  • How Our Genes Can Make Us More Likely to Get Sick: A Simple Look.
  • What People Think is Okay About Editing Genes in Babies.
  • Checking Out How Plants and Tiny Creatures Help Each Other on Farms.
  • How People in Poor Countries See Science That Changes Living Things.
  • Seeing What People Get About How Life Changes Over Time.

Chemistry Research Topics for STEM Students

  • Looking at What People Think About Tiny Tech in Stuff We Use.
  • Checking Out How Schools Teach Eco-Friendly Chemistry.
  • Seeing What People Know About Keeping Workplaces Safe from Chemicals.
  • Understanding How Chemistry Helps Us Make Energy That Won’t Run Out.
  • Thinking About What’s Right and Wrong in Making Chemical Weapons.
  • Studying Different Ways to Use Liquids in Chemistry Experiments.
  • Seeing What People Think About Stuff Added to Food.
  • Finding Out What People Think About Recycling Chemicals.
  • Looking at How Chemicals Mess Up Cities.
  • Understanding How Chemistry Helps Make New Medicines.
  • Understanding What People Think About Nuclear Power as a Sustainable Energy Source.
  • Looking at What Different Cultures Think About Exploring Space.
  • Checking if Boys and Girls Get the Same Chance to Learn Physics.
  • Looking at What People Think About Tiny Bits of Energy Science.
  • Understanding How Physics Helps Us Make Renewable Energy.
  • Thinking About What’s Right and Wrong in Studying Tiny Bits of Matter.
  • Checking How Physics Helps Us See Inside Bodies.
  • Looking at How Scientists Talk About Space Stuff.
  • Understanding How Different People See Time.
  • Seeing What People Think About Smart Computers in Physics.


  • Looking at Whether Boys and Girls Get the Same Chance to Learn Engineering.
  • Understanding How Engineering Helps Us Build Things That Last.
  • Thinking About What’s Right and Wrong in Cars That Drive Themselves.
  • Studying How Engineers Make Things.
  • Seeing What People Think About New Medical Tools Made by Engineers.
  • Understanding How Different Cultures Deal with Water.
  • Thinking About Tough Choices in Making Smart Computers.
  • Looking at How Engineering Is Taught in Countryside Areas.
  • Checking How Engineers Help During Disasters.
  • Seeing What People Think About Making Stuff with 3D Printers.

Mathematics Qualitative Research Topics for STEM Students

  • Looking at Whether Boys and Girls Get the Same Chance to Learn Math.
  • Seeing How Different Cultures Solve Math Problems.
  • Understanding What’s Right and Wrong in Making Computer Rules.
  • Studying How Math is Taught in Poor Countries.
  • Seeing What People Think About Secret Codes and Keeping Data Safe.
  • Thinking About How Math Helps Make Art and Music.
  • Understanding How Different Groups Do Math.
  • Studying Why Some Students Worry About Math.
  • Checking How Math Helps Study Diseases.
  • Seeing How People in Different Cultures Do Math.

Interdisciplinary Topics

  • Where Biology and Engineering Meet in Body Movements.
  • Thinking About What’s Right and Wrong in Making Wearable Gadgets.
  • Studying Programs That Teach Different Sciences Together.
  • Seeing What People Think About Big Fixes for Climate Change.
  • Looking at How Math Helps Make Computers Work.
  • Understanding How Different Groups See Smart Computers and Robots.
  • Studying How Computers Help with Health Care Using Biology.
  • Checking How Learning Science Helps Fight Global Health Problems.
  • Learning About Native Knowledge about Nature.
  • Seeing What People Think About Talking to Computers.

Environmental Science Research Topics for STEM Students

  • Seeing What People Think About Green Energy.
  • Studying Projects That Protect Nature Made by Local Groups.
  • Checking How Native Knowledge Helps Take Care of Nature.
  • Understanding How Different Cultures Deal with Trash.
  • Looking at How Climate Change Affects People.
  • Studying How Schools Teach about Nature.
  • Seeing What People Think About Saving Wild Places.
  • Exploring How Regular People Help Watch Nature.
  • Understanding What Different Cultures Think About City Parks.
  • Looking at Movements That Fight for Fairness About Nature.

Computer Science

  • Understanding How Different Cultures See Keeping Information Safe.
  • Looking at Whether Computers Treat Men and Women Fairly.
  • Studying How Computer Classes Are Taught in Poor Countries.
  • Checking What People Think About Rules for Staying Safe Online.
  • Thinking About What’s Right and Wrong in Making Computers That Think for Themselves.
  • Understanding How Different Cultures Deal with Not Having Computers.
  • Studying How People and Computers Work Together in Fake Worlds.
  • Seeing What People Think About Keeping Computers Safe.
  • Looking at How Computer Science Helps with Health Information.
  • Understanding What People Think About Smart Computers Taking Jobs.

Technology Research Topics for STEM Students

  • Whether Men and Women Get the Same Chance to Use and Like Tech.
  • Seeing How Different Cultures Feel About New Technologies.
  • Studying How Schools Use Tech.
  • Checking What People Think About Making Cities Smart.
  • Thinking About What’s Right and Wrong in Using Body Measurements for Tech.
  • Understanding How Different Cultures Control the Internet.
  • Studying Why Older People Like or Dislike Tech.
  • Seeing What People Think About Rules for Flying Drones.
  • Exploring Native Knowledge of Tech That Helps Nature.
  • Understanding What Different Cultures Think About Health Gadgets You Wear.


  • Studying How Men and Women Make Farming Choices.
  • Looking at How Different Cultures Feel About Farming That Lasts.
  • Studying Programs That Teach Farmers.
  • Checking What People Think About Changing Food DNA.
  • Learning About Native Farming Knowledge.
  • Understanding How Different Cultures Feel About Bug Killers.
  • Studying How Farmers Work in Small Farms with Nature.
  • Checking What People Think About Farming Without Chemicals.
  • Looking at How Farming Helps Deal with Climate Changes.
  • Understanding What Different Cultures Think About Keeping Seeds and Different Plants.

Health Sciences Research Topics for STEM Students

  • Looking at Whether Men and Women Get the Same Healthcare.
  • Seeing How Different Cultures Feel About Treating the Mind.
  • Studying How Doctors and Patients Talk.
  • Checking What People Think About Vaccines.
  • Learning About Native Ways to Heal and Traditional Medicine.
  • Understanding How Different Cultures Deal with Dying.
  • Studying How Doctors Work in Country Areas.
  • Checking What People Think About Seeing a Doctor Online.
  • Exploring What’s Right and Wrong in Studying People.
  • Understanding How Different Cultures Feel About Services for Making Babies.

Social Sciences Research Topics for STEM Students

  • Studying How Men and Women Choose Jobs in Science, Technology, Engineering, and Math.
  • Looking at How Different Cultures Feel About Protecting Nature.
  • Studying Programs That Help People Learn Science, Technology, Engineering, and Math.
  • Checking What People Think About How Governments Make Science Rules.
  • Learning About Native Ideas on How Machines Change Things.
  • Understanding How Different Cultures Feel About Talking About Science.
  • Studying How Much People Know About Science in Different Groups.
  • Checking What People Think About Who Knows a Lot About Science.
  • Exploring What’s Right and Wrong in Reporting Science News.
  • Understanding How Different Cultures See Making Science Facts.


  • Studying How Boys’ and Girls’ Brains Grow and Work.
  • Looking at How Different Cultures See Feeling Bad About Mental Health Problems.
  • Studying How the Brain Can Change and Learn.
  • Checking What People Think About Machines That Connect to the Brain.
  • Seeing How the Brain Works in Addiction.
  • Understanding How Different Cultures Feel About People’s Different Brain Types.
  • Studying How Schools Teach Kids About Keeping Their Brains Healthy.
  • Checking What People Think About Making Brains Work Better.
  • Exploring What’s Right and Wrong in Studying Brains with Machines.
  • Understanding How Different Cultures Feel Pain and Deal with It.

Biomedical Engineering Research Topics for STEM Students

  • Studying Whether Men and Women Get Fair Treatment in Medical Engineering Research.
  • Looking at How Different Cultures See Making Medical Tools.
  • Studying Programs That Teach Medical Engineering.
  • Checking What People Think About Printing Body Parts.
  • Exploring How Medical Engineering Helps People Get Better.
  • Understanding How Different Cultures Feel About Tools That Help People.
  • Studying What’s Right and Wrong in Making People Better with Machines.
  • Checking What People Think About Keeping Medical Implants Safe.
  • Exploring Native Healing Tools.
  • Understanding How Different Cultures Deal with Medical Trash.

Materials Science

  • Studying Whether Men and Women Are Treated Fairly in Making New Materials.
  • Looking at How Different Cultures See Making Things That Last.
  • Studying Programs That Teach About Making Stuff.
  • Checking What People Think About Keeping Tiny Stuff Safe.
  • Exploring How Materials Help in Medicine.
  • Understanding How Different Cultures Feel About Reusing Stuff.
  • Studying What’s Right and Wrong in Studying Stuff.
  • Checking What People Think About Materials That Change.
  • Exploring Native Knowledge of How Stuff Works.
  • Understanding How Different Cultures Make New Things in Art and Design.

Robotics Qualitative Research Topics for STEM Students

  • Studying Whether Boys and Girls Get the Same Chance to Learn About Robots in School and Work.
  • Looking at How Different Cultures See People and Machines Talking.
  • Studying Programs That Teach About Robots.
  • Checking What People Think About Robots Doing Stuff in Everyday Life.
  • Exploring How Robots Help in Health Care.
  • Understanding How Different Cultures Feel About What’s Right and Wrong for Robots to Do.
  • Studying What’s Right and Wrong in Making Robots.
  • Checking What People Think About Machines Doing Jobs.
  • Exploring Native Ideas on Robots and Machines.
  • Understanding How Different Cultures See Using Robots on Farms.

Renewable Energy Research Topics for STEM Students

  • Studying Whether Men and Women Get Fair Jobs in Green Energy.
  • Looking at How Different Cultures See Making Wind Power.
  • Studying Rules for Making Green Energy Happen.
  • Checking What People Think About Using Sun Power.
  • Exploring How Green Energy Helps Light Up Country Areas.
  • Understanding How Different Cultures Feel About Making Energy from Plants.
  • Studying What’s Right and Wrong in Making Green Energy Projects.
  • Checking What People Think About Making Power from Water.
  • Exploring Native Knowledge of Green Power.
  • Understanding How Different Cultures Feel About Digging for Heat Energy.

Best Quantitative Research Topics For STEM High School Students

Research topics for grade 11 stem students, research topics for grade 12 stem students, interesting research topics for senior high school stem students.

Also Read :  350+ Most Interesting Research Topics For ABM Students

Best Qualitative Research Topics for STEM Students PDF

10 major differences between qualitative and quantitative research .

Here are 10 major differences between qualitative and quantitative research:


In conclusion, picking the right research topic is important for science students because it lets them explore what interests them, develop their critical thinking skills, and contribute meaningfully to their studies. 

The best research topics for science students are those that match their passions and curiosity and also give them chances to try things out, examine things closely, and generate new ideas.

Also, doing this kind of research helps students get better at talking with others, solving problems, and seeing how different fields connect, which helps them prepare for what comes next in school and their careers.

In the end, research like this helps science students keep learning, think hard, and be a positive force in science and technology.

FAQs- Qualitative Research Topics for STEM Students

What should stem students consider when choosing a research topic.

STEM students should consider their interests, career goals, available resources, and the potential impact of their research when choosing a topic. It’s also important to consider ethical considerations and the potential implications of the study.

Are there specific areas within STEM that offer promising research topics?

Yes, several areas within STEM offer promising research topics, including renewable energy, environmental sustainability, healthcare innovations, technology advancements, and interdisciplinary studies at the intersection of different STEM fields.

Can STEM students collaborate on research projects?

Yes, collaborating on research projects is common among STEM students. Collaboration allows students to leverage each other’s strengths, share resources, and foster interdisciplinary approaches to solving complex problems.

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100 Qualitative Research Paper Topics

Published by Ellie Cross at November 1st, 2021 , Revised On November 3, 2023

Selecting an interesting research topic is a very daunting task. And it becomes even more daunting when students are required to pick a topic that is:

  • Highly specific
  • Useful to the larger research community
  • Has a lot of material present on it to start with
  • Can be supported by enough facts and figures
  • Instrumental in closing the ‘research gap’ that already exists around it or within the same field of study.
  • Tries to explain the what , why , how , when , where and/or who behind a phenomenon or an event.

Because of all these factors, institutions—schools, colleges and universities alike—pay so much attention to the kind of topics their students will be researching on.

Qualitative research involves describing or explaining an event or a phenomenon without heavily relying on statistical or mathematical practices. Even though some qualitative research papers do make use of such practices to collect data, in the end, they generally rely on summarising and interpreting that data qualitatively.

Did you know that an eclectic method or mixed-methods approach is a research method that uses both quantitative and qualitative means of data collection and interpretation?

How to Choose the Correct Qualitative Research Paper Topic

Settling on the right qualitative research topic for one’s study depends on answers to some questions and personal student reflections, such as:  :

  • Can I research this topic in the time I have been given by my school/college/university?
  • Is there a research gap that my research will be able to fill?
  • Is this topic highly necessary; if I don’t research this topic, will the research community be affected?
  • Has this topic been researched before?
  • Does this topic support doable, practical research objectives and questions?
  • Does my topic lean more towards the quantitative side than the qualitative side?

Such questions, if brainstormed before selecting a topic, will greatly help make the right decision about what kind of research needs to be done.

Still having difficulty choosing the perfect qualitative research topic? Below is a list of 100 qualitative research topics for different types of students.

Qualitative Research Paper Topics for Senior High School Students

In most countries around the world, high school generally comprises grades from 9th or 10th to 12th grade. The courses taught to students in high school mostly include the ones listed below, along with some unique qualitative research topics for each subject.

  • What are the main cultural elements in Charlotte Brontë’s novels? OR How do they reflect modern cultures?
  • How does literary language differ from the non-literary language in writing?
  • What are the differences between poetry and drama?
  • Which Shakespearean play/drama is most relevant to present times and why/how?
  • How do Charles Dickens’ writings portray the pre-industrial revolution era?
  • Why are Charles Bukowski’s writings negatively criticised?


  • Why are coral reefs so important in marine life?
  • How do bones in the human body ossify?
  • Flora and fauna in deserts: truth or fiction?
  • When is exposure to the sun beneficial and harmful to the human body?
  • What is mercury poisoning in humans?
  • What is the world’s oldest plant/animal species?
  • What are the effects and causes of prolonged humidity or lack of rain on land?
  • Is global warming getting worse or is it just a myth?
  • Why do some plants need water and some don’t?
  • Are there any physical benefits of having pets?
  • What are ferrofluids?
  • How do aluminium and mercury react together? What happens/doesn’t happen?
  • What are the properties of aerogel?
  • Can metal be smelled? If not, why, and if so, how?
  • How can old jewellery be turned into gold bars?
  • When does milk become lactose-free?
  • Why are some gases odourless and others aren’t?
  • How are black holes evolving?
  • What is so special about Jupiter’s rings?
  • What is the Fermi Paradox and what are the Five Solutions to it?
  • Where can the law of entropy be witnessed in action?
  • Does the soul have weight? How can it be measured?
  • How does the Large Hadron Collider (LHC) work?
  • What kind of environments would fission and fusion reactions not hold in?
  • What are the major implications of the Civil War in today’s world?
  • How did the age of piracy end?
  • Which civilisation was advanced and why (Roman, Greek, Incan, etc)?
  • What would modern society be like without the two World Wars?
  • Which ancient cultures have survived/are still practiced today? How?
  • What is the Nova Effect?
  • Will AI be the end of humankind?
  • Nihilism: good or bad?
  • Why is Arthur Schopenhauer considered the ‘darkest’ philosopher of all time?
  • Stoicism, Taoism, or Absurdism: which leads to a happier life?
  • How does the Amara Effect work in real life?

Arts and design

  • Do students learn better in a ‘colourful’ and architecturally rich environment?
  • What is the importance of the golden ratio in modern-day design?
  • Lefties are more artistic: myth or fact?
  • What is the importance of birth order according to Adler’s theory?
  • Alcoholism and drug abuse is common in teenagers: why or why not?
  • How do the ID, EGO and SUPEREGO shape an adult’s personality according to Freud?
  • Why is gratitude considered a sign of happiness in young adults?
  • Where do the effects of childhood abuse affect one’s mental well-being in later life stages?
  • Bullied children go on to bully others: fact or fiction?
  • Why is Bach’s classical music given so much importance?
  • Are music and memory connected? How?
  • What are Beethoven’s contributions to present-day orchestral music?

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Qualitative Research Paper Topics for ABM Students

This group of students comprises those who belong to the field of accountancy, business and management. Even though the following topics have been mentioned for each field separately, some of them can be mixed and matched. Because each field in ABM might make use of other, surrounding fields during its research process. This is all because of a simple fact: such fields are very inter-connected.


  • Will Blockchain improve the future of accounting? Why or why not?
  • How has the COVID-19 situation affected accountancy firms globally?
  • Is cryptocurrency the solution to all the financial issues of today’s consumerist society? Why/why not or how?
  • What are some important ethical considerations involved in discretionary accruals?
  • What will an accounting firm be like without interest rates?
  • Do international firms like Coke or Nestle have a better accountancy workforce than local vendors? Why or why not?
  • How can someone launch their own business during the current COVID-19 pandemic? How is it different than launching a business any other time of the year?
  • Is the AI business model the most integrated business approach model out there right now? Why/why not or how?
  • What is the importance of language in communicating business goals, reaching the target audience, etc.?
  • Which business ethics’ theories are followed most rigorously by contemporary businesses and why?
  • When do businesses like Amazon or Shopify least benefit or affect the general public or other businesses?
  • What is the relation between career and talent management?
  • Which affects management more: process planning or project planning? Why or how?
  • Does organisational leadership affect management in small companies? How?
  • Where is construction management most useful?
  • How will an organisation be affected without brand management?

Qualitative Research Paper Topics for STEM Students

STEM students belong to the fields of science, technology, engineering and mathematics. Same as ABM, STEM research topics can also be mixed and matched with one another. Since the STEM fields are also highly intertwined with each one, it becomes difficult to tell sometimes what kind of topics are solely for one field or the other.

For instance, a topic related to global warming can be considered merely scientific. But then again, fields like technology, engineering and mathematics are all different faces of science. So, while discussing the effects of global warming, a student might find themselves discussing how technological advancements can help prevent excessive damage caused by global warming worldwide.

Similarly, mathematics is heavily used in the field of engineering. So, research from one field doesn’t necessarily have to rely on that field alone. It can go on to join with other related fields, too.

The following topics, therefore, might be combined with others to create a whole new topic. Or they can also be used as they are.

  • Is terraforming on Mars (and possibly on other planets too) a good or bad move? Why?
  • How do black holes affect supernovas?
  • Can ice caps melting from global warming be artificially preserved to stop the spread of viruses living under the snow?
  • How has the earth changed in the last 100 years?
  • What is the relation between climate change and flora and fauna growth?
  • Are science and religion two sides of the same coin? Why or why not?
  • The scientific inquiry leads to more questions than answers: fact or fiction?
  • Scientific inventions have destroyed more than created. Is that so? Why or why not?
  • What is the most likely future of energy, be it solar or otherwise?
  • What is the importance of dialectical behaviour therapy (DBT) in helping patients?
  • What are the negative implications of machine learning in today’s world?
  • How has information technology (IT) revolutionised the medical world in the last couple of years?
  • Wireless technology or AI: which is better and why?
  • What is blockchain technology? Or Why is it important?
  • Should nanotechnology be adopted in different spheres of life? Why or why not?
  • How has Python revolutionised the world of technology in contemporary society?


  • What are some important future trends in industrial robotics?
  • How has aerospace engineering helped scientists and engineers discover all they have about space?
  • Where does civil engineering play an important part in construction?
  • Where are industrial pneumatics used mostly these days and how?
  • Why is mechanical design so important in a product’s development process?
  • Which household use engineering products run on thermodynamics and how?
  • What are the fundamentals of submarine engineering?
  • How do hydroelectric power plants function?


  • How do modern construction workers and/or designers make use of the Fibonacci sequence?
  • How do mathematical calculations help determine the endpoint of the universe?
  • How do spacecraft make use of basic math in their construction and working?
  • What is the role of maths in data science?
  • Where are mathematical computations used in game development?
  • Is contemporary mathematical knowledge and practices etc. based on Vedic math? Why/why not or how?
  • Can architects work without the use of geometry? Why or why not?

Explore further: Check out the top 10 tips every emerging qualitative researcher ought to know about before beginning their research.

Other Essay Topics: Discursive Essay Topics & Ideas 2022 , Persuasive Essay Topics – Suggested By Industry Experts , Argumentative Essay Topics and Ideas .

Selecting a research topic is the first and therefore, perhaps the hardest step in the research process. Qualitative research involves using more descriptive, non-statistical and/or non-mathematical practices to collect and interpret data.

There are a couple of important things that should be considered before finalising a research topic, such as whether it’s practical, doable within the assigned time, etc.

There are many different types of qualitative research topics that high school students, ABM (accountancy, business, management) and STEM (science, technology, engineering, mathematics) students can uptake these days, especially with new knowledge being published each day in different fields. However, there is still always more to be discovered, explored and explained.

Selecting a qualitative research topic for senior high school, ABM, or STEM students is made easier when the close relationship between these fields is considered. Since they’re all so interconnected, a topic from one field is bound to include elements of another, closely related field. Such topics can therefore be mixed and matched to create a whole new topic!

Frequently Asked Questions

How to choose the correct qualitative research paper topic.

To choose a qualitative research paper topic, consider your interests, expertise, and available resources. Explore current trends, gaps in knowledge, and societal issues. Seek feedback from peers and advisors. Prioritize relevance, feasibility, and potential impact. Refine your topic to ensure it aligns with your research goals.

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Looking for some unique and workable argumentative essay topics? Need to select a topic for your argumentative essay but unsure where to begin?

Well, sit back and read! Because this article lists many argumentative criminal justice essay topics that are sure to inspire you. Student engagement with criminology and criminal justice

‘Commemorate’ comes from Latin commemorat, which means ‘to remember collectively.’ A commemorative speech, therefore, is a kind of spoken discourse where the speaker is trying to do one or all the following

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55 Brilliant Research Topics For STEM Students

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

Quantitative research topics for stem students, qualitative research topics for stem students, what are the best experimental research topics for stem students, non-experimental research topics for stem students, capstone research topics for stem students, correlational research topics for stem students, scientific research topics for stem students, simple research topics for stem students, top 10 research topics for stem students, experimental research topics for stem students about plants, research topics for grade 11 stem students, research topics for grade 12 stem students, quantitative research topics for stem high school students, survey research topics for stem students, interesting and informative research topics for senior high school stem students.

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

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

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

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

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

  • An exploration into how microbial factories result in the cause shortage in raw metals
  • An experimental study on the possibility of older-aged men passing genetic abnormalities to children
  • A critical evaluation of how genetics could be used to help humans live healthier and longer.
Experimental research in STEM is a scientific research methodology that uses two sets of variables. They are dependent and independent variables that are studied under experimental research. Experimental research topics in STEM look into areas of science that use data to derive results.

Below are easy experimental research topics for STEM students.

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

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

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

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

Below are some simple quantitative research topics for stem students.

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

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

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

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

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

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

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

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

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

Below are possible research topics for STEM students about plants:

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

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

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

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

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

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

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

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

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

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

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

Final Words About Research Topics For STEM Students

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

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  • Published: 02 December 2020

Enhancing senior high school student engagement and academic performance using an inclusive and scalable inquiry-based program

  • Locke Davenport Huyer   ORCID: 1 , 2   na1 ,
  • Neal I. Callaghan   ORCID: 1 , 3   na1 ,
  • Sara Dicks 4 ,
  • Edward Scherer 4 ,
  • Andrey I. Shukalyuk 1 ,
  • Margaret Jou 4 &
  • Dawn M. Kilkenny   ORCID: 1 , 5  

npj Science of Learning volume  5 , Article number:  17 ( 2020 ) Cite this article

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The multi-disciplinary nature of science, technology, engineering, and math (STEM) careers often renders difficulty for high school students navigating from classroom knowledge to post-secondary pursuits. Discrepancies between the knowledge-based high school learning approach and the experiential approach of future studies leaves some students disillusioned by STEM. We present Discovery , a term-long inquiry-focused learning model delivered by STEM graduate students in collaboration with high school teachers, in the context of biomedical engineering. Entire classes of high school STEM students representing diverse cultural and socioeconomic backgrounds engaged in iterative, problem-based learning designed to emphasize critical thinking concomitantly within the secondary school and university environments. Assessment of grades and survey data suggested positive impact of this learning model on students’ STEM interests and engagement, notably in under-performing cohorts, as well as repeating cohorts that engage in the program on more than one occasion. Discovery presents a scalable platform that stimulates persistence in STEM learning, providing valuable learning opportunities and capturing cohorts of students that might otherwise be under-engaged in STEM.

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High school students with diverse STEM interests often struggle to understand the STEM experience outside the classroom 1 . The multi-disciplinary nature of many career fields can foster a challenge for students in their decision to enroll in appropriate high school courses while maintaining persistence in study, particularly when these courses are not mandatory 2 . Furthermore, this challenge is amplified by the known discrepancy between the knowledge-based learning approach common in high schools and the experiential, mastery-based approaches afforded by the subsequent undergraduate model 3 . In the latter, focused classes, interdisciplinary concepts, and laboratory experiences allow for the application of accumulated knowledge, practice in problem solving, and development of both general and technical skills 4 . Such immersive cooperative learning environments are difficult to establish in the secondary school setting and high school teachers often struggle to implement within their classroom 5 . As such, high school students may become disillusioned before graduation and never experience an enriched learning environment, despite their inherent interests in STEM 6 .

It cannot be argued that early introduction to varied math and science disciplines throughout high school is vital if students are to pursue STEM fields, especially within engineering 7 . However, the majority of literature focused on student interest and retention in STEM highlights outcomes in US high school learning environments, where the sciences are often subject-specific from the onset of enrollment 8 . In contrast, students in the Ontario (Canada) high school system are required to complete Level 1 and 2 core courses in science and math during Grades 9 and 10; these courses are offered as ‘applied’ or ‘academic’ versions and present broad topics of content 9 . It is not until Levels 3 and 4 (generally Grades 11 and 12, respectively) that STEM classes become subject-specific (i.e., Biology, Chemistry, and/or Physics) and are offered as “university”, “college”, or “mixed” versions, designed to best prepare students for their desired post-secondary pursuits 9 . Given that Levels 3 and 4 science courses are not mandatory for graduation, enrollment identifies an innate student interest in continued learning. Furthermore, engagement in these post-secondary preparatory courses is also dependent upon achieving successful grades in preceding courses, but as curriculum becomes more subject-specific, students often yield lower degrees of success in achieving course credit 2 . Therefore, it is imperative that learning supports are best focused on ensuring that those students with an innate interest are able to achieve success in learning.

When given opportunity and focused support, high school students are capable of successfully completing rigorous programs at STEM-focused schools 10 . Specialized STEM schools have existed in the US for over 100 years; generally, students are admitted after their sophomore year of high school experience (equivalent to Grade 10) based on standardized test scores, essays, portfolios, references, and/or interviews 11 . Common elements to this learning framework include a diverse array of advanced STEM courses, paired with opportunities to engage in and disseminate cutting-edge research 12 . Therein, said research experience is inherently based in the processes of critical thinking, problem solving, and collaboration. This learning framework supports translation of core curricular concepts to practice and is fundamental in allowing students to develop better understanding and appreciation of STEM career fields.

Despite the described positive attributes, many students do not have the ability or resources to engage within STEM-focused schools, particularly given that they are not prevalent across Canada, and other countries across the world. Consequently, many public institutions support the idea that post-secondary led engineering education programs are effective ways to expose high school students to engineering education and relevant career options, and also increase engineering awareness 13 . Although singular class field trips are used extensively to accomplish such programs, these may not allow immersive experiences for application of knowledge and practice of skills that are proven to impact long-term learning and influence career choices 14 , 15 . Longer-term immersive research experiences, such as after-school programs or summer camps, have shown successful at recruiting students into STEM degree programs and careers, where longevity of experience helps foster self-determination and interest-led, inquiry-based projects 4 , 16 , 17 , 18 , 19 .

Such activities convey the elements that are suggested to make a post-secondary led high school education programs successful: hands-on experience, self-motivated learning, real-life application, immediate feedback, and problem-based projects 20 , 21 . In combination with immersion in university teaching facilities, learning is authentic and relevant, similar to the STEM school-focused framework, and consequently representative of an experience found in actual STEM practice 22 . These outcomes may further be a consequence of student engagement and attitude: Brown et al. studied the relationships between STEM curriculum and student attitudes, and found the latter played a more important role in intention to persist in STEM when compared to self-efficacy 23 . This is interesting given that student self-efficacy has been identified to influence ‘motivation, persistence, and determination’ in overcoming challenges in a career pathway 24 . Taken together, this suggests that creation and delivery of modern, exciting curriculum that supports positive student attitudes is fundamental to engage and retain students in STEM programs.

Supported by the outcomes of identified effective learning strategies, University of Toronto (U of T) graduate trainees created a novel high school education program Discovery , to develop a comfortable yet stimulating environment of inquiry-focused iterative learning for senior high school students (Grades 11 & 12; Levels 3 & 4) at non-specialized schools. Built in strong collaboration with science teachers from George Harvey Collegiate Institute (Toronto District School Board), Discovery stimulates application of STEM concepts within a unique term-long applied curriculum delivered iteratively within both U of T undergraduate teaching facilities and collaborating high school classrooms 25 . Based on the volume of medically-themed news and entertainment that is communicated to the population at large, the rapidly-growing and diverse field of biomedical engineering (BME) were considered an ideal program context 26 . In its definition, BME necessitates cross-disciplinary STEM knowledge focused on the betterment of human health, wherein Discovery facilitates broadening student perspective through engaging inquiry-based projects. Importantly, Discovery allows all students within a class cohort to work together with their classroom teacher, stimulating continued development of a relevant learning community that is deemed essential for meaningful context and important for transforming student perspectives and understandings 27 , 28 . Multiple studies support the concept that relevant learning communities improve student attitudes towards learning, significantly increasing student motivation in STEM courses, and consequently improving the overall learning experience 29 . Learning communities, such as that provided by Discovery , also promote the formation of self-supporting groups, greater active involvement in class, and higher persistence rates for participating students 30 .

The objective of Discovery , through structure and dissemination, is to engage senior high school science students in challenging, inquiry-based practical BME activities as a mechanism to stimulate comprehension of STEM curriculum application to real-world concepts. Consequent focus is placed on critical thinking skill development through an atmosphere of perseverance in ambiguity, something not common in a secondary school knowledge-focused delivery but highly relevant in post-secondary STEM education strategies. Herein, we describe the observed impact of the differential project-based learning environment of Discovery on student performance and engagement. We identify the value of an inquiry-focused learning model that is tangible for students who struggle in a knowledge-focused delivery structure, where engagement in conceptual critical thinking in the relevant subject area stimulates student interest, attitudes, and resulting academic performance. Assessment of study outcomes suggests that when provided with a differential learning opportunity, student performance and interest in STEM increased. Consequently, Discovery provides an effective teaching and learning framework within a non-specialized school that motivates students, provides opportunity for critical thinking and problem-solving practice, and better prepares them for persistence in future STEM programs.

Program delivery

The outcomes of the current study result from execution of Discovery over five independent academic terms as a collaboration between Institute of Biomedical Engineering (graduate students, faculty, and support staff) and George Harvey Collegiate Institute (science teachers and administration) stakeholders. Each term, the program allowed senior secondary STEM students (Grades 11 and 12) opportunity to engage in a novel project-based learning environment. The program structure uses the problem-based engineering capstone framework as a tool of inquiry-focused learning objectives, motivated by a central BME global research topic, with research questions that are inter-related but specific to the curriculum of each STEM course subject (Fig. 1 ). Over each 12-week term, students worked in teams (3–4 students) within their class cohorts to execute projects with the guidance of U of T trainees ( Discovery instructors) and their own high school teacher(s). Student experimental work was conducted in U of T teaching facilities relevant to the research study of interest (i.e., Biology and Chemistry-based projects executed within Undergraduate Teaching Laboratories; Physics projects executed within Undergraduate Design Studios). Students were introduced to relevant techniques and safety procedures in advance of iterative experimentation. Importantly, this experience served as a course term project for students, who were assessed at several points throughout the program for performance in an inquiry-focused environment as well as within the regular classroom (Fig. 1 ). To instill the atmosphere of STEM, student teams delivered their outcomes in research poster format at a final symposium, sharing their results and recommendations with other post-secondary students, faculty, and community in an open environment.

figure 1

The general program concept (blue background; top left ) highlights a global research topic examined through student dissemination of subject-specific research questions, yielding multifaceted student outcomes (orange background; top right ). Each program term (term workflow, yellow background; bottom panel ), students work on program deliverables in class (blue), iterate experimental outcomes within university facilities (orange), and are assessed accordingly at numerous deliverables in an inquiry-focused learning model.

Over the course of five terms there were 268 instances of tracked student participation, representing 170 individual students. Specifically, 94 students participated during only one term of programming, 57 students participated in two terms, 16 students participated in three terms, and 3 students participated in four terms. Multiple instances of participation represent students that enrol in more than one STEM class during their senior years of high school, or who participated in Grade 11 and subsequently Grade 12. Students were surveyed before and after each term to assess program effects on STEM interest and engagement. All grade-based assessments were performed by high school teachers for their respective STEM class cohorts using consistent grading rubrics and assignment structure. Here, we discuss the outcomes of student involvement in this experiential curriculum model.

Student performance and engagement

Student grades were assigned, collected, and anonymized by teachers for each Discovery deliverable (background essay, client meeting, proposal, progress report, poster, and final presentation). Teachers anonymized collective Discovery grades, the component deliverable grades thereof, final course grades, attendance in class and during programming, as well as incomplete classroom assignments, for comparative study purposes. Students performed significantly higher in their cumulative Discovery grade than in their cumulative classroom grade (final course grade less the Discovery contribution; p  < 0.0001). Nevertheless, there was a highly significant correlation ( p  < 0.0001) observed between the grade representing combined Discovery deliverables and the final course grade (Fig. 2a ). Further examination of the full dataset revealed two student cohorts of interest: the “Exceeds Expectations” (EE) subset (defined as those students who achieved ≥1 SD [18.0%] grade differential in Discovery over their final course grade; N  = 99 instances), and the “Multiple Term” (MT) subset (defined as those students who participated in Discovery more than once; 76 individual students that collectively accounted for 174 single terms of assessment out of the 268 total student-terms delivered) (Fig. 2b, c ). These subsets were not unrelated; 46 individual students who had multiple experiences (60.5% of total MTs) exhibited at least one occasion in achieving a ≥18.0% grade differential. As students participated in group work, there was concern that lower-performing students might negatively influence the Discovery grade of higher-performing students (or vice versa). However, students were observed to self-organize into groups where all individuals received similar final overall course grades (Fig. 2d ), thereby alleviating these concerns.

figure 2

a Linear regression of student grades reveals a significant correlation ( p  = 0.0009) between Discovery performance and final course grade less the Discovery contribution to grade, as assessed by teachers. The dashed red line and intervals represent the theoretical 1:1 correlation between Discovery and course grades and standard deviation of the Discovery -course grade differential, respectively. b , c Identification of subgroups of interest, Exceeds Expectations (EE; N  = 99, orange ) who were ≥+1 SD in Discovery -course grade differential and Multi-Term (MT; N  = 174, teal ), of which N  = 65 students were present in both subgroups. d Students tended to self-assemble in working groups according to their final course performance; data presented as mean ± SEM. e For MT students participating at least 3 terms in Discovery , there was no significant correlation between course grade and time, while ( f ) there was a significant correlation between Discovery grade and cumulative terms in the program. Histograms of total absences per student in ( g ) Discovery and ( h ) class (binned by 4 days to be equivalent in time to a single Discovery absence).

The benefits experienced by MT students seemed progressive; MT students that participated in 3 or 4 terms ( N  = 16 and 3, respectively ) showed no significant increase by linear regression in their course grade over time ( p  = 0.15, Fig. 2e ), but did show a significant increase in their Discovery grades ( p  = 0.0011, Fig. 2f ). Finally, students demonstrated excellent Discovery attendance; at least 91% of participants attended all Discovery sessions in a given term (Fig. 2g ). In contrast, class attendance rates reveal a much wider distribution where 60.8% (163 out of 268 students) missed more than 4 classes (equivalent in learning time to one Discovery session) and 14.6% (39 out of 268 students) missed 16 or more classes (equivalent in learning time to an entire program of Discovery ) in a term (Fig. 2h ).

Discovery EE students (Fig. 3 ), roughly by definition, obtained lower course grades ( p  < 0.0001, Fig. 3a ) and higher final Discovery grades ( p  = 0.0004, Fig. 3b ) than non-EE students. This cohort of students exhibited program grades higher than classmates (Fig. 3c–h ); these differences were significant in every category with the exception of essays, where they outperformed to a significantly lesser degree ( p  = 0.097; Fig. 3c ). There was no statistically significant difference in EE vs. non-EE student classroom attendance ( p  = 0.85; Fig. 3i, j ). There were only four single day absences in Discovery within the EE subset; however, this difference was not statistically significant ( p  = 0.074).

figure 3

The “Exceeds Expectations” (EE) subset of students (defined as those who received a combined Discovery grade ≥1 SD (18.0%) higher than their final course grade) performed ( a ) lower on their final course grade and ( b ) higher in the Discovery program as a whole when compared to their classmates. d – h EE students received significantly higher grades on each Discovery deliverable than their classmates, except for their ( c ) introductory essays and ( h ) final presentations. The EE subset also tended ( i ) to have a higher relative rate of attendance during Discovery sessions but no difference in ( j ) classroom attendance. N  = 99 EE students and 169 non-EE students (268 total). Grade data expressed as mean ± SEM.

Discovery MT students (Fig. 4 ), although not receiving significantly higher grades in class than students participating in the program only one time ( p  = 0.29, Fig. 4a ), were observed to obtain higher final Discovery grades than single-term students ( p  = 0.0067, Fig. 4b ). Although trends were less pronounced for individual MT student deliverables (Fig. 4c–h ), this student group performed significantly better on the progress report ( p  = 0.0021; Fig. 4f ). Trends of higher performance were observed for initial proposals and final presentations ( p  = 0.081 and 0.056, respectively; Fig. 4e, h ); all other deliverables were not significantly different between MT and non-MT students (Fig. 4c, d, g ). Attendance in Discovery ( p  = 0.22) was also not significantly different between MT and non-MT students, although MT students did miss significantly less class time ( p  = 0.010) (Fig. 4i, j ). Longitudinal assessment of individual deliverables for MT students that participated in three or more Discovery terms (Fig. 5 ) further highlights trend in improvement (Fig. 2f ). Greater performance over terms of participation was observed for essay ( p  = 0.0295, Fig. 5a ), client meeting ( p  = 0.0003, Fig. 5b ), proposal ( p  = 0.0004, Fig. 5c ), progress report ( p  = 0.16, Fig. 5d ), poster ( p  = 0.0005, Fig. 5e ), and presentation ( p  = 0.0295, Fig. 5f ) deliverable grades; these trends were all significant with the exception of the progress report ( p  = 0.16, Fig. 5d ) owing to strong performance in this deliverable in all terms.

figure 4

The “multi-term” (MT) subset of students (defined as having attended more than one term of Discovery ) demonstrated favorable performance in Discovery , ( a ) showing no difference in course grade compared to single-term students, but ( b outperforming them in final Discovery grade. Independent of the number of times participating in Discovery , MT students did not score significantly differently on their ( c ) essay, ( d ) client meeting, or ( g ) poster. They tended to outperform their single-term classmates on the ( e ) proposal and ( h ) final presentation and scored significantly higher on their ( f ) progress report. MT students showed no statistical difference in ( i ) Discovery attendance but did show ( j ) higher rates of classroom attendance than single-term students. N  = 174 MT instances of student participation (76 individual students) and 94 single-term students. Grade data expressed as mean ± SEM.

figure 5

Longitudinal assessment of a subset of MT student participants that participated in three ( N  = 16) or four ( N  = 3) terms presents a significant trend of improvement in their ( a ) essay, ( b ) client meeting, ( c ) proposal, ( e ) poster, and ( f ) presentation grade. d Progress report grades present a trend in improvement but demonstrate strong performance in all terms, limiting potential for student improvement. Grade data are presented as individual student performance; each student is represented by one color; data is fitted with a linear trendline (black).

Finally, the expansion of Discovery to a second school of lower LOI (i.e., nominally higher aggregate SES) allowed for the assessment of program impact in a new population over 2 terms of programming. A significant ( p  = 0.040) divergence in Discovery vs. course grade distribution from the theoretical 1:1 relationship was found in the new cohort (S 1 Appendix , Fig. S 1 ), in keeping with the pattern established in this study.

Teacher perceptions

Qualitative observation in the classroom by high school teachers emphasized the value students independently placed on program participation and deliverables. Throughout the term, students often prioritized Discovery group assignments over other tasks for their STEM courses, regardless of academic weight and/or due date. Comparing within this student population, teachers spoke of difficulties with late and incomplete assignments in the regular curriculum but found very few such instances with respect to Discovery -associated deliverables. Further, teachers speculated on the good behavior and focus of students in Discovery programming in contrast to attentiveness and behavior issues in their school classrooms. Multiple anecdotal examples were shared of renewed perception of student potential; students that exhibited poor academic performance in the classroom often engaged with high performance in this inquiry-focused atmosphere. Students appeared to take a sense of ownership, excitement, and pride in the setting of group projects oriented around scientific inquiry, discovery, and dissemination.

Student perceptions

Students were asked to consider and rank the academic difficulty (scale of 1–5, with 1 = not challenging and 5 = highly challenging) of the work they conducted within the Discovery learning model. Considering individual Discovery terms, at least 91% of students felt the curriculum to be sufficiently challenging with a 3/5 or higher ranking (Term 1: 87.5%, Term 2: 93.4%, Term 3: 85%, Term 4: 93.3%, Term 5: 100%), and a minimum of 58% of students indicating a 4/5 or higher ranking (Term 1: 58.3%, Term 2: 70.5%, Term 3: 67.5%, Term 4: 69.1%, Term 5: 86.4%) (Fig. 6a ).

figure 6

a Histogram of relative frequency of perceived Discovery programming academic difficulty ranked from not challenging (1) to highly challenging (5) for each session demonstrated the consistently perceived high degree of difficulty for Discovery programming (total responses: 223). b Program participation increased student comfort (94.6%) with navigating lab work in a university or college setting (total responses: 220). c Considering participation in Discovery programming, students indicated their increased (72.4%) or decreased (10.1%) likelihood to pursue future experiences in STEM as a measure of program impact (total responses: 217). d Large majority of participating students (84.9%) indicated their interest for future participation in Discovery (total responses: 212). Students were given the opportunity to opt out of individual survey questions, partially completed surveys were included in totals.

The majority of students (94.6%) indicated they felt more comfortable with the idea of performing future work in a university STEM laboratory environment given exposure to university teaching facilities throughout the program (Fig. 6b ). Students were also queried whether they were (i) more likely, (ii) less likely, or (iii) not impacted by their experience in the pursuit of STEM in the future. The majority of participants (>82%) perceived impact on STEM interests, with 72.4% indicating they were more likely to pursue these interests in the future (Fig. 6c ). When surveyed at the end of term, 84.9% of students indicated they would participate in the program again (Fig. 6d ).

We have described an inquiry-based framework for implementing experiential STEM education in a BME setting. Using this model, we engaged 268 instances of student participation (170 individual students who participated 1–4 times) over five terms in project-based learning wherein students worked in peer-based teams under the mentorship of U of T trainees to design and execute the scientific method in answering a relevant research question. Collaboration between high school teachers and Discovery instructors allowed for high school student exposure to cutting-edge BME research topics, participation in facilitated inquiry, and acquisition of knowledge through scientific discovery. All assessments were conducted by high school teachers and constituted a fraction (10–15%) of the overall course grade, instilling academic value for participating students. As such, students exhibited excitement to learn as well as commitment to their studies in the program.

Through our observations and analysis, we suggest there is value in differential learning environments for students that struggle in a knowledge acquisition-focused classroom setting. In general, we observed a high level of academic performance in Discovery programming (Fig. 2a ), which was highlighted exceptionally in EE students who exhibited greater academic performance in Discovery deliverables compared to normal coursework (>18% grade improvement in relevant deliverables). We initially considered whether this was the result of strong students influencing weaker students; however, group organization within each course suggests this is not the case (Fig. 2d ). With the exception of one class in one term (24 participants assigned by their teacher), students were allowed to self-organize into working groups and they chose to work with other students of relatively similar academic performance (as indicated by course grade), a trend observed in other studies 31 , 32 . Remarkably, EE students not only excelled during Discovery when compared to their own performance in class, but this cohort also achieved significantly higher average grades in each of the deliverables throughout the program when compared to the remaining Discovery cohort (Fig. 3 ). This data demonstrates the value of an inquiry-based learning environment compared to knowledge-focused delivery in the classroom in allowing students to excel. We expect that part of this engagement was resultant of student excitement with a novel learning opportunity. It is however a well-supported concept that students who struggle in traditional settings tend to demonstrate improved interest and motivation in STEM when given opportunity to interact in a hands-on fashion, which supports our outcomes 4 , 33 . Furthermore, these outcomes clearly represent variable student learning styles, where some students benefit from a greater exchange of information, knowledge and skills in a cooperative learning environment 34 . The performance of the EE group may not be by itself surprising, as the identification of the subset by definition required high performers in Discovery who did not have exceptionally high course grades; in addition, the final Discovery grade is dependent on the component assignment grades. However, the discrepancies between EE and non-EE groups attendance suggests that students were engaged by Discovery in a way that they were not by regular classroom curriculum.

In addition to quantified engagement in Discovery observed in academic performance, we believe remarkable attendance rates are indicative of the value students place in the differential learning structure. Given the differences in number of Discovery days and implications of missing one day of regular class compared to this immersive program, we acknowledge it is challenging to directly compare attendance data and therefore approximate this comparison with consideration of learning time equivalence. When combined with other subjective data including student focus, requests to work on Discovery during class time, and lack of discipline/behavior issues, the attendance data importantly suggests that students were especially engaged by the Discovery model. Further, we believe the increased commute time to the university campus (students are responsible for independent transit to campus, a much longer endeavour than the normal school commute), early program start time, and students’ lack of familiarity with the location are non-trivial considerations when determining the propensity of students to participate enthusiastically in Discovery . We feel this suggests the students place value on this team-focused learning and find it to be more applicable and meaningful to their interests.

Given post-secondary admission requirements for STEM programs, it would be prudent to think that students participating in multiple STEM classes across terms are the ones with the most inherent interest in post-secondary STEM programs. The MT subset, representing students who participated in Discovery for more than one term, averaged significantly higher final Discovery grades. The increase in the final Discovery grade was observed to result from a general confluence of improved performance over multiple deliverables and a continuous effort to improve in a STEM curriculum. This was reflected in longitudinal tracking of Discovery performance, where we observed a significant trend of improved performance. Interestingly, the high number of MT students who were included in the EE group suggests that students who had a keen interest in science enrolled in more than one course and in general responded well to the inquiry-based teaching method of Discovery , where scientific method was put into action. It stands to reason that students interested in science will continue to take STEM courses and will respond favorably to opportunities to put classroom theory to practical application.

The true value of an inquiry-based program such as Discovery may not be based in inspiring students to perform at a higher standard in STEM within the high school setting, as skills in critical thinking do not necessarily translate to knowledge-based assessment. Notably, students found the programming equally challenging throughout each of the sequential sessions, perhaps somewhat surprising considering the increasing number of repeat attendees in successive sessions (Fig. 6a ). Regardless of sub-discipline, there was an emphasis of perceived value demonstrated through student surveys where we observed indicated interest in STEM and comfort with laboratory work environments, and desire to engage in future iterations given the opportunity. Although non-quantitative, we perceive this as an indicator of significant student engagement, even though some participants did not yield academic success in the program and found it highly challenging given its ambiguity.

Although we observed that students become more certain of their direction in STEM, further longitudinal study is warranted to make claim of this outcome. Additionally, at this point in our assessment we cannot effectively assess the practical outcomes of participation, understanding that the immediate effects observed are subject to a number of factors associated with performance in the high school learning environment. Future studies that track graduates from this program will be prudent, in conjunction with an ever-growing dataset of assessment as well as surveys designed to better elucidate underlying perceptions and attitudes, to continue to understand the expected benefits of this inquiry-focused and partnered approach. Altogether, a multifaceted assessment of our early outcomes suggests significant value of an immersive and iterative interaction with STEM as part of the high school experience. A well-defined divergence from knowledge-based learning, focused on engagement in critical thinking development framed in the cutting-edge of STEM, may be an important step to broadening student perspectives.

In this study, we describe the short-term effects of an inquiry-based STEM educational experience on a cohort of secondary students attending a non-specialized school, and suggest that the framework can be widely applied across virtually all subjects where inquiry-driven and mentored projects can be undertaken. Although we have demonstrated replication in a second cohort of nominally higher SES (S 1 Appendix , Supplementary Fig. 1 ), a larger collection period with more students will be necessary to conclusively determine impact independent of both SES and specific cohort effects. Teachers may also find this framework difficult to implement depending on resources and/or institutional investment and support, particularly if post-secondary collaboration is inaccessible. Offerings to a specific subject (e.g., physics) where experiments yielding empirical data are logistically or financially simpler to perform may be valid routes of adoption as opposed to the current study where all subject cohorts were included.

As we consider Discovery in a bigger picture context, expansion and implementation of this model is translatable. Execution of the scientific method is an important aspect of citizen science, as the concepts of critical thing become ever-more important in a landscape of changing technological landscapes. Giving students critical thinking and problem-solving skills in their primary and secondary education provides value in the context of any career path. Further, we feel that this model is scalable across disciplines, STEM or otherwise, as a means of building the tools of inquiry. We have observed here the value of differential inclusive student engagement and critical thinking through an inquiry-focused model for a subset of students, but further to this an engagement, interest, and excitement across the body of student participants. As we educate the leaders of tomorrow, we suggest that use of an inquiry-focused model such as Discovery could facilitate growth of a data-driven critical thinking framework.

In conclusion, we have presented a model of inquiry-based STEM education for secondary students that emphasizes inclusion, quantitative analysis, and critical thinking. Student grades suggest significant performance benefits, and engagement data suggests positive student attitude despite the perceived challenges of the program. We also note a particular performance benefit to students who repeatedly engage in the program. This framework may carry benefits in a wide variety of settings and disciplines for enhancing student engagement and performance, particularly in non-specialized school environments.

Study design and implementation

Participants in Discovery include all students enrolled in university-stream Grade 11 or 12 biology, chemistry, or physics at the participating school over five consecutive terms (cohort summary shown in Table 1 ). Although student participation in educational content was mandatory, student grades and survey responses (administered by high school teachers) were collected from only those students with parent or guardian consent. Teachers replaced each student name with a unique coded identifier to preserve anonymity but enable individual student tracking over multiple terms. All data collected were analyzed without any exclusions save for missing survey responses; no power analysis was performed prior to data collection.

Ethics statement

This study was approved by the University of Toronto Health Sciences Research Ethics Board (Protocol # 34825) and the Toronto District School Board External Research Review Committee (Protocol # 2017-2018-20). Written informed consent was collected from parents or guardians of participating students prior to the acquisition of student data (both post-hoc academic data and survey administration). Data were anonymized by high school teachers for maintenance of academic confidentiality of individual students prior to release to U of T researchers.

Educational program overview

Students enrolled in university-preparatory STEM classes at the participating school completed a term-long project under the guidance of graduate student instructors and undergraduate student mentors as a mandatory component of their respective course. Project curriculum developed collaboratively between graduate students and participating high school teachers was delivered within U of T Faculty of Applied Science & Engineering (FASE) teaching facilities. Participation allows high school students to garner a better understanding as to how undergraduate learning and career workflows in STEM vary from traditional high school classroom learning, meanwhile reinforcing the benefits of problem solving, perseverance, teamwork, and creative thinking competencies. Given that Discovery was a mandatory component of course curriculum, students participated as class cohorts and addressed questions specific to their course subject knowledge base but related to the defined global health research topic (Fig. 1 ). Assessment of program deliverables was collectively assigned to represent 10–15% of the final course grade for each subject at the discretion of the respective STEM teacher.

The Discovery program framework was developed, prior to initiation of student assessment, in collaboration with one high school selected from the local public school board over a 1.5 year period of time. This partner school consistently scores highly (top decile) in the school board’s Learning Opportunities Index (LOI). The LOI ranks each school based on measures of external challenges affecting its student population therefore schools with the greatest level of external challenge receive a higher ranking 35 . A high LOI ranking is inversely correlated with socioeconomic status (SES); therefore, participating students are identified as having a significant number of external challenges that may affect their academic success. The mandatory nature of program participation was established to reach highly capable students who may be reluctant to engage on their own initiative, as a means of enhancing the inclusivity and impact of the program. The selected school partner is located within a reasonable geographical radius of our campus (i.e., ~40 min transit time from school to campus). This is relevant as participating students are required to independently commute to campus for Discovery hands-on experiences.

Each program term of Discovery corresponds with a five-month high school term. Lead university trainee instructors (3–6 each term) engaged with high school teachers 1–2 months in advance of high school student engagement to discern a relevant overarching global healthcare theme. Each theme was selected with consideration of (a) topics that university faculty identify as cutting-edge biomedical research, (b) expertise that Discovery instructors provide, and (c) capacity to showcase the diversity of BME. Each theme was sub-divided into STEM subject-specific research questions aligning with provincial Ministry of Education curriculum concepts for university-preparatory Biology, Chemistry, and Physics 9 that students worked to address, both on-campus and in-class, during a term-long project. The Discovery framework therefore provides students a problem-based learning experience reflective of an engineering capstone design project, including a motivating scientific problem (i.e., global topic), subject-specific research question, and systematic determination of a professional recommendation addressing the needs of the presented problem.

Discovery instructors were volunteers recruited primarily from graduate and undergraduate BME programs in the FASE. Instructors were organized into subject-specific instructional teams based on laboratory skills, teaching experience, and research expertise. The lead instructors of each subject (the identified 1–2 trainees that built curriculum with high school teachers) were responsible to organize the remaining team members as mentors for specific student groups over the course of the program term (~1:8 mentor to student ratio).

All Discovery instructors were familiarized with program expectations and trained in relevant workspace safety, in addition to engagement at a teaching workshop delivered by the Faculty Advisor (a Teaching Stream faculty member) at the onset of term. This workshop was designed to provide practical information on teaching and was co-developed with high school teachers based on their extensive training and experience in fundamental teaching methods. In addition, group mentors received hands-on training and guidance from lead instructors regarding the specific activities outlined for their respective subject programming (an exemplary term of student programming is available in S 2 Appendix) .

Discovery instructors were responsible for introducing relevant STEM skills and mentoring high school students for the duration of their projects, with support and mentorship from the Faculty Mentor. Each instructor worked exclusively throughout the term with the student groups to which they had been assigned, ensuring consistent mentorship across all disciplinary components of the project. In addition to further supporting university trainees in on-campus mentorship, high school teachers were responsible for academic assessment of all student program deliverables (Fig. 1 ; the standardized grade distribution available in S 3 Appendix ). Importantly, trainees never engaged in deliverable assessment; for continuity of overall course assessment, this remained the responsibility of the relevant teacher for each student cohort.

Throughout each term, students engaged within the university facilities four times. The first three sessions included hands-on lab sessions while the fourth visit included a culminating symposium for students to present their scientific findings (Fig. 1 ). On average, there were 4–5 groups of students per subject (3–4 students per group; ~20 students/class). Discovery instructors worked exclusively with 1–2 groups each term in the capacity of mentor to monitor and guide student progress in all project deliverables.

After introducing the selected global research topic in class, teachers led students in completion of background research essays. Students subsequently engaged in a subject-relevant skill-building protocol during their first visit to university teaching laboratory facilities, allowing opportunity to understand analysis techniques and equipment relevant for their assessment projects. At completion of this session, student groups were presented with a subject-specific research question as well as the relevant laboratory inventory available for use during their projects. Armed with this information, student groups continued to work in their classroom setting to develop group-specific experimental plans. Teachers and Discovery instructors provided written and oral feedback, respectively , allowing students an opportunity to revise their plans in class prior to on-campus experimental execution.

Once at the relevant laboratory environment, student groups executed their protocols in an effort to collect experimental data. Data analysis was performed in the classroom and students learned by trial & error to optimize their protocols before returning to the university lab for a second opportunity of data collection. All methods and data were re-analyzed in class in order for students to create a scientific poster for the purpose of study/experience dissemination. During a final visit to campus, all groups presented their findings at a research symposium, allowing students to verbally defend their process, analyses, interpretations, and design recommendations to a diverse audience including peers, STEM teachers, undergraduate and graduate university students, postdoctoral fellows and U of T faculty.

Data collection

Teachers evaluated their students on the following associated deliverables: (i) global theme background research essay; (ii) experimental plan; (iii) progress report; (iv) final poster content and presentation; and (v) attendance. For research purposes, these grades were examined individually and also as a collective Discovery program grade for each student. For students consenting to participation in the research study, all Discovery grades were anonymized by the classroom teacher before being shared with study authors. Each student was assigned a code by the teacher for direct comparison of deliverable outcomes and survey responses. All instances of “Final course grade” represent the prorated course grade without the Discovery component, to prevent confounding of quantitative analyses.

Survey instruments were used to gain insight into student attitudes and perceptions of STEM and post-secondary study, as well as Discovery program experience and impact (S 4 Appendix ). High school teachers administered surveys in the classroom only to students supported by parental permission. Pre-program surveys were completed at minimum 1 week prior to program initiation each term and exit surveys were completed at maximum 2 weeks post- Discovery term completion. Surveys results were validated using a principal component analysis (S 1 Appendix , Supplementary Fig. 2 ).

Identification and comparison of population subsets

From initial analysis, we identified two student subpopulations of particular interest: students who performed ≥1 SD [18.0%] or greater in the collective Discovery components of the course compared to their final course grade (“EE”), and students who participated in Discovery more than once (“MT”). These groups were compared individually against the rest of the respective Discovery population (“non-EE” and “non-MT”, respectively ). Additionally, MT students who participated in three or four (the maximum observed) terms of Discovery were assessed for longitudinal changes to performance in their course and Discovery grades. Comparisons were made for all Discovery deliverables (introductory essay, client meeting, proposal, progress report, poster, and presentation), final Discovery grade, final course grade, Discovery attendance, and overall attendance.

Statistical analysis

Student course grades were analyzed in all instances without the Discovery contribution (calculated from all deliverable component grades and ranging from 10 to 15% of final course grade depending on class and year) to prevent correlation. Aggregate course grades and Discovery grades were first compared by paired t-test, matching each student’s course grade to their Discovery grade for the term. Student performance in Discovery ( N  = 268 instances of student participation, comprising 170 individual students that participated 1–4 times) was initially assessed in a linear regression of Discovery grade vs. final course grade. Trends in course and Discovery performance over time for students participating 3 or 4 terms ( N  = 16 and 3 individuals, respectively ) were also assessed by linear regression. For subpopulation analysis (EE and MT, N  = 99 instances from 81 individuals and 174 instances from 76 individuals, respectively ), each dataset was tested for normality using the D’Agostino and Pearson omnibus normality test. All subgroup comparisons vs. the remaining population were performed by Mann–Whitney U -test. Data are plotted as individual points with mean ± SEM overlaid (grades), or in histogram bins of 1 and 4 days, respectively , for Discovery and class attendance. Significance was set at α ≤ 0.05.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The data that support the findings of this study are available upon reasonable request from the corresponding author DMK. These data are not publicly available due to privacy concerns of personal data according to the ethical research agreements supporting this study.

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This study has been possible due to the support of many University of Toronto trainee volunteers, including Genevieve Conant, Sherif Ramadan, Daniel Smieja, Rami Saab, Andrew Effat, Serena Mandla, Cindy Bui, Janice Wong, Dawn Bannerman, Allison Clement, Shouka Parvin Nejad, Nicolas Ivanov, Jose Cardenas, Huntley Chang, Romario Regeenes, Dr. Henrik Persson, Ali Mojdeh, Nhien Tran-Nguyen, Ileana Co, and Jonathan Rubianto. We further acknowledge the staff and administration of George Harvey Collegiate Institute and the Institute of Biomedical Engineering (IBME), as well as Benjamin Rocheleau and Madeleine Rocheleau for contributions to data collation. Discovery has grown with continued support of Dean Christopher Yip (Faculty of Applied Science and Engineering, U of T), and the financial support of the IBME and the National Science and Engineering Research Council (NSERC) PromoScience program (PROSC 515876-2017; IBME “Igniting Youth Curiosity in STEM” initiative co-directed by DMK and Dr. Penney Gilbert). LDH and NIC were supported by Vanier Canada graduate scholarships from the Canadian Institutes of Health Research and NSERC, respectively . DMK holds a Dean’s Emerging Innovation in Teaching Professorship in the Faculty of Engineering & Applied Science, U of T.

Author information

These authors contributed equally: Locke Davenport Huyer, Neal I. Callaghan.

Authors and Affiliations

Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada

Locke Davenport Huyer, Neal I. Callaghan, Andrey I. Shukalyuk & Dawn M. Kilkenny

Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, ON, Canada

Locke Davenport Huyer

Translational Biology and Engineering Program, Ted Rogers Centre for Heart Research, University of Toronto, Toronto, ON, Canada

Neal I. Callaghan

George Harvey Collegiate Institute, Toronto District School Board, Toronto, ON, Canada

Sara Dicks, Edward Scherer & Margaret Jou

Institute for Studies in Transdisciplinary Engineering Education & Practice, University of Toronto, Toronto, ON, Canada

Dawn M. Kilkenny

You can also search for this author in PubMed   Google Scholar


LDH, NIC and DMK conceived the program structure, designed the study, and interpreted the data. LDH and NIC ideated programming, coordinated execution, and performed all data analysis. SD, ES, and MJ designed and assessed student deliverables, collected data, and anonymized data for assessment. SD assisted in data interpretation. AIS assisted in programming ideation and design. All authors provided feedback and approved the manuscript that was written by LDH, NIC and DMK.

Corresponding author

Correspondence to Dawn M. Kilkenny .

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Davenport Huyer, L., Callaghan, N.I., Dicks, S. et al. Enhancing senior high school student engagement and academic performance using an inclusive and scalable inquiry-based program. npj Sci. Learn. 5 , 17 (2020).

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qualitative research topics for senior high school students stem

Pursuing STEM Careers: Perspectives of Senior High School Students

Abstract: this qualitative descriptive research explored the perspectives of stem (science, technology, engineering, and mathematics) senior high school students in a public secondary school in zambales, philippines on their reasons why they enrolled in stem and their intent to pursue relevant career. a total of 20 grade 12 students were purposively selected as participants of the research. the participants were interviewed using a validated structured interview guide. the recorded interviews were individually transcrib… show more.

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Cited by 10 publication s

References 37 publication s, challenges encountered by junior high school students in learning science: basis for action plan.

Science education is an essential element in thriving and surviving in a volatile, uncertain, complex, ambiguous, disruptive, and diverse (VUCAD 2 ) world. This cross-sectional research determines the challenges of junior high school students in learning science. A total of 123 junior high school students from four government-owned high schools in Zambales, Philippines, served as respondents of the study. Descriptive and inferential statistics were employed in analyzing the data. The developed Challenges in Learning Science Questionnaire (CLSQ) was used as the primary data gathering tool (α=0.95). Results revealed that junior high school students generally encounter not much challenges across all domains in learning science (M=2.06). However, based on the qualitative data, students encounter some issues and problems in learning the subject in terms of student motivation, student cognitive ability, teacher characteristics, subject matter content, medium of instruction, learning environment, instructional resources, curriculum and parental support. The t-test comparison revealed that male students encounter more challenges in terms of instructional resources and parental support compared to their female counterparts. The proposed action plan is crafted to minimize further the challenges encountered by the students in learning science. The teachers may consider varied and innovative pedagogical practices to explain better complex and complicated topics for better Science learning in a VUCAD 2 world.

Analysis of barriers, supports and gender gap in the choice of STEM studies in secondary education

Society is more digitised than ever and there is an urgent need to train people in these sectors, where women are still under-represented. A quantitative descriptive, correlational and explanatory descriptive design was used to identify barriers, supports and gender gaps in Science, Technology, Engineering and Mathematics in Secondary Education by analysing the interest and perception of 1562 students and 432 teachers. Descriptive statistics, Chi-square and Lambda test and Crame’s V or Phi test were performed together with a qualitative analysis. The results show that fewer female students want to pursue STEM studies, with girls preferring health and education professions and boys preferring engineering and computer science. Indeed, their motivation is different since we found correlations between being a girl and choosing STEM for helping people and society, while earning money is important for boys. Girls believe more necessary than boys to have qualities to study STEM and less often perceive themselves as intelligent and courageous. Our study revealed that families and teachers encourage more boys than girls towards STEM activities. Teachers believe that girls are influence by preconceived ideas, lack of STEM knowledge and lower self-esteem. Regarding gender equality, almost half state that no objectives are included in the curricula, 43.85% do not include it in subjects and only 30% received training. Consequently, female vocations need to be promoted by teaching how STEM solves real-life problems, fostering creativity, increasing self-confidence, promoting STEM activities and making female role models visible. Teachers should receive more gender training and promote gender-sensitive STEM education.

Students' Motivation and Perception in Learning Social Science Using Distance Learning Modality during COVID-19- Pandemic

Aims: This paper assessed the motivation and perception of Grade 12 public school students in learning social science during the pandemic. It also investigated the difference in their motivation and perception. Study Design:  Descriptive-comparative design. Place and Duration of Study: School Division of a Component City in Northern Negros Occidental, between January 2021 to July 2022. Methodology: The study utilized the descriptive-comparative design. The study was assessed by 436 stratified randomly sampled students. The assessments were gathered using the modified motivation and perception questionnaires. In analyzing the data, mean, standard deviation, Mann Whitney, and Kruskal Wallis were employed. Results: Generally, the motivation (M=3.83, SD= 0.67) shows an agreeable result. The extrinsic goal orientation (M=4.15, SD= 0.88) is rated highest with an agreeable result, and social engagement (M=3.46, SD= 0.92) is the lowest with a neutral result. Meanwhile, they have agreeable perceptions (M=3.69, SD= 0.65) with perceived value (M=3.79, SD= 0.79) as highest and perceived teachers' attitude (M=3.46, SD= 0.89) as lowest. Moreover, there was no difference in their motivation when group according to sex [U=21954.5, p=0.721] and track [U=22104.0, p=0.875]. While a significant difference in academic performance [χ2(4)=53.069, p=0.000]. In terms of perception, it found no difference when grouped according to sex [U=22309.0, p=0.771] and track [U=22163.0, p=0.912]. While a significant difference in academic performance [χ2(4)=32.042, p=0.000]. Conclusion: The study implies the need to address students' motivation and perception issues to ensure their quality learning of social science.

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High school student helps transform 'crazy idea' into innovative research tool

Like many good ideas in science, it started with a walk in the woods.

During a stroll through the Berlin Botanic Garden in 2019, HHMI Janelia Research Campus Group Leader Jan Funke and some of his scientific colleagues started chatting about a familiar topic: how to get more information out of insect connectomes.

These wiring diagrams give researchers unprecedented information about brain cells and how they connect to each other, but they don't tell scientists how the signal from one neuron affects the other neurons in its network.

The group wondered if they might be able to use information from previous experiments identifying the neurotransmitters released from some neurons to predict the neurotransmitters released from others in the connectome. Neurons use neurotransmitters to communicate with each other, with different chemicals responsible for different signals.

The human eye can't tell the difference between the synapses on neurons where different neurotransmitters are released, but perhaps a computer model could. Funke and his colleagues were skeptical, but they thought it might be worth giving it a try.

"This is basically where we left it: we have the data, I guess we could try," Funke says. "We were not particularly optimistic."

Back at Janelia, Funke decided to give the project to Michelle Du, a high school student who was starting a summer internship in his lab. The project would allow Du to learn how to train a neural network to recognize images -- a useful skill for a budding computer scientist even if the project did not yield results.

A few days into her internship, Du showed up in Funke's office having trained the model on published data and evaluated its performance on test data. Though Funke had little hope it would work, the model was more than 90 percent accurate in predicting some neurotransmitters.

"I couldn't believe it," Funke says. "The numbers were way too good."

After checking the data and the model, Funke, Du, and their colleagues were convinced that the numbers weren't a mistake: The model could predict neurotransmitters. But the team was still cautious, and they didn't have a good grasp on how the network was making the predictions.

"I should have been very happy, but instead I was worried because we didn't understand what was going on," Funke says.

After ruling out possible confounders that could be skewing their results, the team developed a way to understand what the network was seeing that allowed it to make predictions.

First, they used their network to predict a neurotransmitter from a known image, which it did successfully. Then, they asked a separate network to take that known image and change it slightly to create an image corresponding to the release of a different neurotransmitter -- essentially identifying the minimum traits that need to be changed for the model to predict one neurotransmitter over 4another. Lastly, the team developed a separate method to identify these distinct traits.

From this information, the team understood the different features their original network used to make predictions. This gave them confidence to release their method to the wider neuroscience community in 2020.

"What most of the neuroscience community has seen from this work is the predictions," Funke says. "They were happy to use it, but for us it was very important to make sure it was actually working."

Five years later, Du is now an undergraduate at Duke University, and the method she helped develop has been used to predict neurotransmitters in connectomes of the fruit fly hemibrain, ventral nerve cord, and optic lobe created by Janelia researchers and collaborators, as well as the adult fly brain connectome created by FlyWire.

The information helps scientists understand how neurons in a circuit affect each other so they can then form hypotheses about the function of brain circuits that can be tested in the lab.

"It really all started with a bit of a crazy idea, something that no one was really too optimistic about. And what do you do with a crazy idea? You give it to a high school student as a learning experience," Funke says. "We were very fortunate that Michelle was extremely talented."

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  • Nils Eckstein, Alexander Shakeel Bates, Andrew Champion, Michelle Du, Yijie Yin, Philipp Schlegel, Alicia Kun-Yang Lu, Thomson Rymer, Samantha Finley-May, Tyler Paterson, Ruchi Parekh, Sven Dorkenwald, Arie Matsliah, Szi-Chieh Yu, Claire McKellar, Amy Sterling, Katharina Eichler, Marta Costa, Sebastian Seung, Mala Murthy, Volker Hartenstein, Gregory S.X.E. Jefferis, Jan Funke. Neurotransmitter classification from electron microscopy images at synaptic sites in Drosophila melanogaster . Cell , 2024; 187 (10): 2574 DOI: 10.1016/j.cell.2024.03.016

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Pursuing STEM Careers: Perspectives of Senior High School Students

Profile image of Danilo V . Rogayan Jr.

2020, Participatory Educational Research

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

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