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Boone Central Data Training

Boone Central Data Training. November 28, 2011 Toby Boss ESU 6. My Background. Goals. To increase knowledge about the use of data to influence instruction To form a consistent vocabulary for the use of data

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Boone Central Data Training

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  1. Boone Central Data Training November 28, 2011 Toby Boss ESU 6

  2. My Background

  3. Goals • To increase knowledge about the use of data to influence instruction • To form a consistent vocabulary for the use of data • To build a common practice for analyzing data through organization, management and use

  4. Wiki • http://boonecentraldata.wikispaces.com/ • See Agenda

  5. Looking at Data

  6. Goal • To increase knowledge about the use of data to influence instruction

  7. Why is data important?

  8. “Without data, you’re just another person with an opinion.” Scott Ebbrecht, Principal in Westernville, Ohio

  9. Always keep the kid in the chair

  10. School Improvement Empowerment NCLB Assessments Site Based Decision Making Standards Accountability SafeSchools StaffDevelopment School-to-Work What is required to focus our efforts?

  11. The Big Arrow Aim of the District

  12. Aim of the District District Goals& Measures Random Acts of Improvement

  13. Aim of the District District Goals & Measures Aligned Acts of Improvement

  14. Teachers were asked “To what attribute do you attribute the lack of achievement of your students?” • Some teachers indicated characteristics of students, lack of motivation, their parents, socioeconomic status, etc. • Some teachers indicated things that teachers do, looking at their skills. • Students taught by teachers who were concerned about teacher skills achieved 3 times higher than those whose teachers cited student characteristics.

  15. The Real Question • What is it that WE are doing that might contribute to these results? • The objective here is to reflect about our practices and determine where WE can improve what WE do.

  16. Problem or Condition • A “problem” is something we can do something about, so we can focus time and energy in that direction. • A “condition” is something that we cannot do anything about—we acknowledge it and go around it, but we do not waste time trying to change it.

  17. For Example… • Through disaggregation we find students from single parent families are not reading at grade level by 3rd grade. • Coming from a single parent family is a condition. • Reading below grade level is a problem. • Strategies and interventions can be implemented based on the condition. • Establish a mentor program. • Create a before or after school program.

  18. What are some other “conditions”?

  19. What are some other “problems”?

  20. Some Ground Rules • Don’t blame kids; it is not their fault. • Don’t use kids as excuses. • Don’t blame teachers. • Data is just information about the current state of affairs. • These are our students. • The real question is “What are we going to help our students learn.”

  21. continuous improvement • members of an organization acquire and use information to change and implement action

  22. use data to: • ask the right questions • define needs • plan interventions • evaluate progress

  23. Data should inform teams about how to improve learning.

  24. Teamwork

  25. Why is data important?

  26. Goal • To form a consistent vocabulary for the use of data.

  27. Measures • Norm Referenced • Criterion Referenced

  28. Norm Referenced • Measure student performance against a group (called a norm) • A common way to present information is in the form of a bell curve. • Norm referenced guarantees a set number of students in each performance category – based on how well they perform against each other.

  29. NRT • terra nova • Itbs • nwea • stanford • explore • plan

  30. national stanines • normalized test scores that divide the normal curve into broad intervals ranging from 1 to 9

  31. scale score • mathematically transformed raw score • depend on test taken • range is 1-999 • scales span all levels and grades of test

  32. national percentilenp • norm referenced • range from 1-99 • specify the percentage of students in a national norm group whose scores fall below the given students test score

  33. normal curve equivalent nce • normalized test scores on an equal interval scale • range from 1 - 99 with one point change same throughout

  34. limitations • extent to which the test captures and covers the domain it is trying to measure • not sufficiently aligned to curricular standards and instructional emphasis

  35. Criterion Referenced • Student performance is judged against a criteria. • No set number of students in performance categories.

  36. Student Performance Data

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