🔬 SteamCity Protocols: Scientific Inquiry Rooted in Urban Realities

The SteamCity scientific protocols have been finalized and tested in diverse situations, local contexts, and disciplines with teachers all across Europe within 2024–2025. Developed through collaborative training and experimentation with educators, these protocols are now being translated into all project languages for final publication to a wider audience.

SteamCity was designed from the outset with urban contexts in mind. The protocols invite teachers to implement scientific investigations that directly engage with the challenges of city life — air and noise pollution, biodiversity in fragmented habitats, energy use, public lighting, or the integration of artificial intelligence in urban systems.

Across more than 25 full protocols and over 75 distinct experiments, students are guided through the full arc of a scientific investigation, always anchored in real-world urban issues.

Each protocol proposes a structured, inquiry-based framework that empowers students to explore their immediate environment through the lens of scientific reasoning. Firmly anchored in Inquiry-Based Learning (IBL), the protocols guide students through every phase of the scientific method: defining a research question, building hypotheses, collecting and analyzing data, interpreting results, and communicating conclusions. They are not designed as theoretical exercises, but as investigations grounded in everyday urban experiences.

This structure ensures scientific rigor, while the local, open-ended nature of the problems encourages creativity, student agency, and engagement. Because each protocol is adaptable to context, teachers can modulate complexity and cross-disciplinary links — for instance, combining physics and ethics, biology and programming, or geography and civic education.

Diversity of the pedagogical strategies for Active Learning

Across the protocols, multiple pedagogical strategies are mobilized:

• Learning-by-Doing and Field-Based Exploration: Students conduct measurements, build devices, or map their surroundings.

• Civic and Ethical Reasoning: Investigations are connected to public issues such as urban mobility, energy equity, or biodiversity protection.

• Simulation and Scenario-Based Learning: Students explore future-oriented questions, such as the regulation of autonomous vehicles or sustainable lighting design.

• Digital and Data Literacy: Learners use sensors, collect geotagged data, or train AI models, deepening their understanding of how cities function—and how science can be used to make them more livable.

Urban Fieldwork as Scientific Inquiry

Most SteamCity protocols begin with real-world urban observation. Students formulate hypotheses in response to a tangible question, then gather field data to test and refine their assumptions. In “Mapping of Pollinators through Counting”, for instance, learners identify likely habitats across the city and validate them using non-lethal traps placed in gardens, schoolyards, or roadside green spaces. In “Whisper Walls”, they investigate how different construction materials attenuate noise and examine the implications for urban comfort and mental well-being. In “Shine Smart, Shine Bright”, they assess lighting infrastructure using grid-based observation tools that combine technical indicators (intensity, angle, source) with social ones (comfort, safety).

These investigations rely on tools built or assembled by students themselves — microcontrollers, air quality sensors, decibel meters — and require them to combine qualitative observations with quantitative data. In “SoundSquad”, students map the acoustic character of neighborhoods using both subjective perception and objective measurements. In “CO₂ Sensors for Indoor Air Quality”, they triangulate sensor data with situational analysis, learning to interpret variability and bias in environmental readings.

Scientific Inquiry with a Civic Perspective

What distinguishes SteamCity protocols is their systematic linkage between science and society. They are designed not only to develop analytical skills, but also to foster awareness of collective challenges and responsibilities.

In “Energy and Everyday Life”, students examine past and present patterns of energy consumption and debate scenarios for ecological transition, using tools such as the Negawatt scenario. In “Roobopoli Self-Driving Vehicle”, they simulate the logic of autonomous transport while critically assessing environmental and ethical consequences. “FactBusters” trains students to question sources of information, develop testable claims, and design their own verification methods — cultivating media literacy through experimental practice.

These experiences integrate moments of reflection on issues such as data privacy, algorithmic bias, environmental justice, or intergenerational responsibility. Scientific knowledge is not presented as neutral or detached, but as embedded in complex urban systems and ethical choices.

Exploring and Prototyping Possible Futures

Many protocols incorporate speculative or scenario-based components, encouraging students to project themselves into future-oriented problem-solving.

In “The Great Sound Escape”, students test different insulation materials and translate findings into building design recommendations. In “Bot Buddy Adventure”, they develop AI-based conversational agents intended to assist city dwellers — deciding what functions matter, what information should be included, and how to balance user needs with technical constraints. “Data vs. Context” places them in the role of urban decision-makers, navigating planning choices with incomplete or ambiguous data sets.

These scenarios encourage students not only to imagine change, but to engage in prototyping and iterative design. Hypotheses are not just discussed — they are built, tested, and refined.

Interrogating Technology and Data

A transversal dimension of many protocols is the development of critical data and AI literacy. Students work with environmental and behavioral data, use digital tools to observe and represent urban phenomena, and increasingly engage with algorithmic systems not just as users, but as constructors.

In “Birdsong AI Explorer”, for example, students collect acoustic data, label bird calls, and train a machine learning model to classify species. They are introduced to key concepts such as precision, recall, labeling bias, and model generalization. They learn to assess a model’s limits, reflect on its training data, and understand how environmental complexity can affect prediction outcomes.

Rather than treating digital tools as opaque or given, the protocols encourage students to question their design and impact — asking not only what a system does, but who it serves, how it learns, and where its blind spots lie.

The upcoming multilingual publication of these protocols before summer 2025 will make them freely accessible to the broader educational community. Teachers will be able to integrate them into their practice, adapt them to their context, and use them to foster critical, reflective, and action-oriented scientific learning.

SteamCity is not about abstract science. It’s about equipping learners with the tools to understand and transform the city — one experiment at a time.