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Educator Professional Development Onboarding to the Data Science Learning Progressions

Hannah Kurzweil

Section Putting It All Together: Your Personal Toolkit Action Plan

You’ve explored strategies for selecting tools, finding datasets, setting up technology, and evaluating new resources. Now let’s create a concrete plan for building and maintaining your data science toolkit over time.
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Exploration 55. Choose Your Toolkit Development Approach.

Consider which approach matches your current situation and comfort level:
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Option 1: Minimalist Approach - Start with 1-2 tools you can master completely before adding anything new. Focus on paper-based backups and simple digital tools.
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Option 2: Gradual Builder - Identify 3-4 core tools and spend this year becoming proficient with them. Add one new tool each semester based on emerging needs.
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Option 3: Early Adopter - Comfortable with technology and want to explore multiple options. Focus on systematic evaluation and documentation of what works.
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Option 4: Collaborative Approach - Partner with colleagues to share toolkit development. Different people focus on different tool categories and share discoveries.
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Checkpoint 103.

What’s the most important principle to remember when building your data science toolkit?
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Hint.
Think about the purpose of the toolkit and what makes it most useful for teaching.
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Solution.
The best toolkit is the one that helps you teach data science concepts effectively and consistently. It should reduce your workload, not increase it. Tools should be reliable, appropriate for your students, and aligned with your teaching goals. Don’t chase the latest trends—focus on building a solid foundation of tools you can use confidently.
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Checkpoint 104. My Data Science Toolkit Action Plan.

Create your specific plan for building and maintaining your toolkit over the next year.
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(a)

Which development approach (minimalist, gradual builder, early adopter, collaborative) best fits your situation? Why?
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(b)

List 3 specific tools you want to set up and test in the next month. What will you use each one for?
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(c)

Identify 5 datasets you want to find and organize for immediate use. What subjects/topics will they support?
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(d)

How will you stay organized and avoid toolkit overwhelm? What boundaries will you set?
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(e)

Who can you partner with or learn from as you build your toolkit? How will you connect with other data science educators?
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Remember: Your toolkit should evolve with your teaching practice. Start simple, build systematically, and focus on tools that enhance student learning.
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Checkpoint 105.

Before moving to the final module, reflect: What aspects of toolkit building feel most exciting to you? What feels most challenging? How will you maintain momentum as you develop your resources over time?
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