Starting a STEM project in the classroom does not always have to be by following a specific protocol. Ideas often start in conversations, when some student comments about a real problem experienced in their routine, in the community or something they saw on the way to school. From this discussion, a simple question can shape a robust design: “why and how does this problem happen?”. From initial curiosity, young people start to observe the surroundings, collect information and compare different sources to better understand reality. It is at this moment that data in STEM projects are no longer merely instrumental and can become concrete tools to investigate challenges and make decisions.
Throughout the project journey,, from problem mapping to prototyping and pitch preparation, evidence-based research strengthens critical thinking and helps turn ideas into solutions that are more connected to the local context. In this way, hypotheses are no longer just perceptions and are analyzed based on concrete information.
In the phase of empathy, for example, still at the beginning of the journey, the use of data in STEM projects helps to map community problems more accurately, identifying social, environmental and/or economic challenges that impact people’s daily lives. When the time comes to define the problem, data-driven research allows for deeper systemic analysis of the challenge. Literature reviews, analysis of existing solutions, and evidence-based discussions strengthen scientific methodology and reduce decisions based on axioms alone. Thus, data in STEM projects contribute to better delineating the focus of research and guide the next steps.
Literature search as a starting point
Bibliographic research is one of the pillars of school research. Consulting scientific journals, books, reports and reliable documentaries helps students understand what has been studied and identify knowledge gaps. When working with data in STEM projects, teams develop skills such as critical reading, scientific literacy, and hypothesis validation – all of which are key competencies in active methodologies and science education.
This basis tends to generate more consistent solutions. The argentine project “Bastet Haus“, finalist of Solve for Tomorrow in the country in 2024, illustrates this process well. By analyzing local data on homeless people in the city of Buenos Aires, the team decided to develop sustainable bricks made with cigarette butts, prioritizing simplicity, scalability and economic accessibility. In this case, the data in STEM projects guided the choice of problem and contributed to a solution connected to the reality of the community.
Data also allows you to test ideas and improve solutions throughout the process. The Chilean “Electricistas del Sonido” team, finalist of the program in 2023, began their project by observing information about public safety and noise pollution in Santiago. From previous studies and literature review, the proposal to transform sound energy into electricity for urban lighting has emerged.
The impact of data on pitch credibility
Even in the final stage of the project, when it comes time to present the idea briefly and objectively in the pitch, evidence-based communication can be a great ally. Arguments supported by data make projects more convincing, demonstrate subject matter mastery and evidence the ability of critical analysis of students. The use of graphs, indicators and reliable references shows how data in STEM projects contribute to clearer and well-structured narratives
By organizing research findings, interviews, and literature reviews, teams construct presentations that connect scientific data to real community stories. Thus, the data in STEM projects are no longer just numbers and support narratives capable of sensitizing different audiences.
Integrating data into STEM projects from the beginning of the journey, from empathy to problem definition, through bibliographic research and hypothesis validation, improves prototype quality, strengthens pitch credibility and develops essential skills for school research. More than numbers, data are tools for understanding the world, proposing relevant solutions and building lasting learning.
5 steps to use data and make STEM projects more robust
- Map the problem with real data: Observe the community, collect initial information and identify patterns that confirm the relevance of the challenge.
- Do a good literature search: Look for reliable sources (scientific articles, reports, books and educational materials) to understand what has already been studied.
- Cross-reference secondary data with community listening: Combine existing surveys with interviews and observations to enhance understanding of the local context.
- Use data to test hypotheses and improve the prototype: Analyze results, review ideas, and make evidence-based adjustments throughout solution development.
- Turn data into clear arguments in the pitch: Organize charts, indicators, and key findings to communicate project impact convincingly and grounded.
