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Deeper Learning Competencies
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Critical Thinking & Problem Solving
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- I can use a simple sample of thrift-store clothing or paper-doll outfit results to name a possible problem, like whether a piece might work for a career or budget, and choose a basic solution with support from my team
- I can show my thinking with simple counts, comparisons, or pictures, even if my sample is not yet representative.
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- I can use a sample of clothing options to make a reasonable recommendation for a capsule wardrobe and explain how the sample helps answer the question, “How do we dress for success on a budget?” I can use ratios, percentages, or a simple probability model to compare costs or clothing availability, and I can describe a likely reason if my prediction and results do not match closely.
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- I can analyze representative sample data from thrift-store options to decide which wardrobe pieces are most versatile and affordable for a career recommendation card
- I can develop a probability model, compare predicted and observed frequencies, and use ratios and percents to justify why my solution is practical for a specific profession.
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- I can independently investigate clothing samples and chance results to choose the most reliable and cost-effective capsule wardrobe for a profession, explaining how representative data supports my conclusion
- I can connect probability, observed frequency, and multistep ratio-percent calculations to compare options, identify discrepancies, and defend a thoughtful recommendation that addresses the needs of the community.
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Deeper Learning Competencies
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Content Expertise
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- I can use a simple data sample from thrift-store clothing or paper-doll outfit choices to identify a few career-appropriate items and tell whether the sample seems representative
- I can solve basic cost or percent problems with support and make a simple prediction about which clothing pieces are more likely to be available.
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- I can collect and organize sample data about clothing availability, then use ratios or percentages to compare costs and see which items are practical for a capsule wardrobe
- I can build a probability model for outfit or clothing choices and compare it to what I observe in the sample.
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- I can use representative samples and probability models to explain how likely it is to find versatile, career-appropriate clothing within a budget
- I can accurately compare predicted and observed frequencies, and use ratio and percent calculations to justify recommendations for a thrift-store shopping guide.
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- I can independently analyze representative thrift-store data, justify why my sample supports my conclusions, and explain any differences between predicted and observed results
- I can combine probability, proportional reasoning, and cost analysis to create a polished capsule wardrobe recommendation that helps a specific career community dress for success on a budget.
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Deeper Learning Competencies
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Collaboration
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- I can participate in a team task by sharing ideas, listening to others, and helping create a basic paper-doll outfit or wardrobe choice for a profession
- I can contribute to group decisions when the choices are already clear and I can explain my own role in the plan.
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- I can work with my team to sort clothing options by profession, budget, and usefulness, and I can help make fair decisions using data we collect from our paper-doll challenge or sample thrift-store information
- I can use feedback from teammates and a career counselor to improve our recommendation card with support.
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- I can collaborate with my team to divide tasks, compare ideas, and use representative sample data, probability results, and cost calculations to build a practical capsule wardrobe recommendation
- I can explain how our group decisions were based on evidence and adjust our plan when new data or feedback shows a better choice.
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- I can lead and contribute to a team process that uses sampling, probability, ratios, and percent calculations to create a clear, accurate, and audience-friendly thrift-store shopping guide for a specific career
- I can help my team resolve disagreements, justify our choices with data and community feedback, and revise our product so it is useful for people starting a new career.
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Deeper Learning Competencies
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Effective Communication
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- I can share my ideas and questions about a career clothing guide using simple words, pictures, or examples, and I can listen to a partner or team member when we discuss which outfit pieces fit the budget and profession
- I can help my group explain at least one choice from our paper-doll challenge or survey results.
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- I can explain my thinking clearly when I describe why some clothing pieces work better for a career and budget, and I can use evidence from our sample data, probability results, or cost calculations to support my ideas
- I can respond to feedback from teammates or a career counselor and revise part of my guide to make it clearer.
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- I can present my group’s thrift-store shopping guide with organized reasoning, using representative sample data, probability models, and ratio or percent calculations to explain how our recommendations meet the career needs and budget
- I can communicate respectfully with my team and audience, compare predicted and observed results, and revise our work based on feedback and any differences we notice.
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- I can communicate a polished, persuasive thrift-store shopping guide that clearly explains how to dress for success on a budget for a specific profession, using accurate data, probability reasoning, and proportional calculations
- I can adapt my message for community members, answer questions with evidence, and help my team refine our recommendations so they are practical, career-appropriate, and ready for the thrift store or showcase.
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Deeper Learning Competencies
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Academic Mindset
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- I can identify a personal strength, role, or interest I bring to our team and help with a small part of our capsule-wardrobe project, such as organizing ideas, choosing clothing pieces, or recording simple data from our paper-doll challenge
- I can use feedback from my peers or a career counselor to name one way our guide can better support people starting a new career.
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- I can explain how my team’s choices and samples help us learn about what clothing is likely to work for a job and budget, and I can contribute to a representative survey, probability model, or cost calculation
- I can revise my work with support to make our thrift-store guide more practical, respectful, and clear for shoppers.
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- I can use data, probability, ratios, and percent calculations to justify which wardrobe pieces are most versatile and affordable for a specific profession, and I can explain why our sample is or is not representative
- I can collaborate with my team to revise our shopping guide based on observed results and expert feedback, showing growing confidence in sharing ideas and making decisions.
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- I can independently reflect on what my team learned from the launch challenge, representative sampling, and probability comparisons, and use that learning to improve our capsule wardrobe recommendations for real community needs
- I can confidently communicate how our evidence, calculations, and feedback show that our guide helps people dress for success on a budget, and I can support others by contributing thoughtful ideas, respectful listening, and shared leadership throughout the project.
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