Earth System Scientist

Cinevva's analyzer read this game's design doc and its source, then wrote the brief below. "Make your own" hands it to the game creator as your opening message, so you start from a real spec rather than a one-line idea.

Create a responsive single-page educational investigation web game titled “Earth System Scientist,” subtitled “Indonesian wildfire investigation lab,” for a Grade 8–9 science project. It is an interactive, multi-step Earth-systems research dashboard rather than an arcade game. The subject is how dry conditions/El Niño and human activity can connect to wildfire hotspots, smoke, aerosols, PM2.5, atmospheric processes, water availability, and ecosystem change in West Kalimantan. Use a dark, polished science-lab visual style: deep navy/blue-green background, subtle animated floating blue particles/stars, translucent dark cards with rounded corners, thin teal borders, soft shadows, bright mint green and cyan-blue accents, yellow caution accents, and occasional red/orange wildfire accents. Use a clean system sans-serif font. The header is fixed across the top with a glowing spherical blue-green Earth logo, the title, and on the right an “Investigation 1/8” pill plus a slim green-to-blue progress bar. On desktop, show a left vertical “Investigation path” sidebar; on small screens turn it into a horizontally scrollable bottom navigation bar. Navigation items are: START, INVESTIGATE, EARTH SYSTEM, CAUSE & EFFECT, EXPERIMENT, ENTER DATA, GRAPH DATA, ANALYZE, GENERALIZE, IMPROVEMENTS, ACTION PLAN, 10-YEAR SCENARIO, CONCLUSION. Highlight the active item with a darker teal background and mint inset edge. Include a sidebar note reminding users to separate evidence from inference, distinguish background numbers from experiment results, and use “can,” “may,” and “potentially” when evidence is not causal.

The START screen should visually match the supplied screenshot: a large hero area with green uppercase eyebrow “GRADE 8–9 SCIENCE SET PROJECT,” oversized heading “Investigate a living Earth system.”, explanatory text saying the player is the Earth System Scientist tracing interconnected West Kalimantan conditions, wildfire, smoke, aerosols, PM2.5, atmospheric processes, water availability, and ecosystems, and two large buttons: “START INVESTIGATION” and “OPEN EARTH SYSTEM.” Beside it, show a large rounded Earth card with a glowing blue spherical planet, two soft green land shapes, a dashed orbit ring and subtle rotating halo. Below, show four KPI cards: background hotspots “154,000” by Aug 11; background “112 µg/m³” PM2.5 in Pontianak; experiment data shown as an em dash while waiting for LUX readings; and a scientific rule card saying “CAN,” not “proves.” Add a research-question card containing the question about El Niño/human activities, dryness, wildfire hotspots, atmospheric pollution/PM2.5, and rainfall cycles, plus a notice that separates Background/Research Data, Our Experiment Data, and Demo/Game Data.

Implement these connected screens and interactions:
1) INVESTIGATE / OUR RESEARCH / BACKGROUND DATA: show six supplied timeline/research facts exactly as context: July 27—96,000 fire hotspots detected across Indonesia; August 9—28,680 hectares burned in West Kalimantan; August 11—154,000 hotspots detected, a 60% increase from July reports; August 12—API exceeded 200 in Tebedu, Sarawak and haze crossed into Sarawak; One week—17.1 million tonnes of CO emissions, 429% above average; August 2026—PM2.5 reached 112 µg/m³ in Pontianak. Pair this with a hypothesis card stating that human activity and El Niño-driven temperatures may increase wildfire activity, smoke/emissions, PM2.5, atmospheric/cloud and water-cycle stress, and ecosystem damage over time. Clearly label background data and caution that it does not alone prove causation. Include a NEXT: EARTH SYSTEM CONFLICT button.
2) EARTH SYSTEM: show a central red/orange “WILDFIRE + ATMOSPHERIC POLLUTION” conflict card, surrounded by system cards for ATMOSPHERE (smoke/aerosols/PM2.5, air quality, clouds, particles), HYDROSPHERE (water vapor, condensation, rainfall, drought), BIOSPHERE (forests, plants/animals, biodiversity), GEOSPHERE/LAND (dry vegetation, burned areas, soil moisture), and HUMAN/SOCIAL SYSTEM (land clearing, agricultural burning, fire prevention, community response). Each card has a small clickable “click link” chip that opens a concise explanation of the possible relationship. A button follows the cause-effect chain.
3) CAUSE & EFFECT: display a tall interactive chain with clickable nodes: dry conditions/El Niño → drier vegetation and land → higher wildfire risk → more hotspots → smoke and aerosols → higher particulate pollution/PM2.5 → changes in atmospheric conditions → possible changes in condensation/cloud processes → possible precipitation effects → changes in water availability → drought stress → ecosystem impacts. Beside it show a possible feedback loop: drought → drier vegetation → higher fire risk → more smoke/PM2.5 → back toward drought. Explanations must use cautious scientific wording and mention uncertainty, variables, and time lags. Continue to the experiment.
4) EXPERIMENT / WHAT CHANGES IN THE ECOSYSTEM?: split into BIOTIC factors (trees, plants, animals, microorganisms, forest ecosystems, biodiversity) and ABIOTIC factors (temperature, air quality/PM2.5, smoke/aerosols, rainfall/humidity, soil moisture, water availability/light). Provide clickable pathway buttons for wildfire-to-habitat change and smoke-to-PM2.5-to-air-quality, and a careful explanation not to invent measurements for unmeasured variables.
5) ENTER DATA / OUR EXPERIMENT DATA: explain a transparent 2L bottle/chamber experiment. Show variables: independent = aerosol particle concentration; dependent = LUX/light measurement; controlled = humidity/water amount, temperature, light distance, chamber size, trial duration, and other conditions. Provide informational buttons explaining that LUX measures visible light reaching the sensor and is an indirect indicator of scattering/transmission, not rainfall, and distinguishing direct measurements from inferred effects. Provide a form to enter aerosol concentration and optional Trial 1, Trial 2, and Trial 3 LUX values, with a “SAVE REAL READING” button. Store rows in state and show them in a table. Do not generate fake experiment readings; initially display “WAITING FOR OUR EXPERIMENT DATA.”
6) GRAPH DATA: render an actual canvas scatter plot only from entered data, with X-axis aerosol concentration and Y-axis LUX reading. Keep it empty until readings are entered. Plot each available trial as a mint point and provide a SHOW MEAN/HIDE MEAN toggle that overlays yellow mean points per concentration. Explain that patterns can describe association but do not establish causation or rainfall effects; explicitly say LUX does not directly measure rainfall. Show a visual chain from aerosol concentration to particles, light scattering/transmission, LUX, and observed pattern.
7) ANALYZE: show the six supplied research facts in a horizontal timeline/card layout and state that this is not a complete historical record. Show an empty area saying no additional year-by-year project data is available. Include a dropdown where the learner can select “Not enough data,” “Increasing,” “Decreasing,” or “Variable,” and label the selection as an interpretation rather than an automatically generated conclusion. Continue through GENERALIZE, which shows Small-scale model → Atmospheric particle behavior → Scientific concept → Real Earth system, with limitations explaining that the bottle model represents only part of the atmosphere.
8) IMPROVEMENTS: three cards for EXPERIMENT, DATA, and SIMULATION. List improvements such as more trials, consistent aerosol concentrations, precise LUX, better temperature/humidity control, consistent light distance, longer observation, improved chamber design; longer data periods/more years/more observations/location comparisons; and more Earth-system variables, historical data, uncertainty/error visualization, and realistic atmospheric interactions.
9) ACTION PLAN: provide three selectable action cards: NOW (prevention, avoid unnecessary burning, monitor fires/air quality, awareness), NEXT 1–3 YEARS (education, forest protection, early reporting, more data), and LONGER TERM (monitoring, planning, ecosystem restoration). Selected cards visibly change styling. Show a qualitative chain: action → reduced wildfire risk → less smoke/aerosols → lower pollution exposure → better atmospheric conditions → protection of water-cycle and ecosystem conditions. No exact percentages.
10) 10-YEAR SCENARIO: show a range slider with labels NOW, 5 YEARS, and 10 YEARS. Pair a CURRENT RISK PATHWAY card—human-caused ignition + dry conditions → wildfire risk → smoke/aerosols → air pollution → atmospheric and water-cycle stress → ecosystem stress—with an ACTION PATHWAY card whose copy changes by slider: starting points of prevention/hotspot monitoring/forest protection/community awareness; planned lower wildfire risk, faster response, and better awareness; or the goal of better air quality, water-cycle conditions, and healthier ecosystems. Label this as a goal/scenario, not a guaranteed prediction or future numerical dataset. Include qualitative KPI cards: Lower wildfire risk, Faster wildfire response, Healthier ecosystems.
11) CONCLUSION DASHBOARD: show the final problem chain from wildfire activity through smoke/aerosols, PM2.5/air pollution, atmospheric effects, and potential water-cycle/ecosystem effects. Show evidence status: six supplied background values, number of entered experiment rows or waiting for actual readings, graph availability/empty state, available project timeline, and interactive cause-effect model. State that the project supports investigating possible connections, while the experiment directly describes only entered aerosol concentration versus LUX; it does not directly measure rainfall or prove real-world precipitation change. Explicitly list uncertainties including rainfall, cloud formation, real-world PM2.5 causation, long-term ecosystem change, and missing historical years. End with a 10-year goal focused on fire prevention, hotspot monitoring, community awareness, forest protection, and a button to revisit the final system map.

All navigation buttons should update the current view and investigation stage (1–8), update the header progress, and scroll the content area to the top. Interactive relationship arrows/chips can use compact modal or alert-style explanatory feedback. Preserve entered data, selected action cards, trend choice, mean toggle, and scenario slider while navigating. Make the layout responsive: desktop two-column dashboard with sidebar, mobile stacked cards with bottom navigation; maintain readable cards, controls, tables, and charts.