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Using Data to Drive Improvement

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  1. Using Data to Drive Improvement Presented by: Sherry Ward, M.S. Ed., PD

  2. Today we will examine: • Setting the stage for data use • Collaborative structures for using data • Data use cycles • Establishing protocols for data use • Data sources and multiple measures • Analyzing data

  3. Setting the stage for a data-driven culture

  4. Collaborative Structures for Data Use

  5. Stages of Data User Process 1. Begin the inquiry, identify objectives, and define questions: What do we need to know? 2. Determine what types of data are needed to answer the questions, how the data will be collected, and who will be responsible for collection. 3. Collect and disaggregate the data. 4. Determine how the data will be summarized, analyzed, and interpreted. 5. Determine with what audiences the data will be shared and the appropriate presentations. 6.Provide a framework for the data dialogue; design appropriate solutions and an action plan.

  6. Making data an ongoing cycle of instructional improvement

  7. Ongoing Data Cycle

  8. Three (3) data tips: • Start small….think big • Repetition helps…get through the cycle several times each year • Be audacious….keep your vision in mind….boldly move forward

  9. Protocols to support data use • School leadership team review and revising the Action Plan/School Improvement Plan meeting protocol • Assessment Writing meeting protocol • Data analysis meeting protocol • Lesson planning meeting protocol

  10. So Much Data…So Little Time... • What will it tell you? • What do you need to know? • How can it help you? • Where is it found?

  11. Quantitative Data Sources • ABCs • AYP • EVAAS • Disaggregated • Goal Summary • LEA and School Report Cards • ABCTools Reports • School / District benchmark tests

  12. AYP and ABCs • •

  13. Disaggregated Report •

  14. NC School Report Cards •

  15. Teacher Work Condition (TWC) Survey •

  16. Education Value-Added Assessment System (EVAAS) NC DPI EVAAS Login

  17. ABCTools • Historical Audit Report • Matrix Report

  18. Goal Summary Reports

  19. Indicators Filling in the missing pieces of the puzzle

  20. Indicators are used for: 1. creating district, school, and student profiles; • developing comprehensive progress reports for accountability purposes; and • reflecting, planning, and decision making.

  21. What’s the right mix of data?

  22. Professional Development, Class Size, Reading/Math Programs, Tutoring, After-School, Summer School, Finance Demographics School Processes Perceptions Student Learning Enrollment, Attendance, Drop-out Rate, Ethnicity, Gender, Grade Level, Teachers Standardized Tests, Norm/Criterion Referenced Tests, Teacher Observations of Abilities, Authentic Assessments Perceptions of Learning Environments, Values and Beliefs, Attitudes, Observations

  23. Changes in the context of the school Demographics How classrooms change School Processes Perceptions Information on student performance on different measures Student Learning Improvements in the environment

  24. Tells us if different groups of students are experiencing school differently Tells us student participation in different programs and processes Demographics Allows the prediction of actions/ processes/ programs that best meet the learning needs of all students School Processes Perceptions Tells us if a program is making a difference in student learning results Student Learning Tells us the impact of student perception of the learning environment on student learning

  25. Creating a Culture of Inquiry “Willingness to ask questions – and to look for the real answers- gets to the heart of how data can stimulate the school change process.” Ruth S. Johnson, “Using Data to Close the Achievement Gap: How to Measure Equity in Our Schools”, 2002

  26. Where are we?Why are we here?What needs to change?

  27. What Does the Data Tell Us?

  28. Examining raw data • AYP • ABCs • School Report Card • NCTWC Survey

  29. Analyzing the Root Causes Why?

  30. Developing testable hypotheses • Based upon what we’ve found out about our issue while completing a root cause analysis, what would improve outcomes for students?

  31. Data-driven decisions are essential to improvement

  32. DARE TO BE “AUDACIOUS” “Every great advance in science has issued from a new audacity of imagination.” - John Dewey, The Quest for Certainty: A Study of the Relation of Knowledge and Action

  33. Citations Bernhardt,V. L., (1998,March), Multiple Measures, Invited Monograph No. 4.California Association for Supervision and Curriculum Development (CASCD) Learning Point Associates, (2004, December), Guide to Using Data in School Improvement Efforts: A Compilation of Knowledge from Data Retreats and Data Use at learning Point Associates U.S. Department of Education, Doing What Works, /