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Empowering Educators: Unpacking Data Literacy for Effective Teaching

Explore data literacy principles, L4GA baseline findings, and instructional recommendations for teachers. Understand data interpretation, instructional decision-making, and reading skills data tiers. Gain insights from data survey conceptual frameworks and preliminary findings.

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Empowering Educators: Unpacking Data Literacy for Effective Teaching

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  1. Enhancing Data Literacy: Using and Unpacking L4GA Baseline data Gary E. Bingham, Kevin Fortner, Rihana Mason Georgia State University

  2. Agenda • Data Literacy Principles • Discuss Survey Initial Findings • Discuss L4GA Initial Findings • Recommendations

  3. Surrounded by Information

  4. What is Data Literacy? • The nature of the specific knowledge and skills teachers need to use data effectively • Gummer & Mandinach, 2015

  5. Necessary & Important

  6. Data for What Purpose?

  7. Georgia’s Continuous Improvement Cycle

  8. What do Effective Teachers Do? • Identify a student learning issues • Using data • Verify the causes of the learning challenges • Generate possible solutions or instructional practices that target the learning challenge • Implement instructional strategies • Monitor instructional outcomes • (Repeat) Love, Stiles, Mundry, & DiRanna, 2008

  9. Data Literacy • Data Location • Finding relevant information • Who houses data? Where is it located? Access? • Data Comprehension • What do the data signify? • Data Interpretation • Figuring out what the data mean • Instructional Decision Making • Selecting an instructional approach that addresses the situation or learning need identified • Question Posing • Framing instructionally relevant questions of data • Querying Data • What conditions best support student performance?

  10. ReadingSkills

  11. Data Tiers

  12. PALS-PreK

  13. PreKL4 Data

  14. PALS-PreK?

  15. Data Survey Preliminary Findings

  16. DATA SURVEY CONCEPTUAL FRAMEWORK(adapted from IES REL Appalachia) General Attitudes Perceptions of Data Quality Wayman, Wilkerson, Cho, Mandinach, & Supovitz, 2016

  17. Four Groups N = 757 Respondents

  18. Data is Useful?

  19. Data is Useful?

  20. Identify Learning Goals?

  21. Identify Learning Goals?

  22. Identify Learning Goals?

  23. Data Literacy Survey Draft Results

  24. Ownership & Collaboration?

  25. DATA SURVEY CONCEPTUAL FRAMEWORK(adapted from IES REL Appalachia) General Attitudes Perceptions of Data Quality Wayman, Wilkerson, Cho, Mandinach, & Supovitz, 2016

  26. Year 1 of Striving Readers Initial Data

  27. Data Process

  28. DIBELS-NWF Across Timepoints by Grade Nonsense Word Alphabetic Principle

  29. DIBELS- NEXT ORAL READING FLUENCY

  30. DIBELS-DORF Across Three Time Points by Grade Oral Reading Fluency

  31. HMH-RI • Lexile Framework for reading provides a common scale for measuring text difficulty and student reading ability Vocabulary Comprehension

  32. Reading Inventory Primary Grades

  33. Reading RI Reading Inventory Middle School

  34. Reading Inventory High School

  35. Prior Funded LEAS?

  36. Take Home Messages

  37. Moving Forward • Uploading data in timely manner • Quicker analysis • Helps us spot challenges • Communicate with GA DOE when changes take place • Vendor change? Challenging experiences? • Collaboration and Communication is Key • Various stakeholders and purposes • Communicate with us around the templates • How are they working? Feedback? • Available for consultations at 3pm • Be a Resource to others • Prior vs. New LEAs to L4

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