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Start with the local climate question—not a list of AI apps. Choose a tool only if it helps students gather, analyze, or communicate evidence they need, and keep students responsible for checking that evidence and deciding what action to recommend. Free NASA data and citizen-science activities may answer some questions without an AI subscription or new equipment.

Start by defining the project question

Write down four things before comparing tools: the place you are studying, the climate concern, the action the team hopes to inform, and the evidence needed to make a sound recommendation. For example, a school team investigating neighborhood heat needs to establish whether it is studying temperatures across a campus, comparing tree cover, or deciding where shade might help. Those are different questions and may call for different data and methods.

Then ask whether AI adds a capability the project actually needs. A map, spreadsheet, field observation, existing dataset, or established citizen-science method may answer the question more directly. AI is an option to evaluate, not a requirement for a climate-action project.

Use a student-centered framework to make the choice

UNESCO’s 2024 AI competency framework for students is product-agnostic: it describes capabilities for engaging with AI rather than endorsing a particular product. It sets out 12 competencies across four dimensions—human-centred mindset, ethics of AI, AI techniques and applications, and AI system design—and organizes learning across Understand, Apply, and Create. Use those ideas to guide a practical tool decision.

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  1. Keep people in charge. Students should define the question, inspect evidence, interpret uncertainty, and make recommendations. UNESCO says AI should support human decision-making and intellectual development; it should not replace students’ judgment. UNESCO’s framework explainer also identifies fairness, transparency, privacy, accountability, and human agency as important concerns.
  2. Check how the tool handles information. Identify what student, personal, or location data would be entered and retained. Confirm that the tool’s use is permitted by school policy and applicable local rules. The sources cited here do not verify the current privacy terms or student settings of individual vendors, so check those directly before classroom use.
  3. Ask whether results can be checked. Students need to trace claims to credible data, methods, and sources. Treat generated text or analysis as a lead to verify, not evidence in itself. Consider whether a model or dataset might omit affected communities or produce results that are hard to explain.
  4. Account for access and environmental cost. Consider device, internet, account, training, accessibility, and budget needs, and whether all students can participate equitably. UNESCO asks students to examine the environmental impacts of AI use and training and to explore climate-friendlier approaches. If an offline or lower-resource method will do the job, weigh that option too. The framework connects project-based learning with understanding those impacts.
  5. Try a small, low-risk task first. Compare a tool’s output with a known source or a project observation before relying on it. This gives students a chance to spot unsupported claims and understand what the tool can—and cannot—contribute.

Consider these project routes before buying a tool

Existing data and structured observations can provide a useful starting point. Match the method to the scale and decision in the project; a resource covering a broad region may not answer a question about one street or schoolyard.

Analyze existing Earth-observation data

NASA’s My NASA Data provides grades 3–12 classrooms with authentic NASA satellite data and tools for analyzing Earth-system phenomena. NASA Earth Observations also provides regularly updated maps and a simple analysis tool. These can help a team investigate a question using existing observations, without buying monitoring equipment or adopting a commercial AI product.

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Connect Earth data to a community decision

NASA Earth Action describes applying Earth-observation data to decisions involving water, energy and infrastructure, wildfires, conservation, and air quality. It offers training and project-design resources. Check that the data’s geographic scale and subject match the local decision your team wants to inform.

Collect observations through citizen science

NASA’s classroom learning resource describes GLOBE Observer activities for clouds and tree observations. The cloud activity connects observations from the ground with satellite views, while tree-height observations can help validate satellite data. Use the selected program’s method rather than collecting measurements ad hoc.

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Monitor precipitation with an approved activity

NASA’s citizen-science learning resource describes a CoCoRaHS precipitation activity using a project-approved rain gauge. That resource lists a $30 gauge for the activity and notes educational materials for grades 3–5, with additional resources for middle and high school. The amount is the figure in NASA’s resource, not a current price quote; verify the activity’s current specifications and requirements before buying. This is one optional monitoring route, not a general requirement for choosing AI tools.

Compare candidate approaches with the same questions

Use this checklist to compare an AI service with another tool or method, including a non-AI option. The criteria synthesize UNESCO’s competencies and NASA’s project resources; they are not a product ranking or test.

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Criterion Questions to ask
Project fit Does it address the stated question at the location and scale needed?
Evidence quality Can students trace outputs to credible data, methods, and sources?
Human oversight Can students inspect, challenge, and explain the output?
Privacy and safety What student, personal, or location data is entered or retained, and does school policy permit the use?
Bias and inclusion Could the data or model omit affected communities, and can students access the tool equitably?
Environmental footprint Is AI use proportionate to its benefit, and would a lower-impact method be suitable?
Practical constraints What internet, device, account, training, accessibility, and budget needs apply?
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Support on Ko-Fi

Make the final choice—and document it

Choose the approach that meets the project’s evidence needs while allowing students to understand and check how the work was done. A practical project note can record:

  • the local question and why the chosen method fits it;
  • the data, observations, and sources used;
  • what students checked themselves and where uncertainty remains;
  • what personal or location information was shared, if any; and
  • why the team chose AI or a non-AI alternative, including relevant access and environmental considerations.

That record makes the project easier to explain and helps students distinguish observations and verified evidence from a tool’s suggestions.

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