Adding It All Up Data-Driven Minds: Prepping Students for a Smarter Future
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Jul 9, 2025 Joshua Sawyer, a seasoned educator with two decades of experience, and Mahmoud Harding, an instructional design director specializing in K-12 data science, delve into the world of data literacy and its importance in math education. They break down the difference between data literacy and data science, highlighting how both empower students to transition from data consumers to creators. Tips on integrating data into the classroom, using relatable analogies, and recommending practical resources make for an engaging discussion on preparing students for a data-centric future.
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Literacy vs. Science: Distinct Skill Sets
- Data literacy focuses on reading, interpreting, and critiquing data while data science focuses on generating insights through hands-on analysis using tools.
- Mahmoud Harding emphasizes ethics, source critique, visualization, and computational processes as distinct but connected skills.
Music Analogy For Data Skills
- Joshua Sawyer compares data literacy to musical appreciation and data science to being a musician who composes and deconstructs music.
- The analogy highlights appreciation versus application when working with data.
Begin With One Small Data Lesson
- Start small and be intentional: change one or two lessons to incorporate data and align them with existing standards and pacing.
- Use simple contexts (favorite colors, shows) to prompt questions about data collection, inclusion, and representation.