Weather Wizards: Build a Weather Station

Learning Goals & Products

Learning Goals

Students will be able to formulate an investigable community weather question about local temperature, wind, humidity, or precipitation patterns and explain why it matters to people where they live.

Students will be able to design and calibrate simple weather instruments to collect reliable local weather measurements.

Students will be able to collect and document repeated local weather data using consistent procedures in a field notebook or digital log.

Students will be able to analyze weather data with tables, graphs, averages, and comparisons to identify patterns, changes, and anomalies.

Students will be able to interpret local weather patterns in relation to shade, drainage, humidity clues, and other community conditions.

Students will be able to justify conclusions about a community weather question using evidence from their own data and acknowledge limitations or conflicting results.

Students will be able to collaborate to revise methods, interpret shared findings, and contribute one scientific insight and one teamwork strength during reflection and exhibition tasks.

Products

individual

Individual Weather Investigation Notebook and Data Log

A personal research notebook that documents the student's question, instrument testing, data collection, graphs, source notes, and analysis over time. It shows individual mastery of investigation methods, data quality, and evidence-based reasoning.

team

Community Weather Data-Story Presentation and Forecast Fest Exhibit

A collaborative presentation and exhibit that synthesize team data, methods, visualizations, conclusions, limitations, and next questions for a public audience. The product must show how each member's evidence contributed to the final claims.

Rubric

Competency Progression Rubric Competency-first rubric

Category	Learning Goal	Stage 1	Stage 2	Stage 3	Stage 4
Deeper Learning Competencies	Critical Thinking & Problem Solving	I can ask questions about what I notice during the Weather Mystery Walk and identify possible explanations using simple evidence I record (e.g., temperature, wind, shade, humidity, drainage).	I can propose a plan to test a few explanations by selecting appropriate simple instruments, collecting consistent local data, and revising my questions based on what the data shows.	I can analyze patterns in my collected data (such as comparing days/locations and calculating averages or trends) and use those patterns to build a clear, evidence-based claim about my community weather question.	I can independently evaluate the quality of my evidence and instrument results, explain why my conclusion makes sense (including uncertainty or limitations), and connect my findings to broader weather/climate ideas or research with a justified next step.
Deeper Learning Competencies	Effective Communication	I can use appropriate science language to communicate my observations from the Weather Mystery Walk and early testing in a shared field notebook or digital log, including simple questions I still have about the community weather patterns.	I can explain my instrument setup, calibration notes, and collected local data in weekly displays by using clear labels, units, and basic charts (e.g., averages or comparisons), and I can describe how the evidence relates to my community weather question.	I can communicate my findings through a short, organized data-story (claims with evidence and a clear “because” link) and I can actively respond to feedback from my science partner by revising my explanations and graphs to be more accurate.	I can present at a Forecast Fest station with empathy and clarity by guiding guests through my instrument station and data-story, answering questions using evidence, and reflecting on how my communication choices (models, visuals, and wording) improved my understanding over time.
Deeper Learning Competencies	Collaboration	I can work respectfully with my group during instrument building and data collection by taking an assigned role, following shared procedures, and contributing my observations to our shared field notebook or digital log.	I can collaborate more actively by co-planning how we will test and calibrate instruments, using group talk to explain my ideas, and adjusting our plan when my observations or the science partner’s feedback suggest changes.	I can strengthen shared decision-making by negotiating roles, resolving misunderstandings using evidence from our notes, and leading parts of the process (e.g., assigning tasks for data displays) while keeping others included.	I can demonstrate leadership and relational agency by coordinating teamwork across sessions, helping my group use feedback to improve reliability and interpretations, and clearly reflecting on how our collaboration shaped the scientific insight we report at Forecast Fest.
Deeper Learning Competencies	Academic Mindset	I can describe what local weather phenomena mean for my community and connect my own observations from the Weather Mystery Walk to a question I want to investigate I can set a personal goal for how I will participate in instrument building, data collection, or reflection and follow the project steps with support.	I can use feedback from my college/university science partner to revise my instrument use, data logging, or questions so my work becomes more accurate and consistent I can explain how my thinking about the community weather question is changing by adding one scientific insight and one teamwork strength after each data session.	I can independently troubleshoot my methods (such as calibrating, repeating measurements, or adjusting how I record data) when results are unclear, and I can justify my choices with evidence from my field notes or logs I can identify patterns or limitations in my data and connect them to bigger ideas about weather/climate, showing clear growth in my understanding across the project.	I can consistently take ownership of the quality of my learning by planning and refining my approach to ensure reliable data and meaningful interpretation of patterns I can use reflection to set next-step actions, demonstrate resilience when findings change, and clearly articulate how my identity and sense of belonging in science helped me make decisions and communicate results at Forecast Fest.