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Data Smarts

Data Smarts. Looking at Trend Data Before Jumping. Agree or Disagree. Data have no meaning. Knowledge is both a personal and a social construction. There is a reciprocal influence between the culture of the workplace and the thinking and behavior of its members. Wellman and Lipton, 2004.

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Data Smarts

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  1. Data Smarts Looking at Trend Data Before Jumping

  2. Agree or Disagree • Data have no meaning. • Knowledge is both a personal and a social construction. • There is a reciprocal influence between the culture of the workplace and the thinking and behavior of its members. Wellman and Lipton, 2004

  3. Agree or Disagree • Understanding should precede planning. • Cycles of inquiry, experimentation and reflection accelerate continuous growth and learning. • Norms of data-driven collaborative inquiry generate continuous improvements in student learning. Wellman and Lipton, 2004

  4. Key Things to Remember About Data • Just Numbers 2 7 0 3 1 6 5 9 6 6 (2 7 0) 3 1 6- 5 9 6 6

  5. Key Things to Remember About Data • Just Numbers • Made to Look How We Want

  6. Key Things to Remember About Data • Just Numbers • Made to Look How We Want

  7. Key Things to Remember About Data • Just Numbers • Made to Look How We Want • No Actions from Data

  8. Key Things to Remember About Data • Just Numbers • Made to Look How We Want • No Actions from Data • Without Context

  9. Data is Like

  10. Data Wise Improvement Process • Prepare • Organize for Collaborative Work • Build Assessment Literacy • Inquire • Create Data Overview • Dig into Student Data • Examine Instruction

  11. Data Wise Improvement Process • Act • Develop Action Plan • Plan to Assess Progress • Act and Assess

  12. PREPARE—Organizing for Collaborative Work • Build Strong System of Teams • Create a Schedule for Regular Collaborative Work • Plan Productive Meetings • Establish Group Norms • Compass Points Protocol

  13. Compass Points Protocol • Select one of the four characterizations that best describes your orientation when working on a team: • North—Just Get it Done • West—Pay Attention to Details • East—Look at the Big Picture • South—Take into Account Everyone’s Feelings • Strengths and OFIs

  14. Inquiry

  15. Data Analysis 5-Step Process • Table—Create a Table of Your Data. • Graph—Graph Results from the Table. • Observations—What is the data showing you? WriteStatements about the Data. • HOPs—Write a Hypothesis of Practice. We have . . . Example: We have students that are on grade level that are not proficient. • Connections—What You Might Do.

  16. ACT—Develop Action Plan • Theory of Action • If we do X, then Y follows. • Look at many strategies and discuss impact and feasibility. • How will you recognize it? What are the indicators for all groups involved. • Draft an action plan with a clear objective, strategy and assessment. • Think about support to all groups involved.

  17. MAP Growth Data—Grade 1

  18. MAP Data

  19. Student Level Data • Who? • What? • When? • Where? • Why?

  20. TELL Survey

  21. Key Data Points to Track in Unbridled Learning • Breakdowns of Novice-Apprentice-Proficient-Distinguished by Grade Level by Subject • Follow by Cohort Group—Graduating Class of 20XX • Tip the Scale—Percent N/A Compared to Percent P/D

  22. Key Data Points to Track in Unbridled Learning • College/Career Readiness • Number of Seniors CCR Starting the Year CCR • Percent CCR Based on EXPLORE, PLAN and ACT

  23. Key Data Points to Track in Schools • T-PGES • Student Growth Goals • Non-Academic • Attendance • Discipline

  24. Write Around. . . • Name • My school/district needs to improve X. • What data might the school collect?

  25. TREND • T—Think, Slow Down • R—Read the Data • E—Encourage Multiple Data Points—Not One Point in Time • N—Notice the Students—We Don’t Teach Widgets • D—Drive the Change, Focus on the Teaching and Learning

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