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Deeper Learning Competencies
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Critical Thinking & Problem Solving
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- I can identify a real problem on the campus woodland (e.g., invasive species, poor habitat conditions, or human access impacts) and propose a simple restoration/land-use idea that matches what I observed and measured so far.
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- I can use multiple pieces of site evidence (species observations, soil/sunlight/drainage results, and basic survey data) to evaluate possible solutions, explain why each option could reduce impacts, and revise my plan with clearer criteria (biodiversity, safety, and community needs).
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- I can design and refine a more detailed land-use solution by testing tradeoffs among competing options, using scientific explanations and prioritized evidence to justify choices and revise my approach when data or feedback shows problems.
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- I can create and improve an evidence-based proposal for leadership by comparing and refining redesign solutions using simulations/models and robust data, clearly explaining how my solution reduces impacts on biodiversity and balances ecological and community constraints.
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Deeper Learning Competencies
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Collaboration
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- I can share roles and contribute data or materials in my team by completing assigned field, mapping, or notebook tasks on time and using the team’s agreed plan for how we work.
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- I can work with my team to make shared decisions by proposing ideas, explaining how my evidence (e.g., species notes, soil/sunlight/drawings) supports them, and revising our plan based on group feedback.
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- I can coordinate collaboration by leading parts of the design process (such as comparing redesign options or organizing evidence for a zone poster) while resolving disagreements respectfully and ensuring everyone’s voice is reflected in the final proposal.
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- I can independently sustain effective teamwork by facilitating critique and iteration, integrating multiple sources of evidence and tradeoffs into our solution, and clearly communicating our revised direction to classmates and public audiences (e.g., during the pitch or gallery walk).
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Deeper Learning Competencies
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Effective Communication
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- I can share my observations and evidence (e.g., species notes, soil/sunlight results, and survey data) clearly in my field notebook so others can follow what I noticed and where it came from.
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- I can communicate my emerging land-use ideas using scientific evidence from my site data, showing relationships between human impact and biodiversity in both writing and simple visuals (charts, annotated sketches, zone map drafts).
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- I can present a reasoned proposal with clear claims, supporting evidence, and explanations of tradeoffs, and I can revise my communication after feedback by strengthening accuracy, clarity, and connections to specific criteria (ecological responsibility and community needs).
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- I can deliver and defend an evidence-based redesign pitch for a complex real-world audience, using coherent visuals (scaled maps, before/after concept boards, and data graphs) and models/simulations to explain how my solution would reduce impacts, anticipate questions, and refine my message during the open house.
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Deeper Learning Competencies
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Content Expertise
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- I can describe how human actions on the campus site (like neglect, access, and landscaping choices) affect biodiversity by using my field observations to identify invasive vs
- native species and habitat conditions.
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- I can use my collected field data (soil, sunlight, drainage, and survey results) to explain connections between habitat factors and biodiversity, and I can justify at least one restoration/land-use idea with evidence from the site.
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- I can design and evaluate a land-use plan by refining a proposed solution to reduce impacts on biodiversity, using scientific reasoning, prioritized criteria, and tradeoffs (e.g., safety, habitat quality, access) supported by data and maps.
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- I can create or revise a simple simulation/model and use it to test how different restoration/design choices could change biodiversity outcomes, then I can defend a refined, evidence-based proposal by comparing competing options using clear reasoning and data.
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Deeper Learning Competencies
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Academic Mindset
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- I can describe what I learned from field observations about the campus ecosystem and connect it to a personal sense of place and responsibility by using specific notebook evidence (e.g., species notes, soil/sunlight results) to explain how people affect biodiversity.
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- I can set a specific learning goal for improving my land-use ideas and monitor my progress using feedback, reflection notes, and new data from the site survey; I can revise my thinking when evidence shows my earlier claims were incomplete or not supported.
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- I can independently pursue and justify evidence-based improvements to my redesign proposal by comparing competing options (based on prioritized criteria and tradeoffs) and explaining how my choices reduce human impacts on biodiversity while meeting community needs.
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- I can refine my proposal through iterative critique by using scientific reasoning and multiple data sources (field data, maps, graphs, and simulations) to defend changes I make; I can articulate how my thinking and confidence evolved and what I would improve next if the community/leadership questions my plan.
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Deeper Learning Competencies
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Self Directed Learning
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- I can follow a clear plan for learning tasks (field notes, surveys, maps, and drafts) and check off steps as I go, using teacher-provided goals and examples to complete my work accurately.
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- I can monitor my progress toward learning goals by comparing my field data, graphs, and draft redesign ideas to the project criteria, and I can ask targeted questions or seek specific feedback when something is unclear.
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- I can independently revise my land-use proposal using evidence from my own site data and peers’ feedback, explaining what I changed and why it better reduces human impacts on biodiversity or improves habitat conditions.
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- I can lead my own learning cycle by setting sub-goals, selecting and prioritizing which evidence best supports tradeoffs in my redesign options, and refining a final, evidence-based pitch with clear justification and documented reflection on how my thinking evolved.
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