2007 MESPA Data-Driven Elementary School Principals

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Dr. Scott McLeod, CASTLE, University of Minnesota; February 7, 2007; Data-Driven Elementary School Principals

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  • 2007 MESPA Data-Driven Elementary School Principals

    1. 1. Data-Driven Elementary School Principals Dr. Scott McLeod University of Minnesota
    2. 2. Get this presentation <ul><li>www.scottmcleod.net/mespa </li></ul><ul><li>www.scottmcleod.net/contact </li></ul><ul><li>www.schooltechleadership.org </li></ul><ul><li>www.dangerouslyirrelevant.org </li></ul>
    3. 3. 9 essential elements of data-driven PLCs Frequent formative assessments Professional learning communities rooted in student information Making instructional changes <ul><li>Data safety Data transparency </li></ul><ul><li>Technology Alignment for results </li></ul>Good baseline data Measurable instructional goals
    4. 4. Statewide DDDM readiness study <ul><li>Teachers (n = 3,135 / 11,120?) (28%?) </li></ul><ul><li>Principals (n = 791 / 1,770) (45%) </li></ul><ul><li>Superintendents (n = 202 / 351) (58%) </li></ul><ul><li>District technology coordinators (n = 139 / 351) (40%) </li></ul><ul><li>4,267 Minnesota educators </li></ul><ul><li>Awesome! </li></ul>
    5. 5. Elementary principals by gender, race / ethnicity 95% White
    6. 6. Elementary principals by urbanicity
    7. 7. All respondents by AYP status
    8. 8. 9 essential elements of data-driven PLCs Frequent formative assessments Professional learning communities rooted in student information Making instructional changes <ul><li>Data safety Data transparency </li></ul><ul><li>Technology Alignment for results </li></ul>Good baseline data Measurable instructional goals
    9. 9. I receive state assessment results each year [teachers]
    10. 10. Teachers receive other yearly assessment results each year
    11. 11. Teachers collaborate to create and use common periodic assessments for student progress monitoring
    12. 12. Teachers use other (not teacher-created) periodic assessments for student progress monitoring
    13. 13. Timeliness and utility of yearly / formative data
    14. 14. Timeliness and utility of yearly / formative data
    15. 15. Timeliness and utility of yearly / formative data
    16. 16. Timeliness and utility of yearly / formative data
    17. 17. Measurable instructional goals
    18. 18. Teacher teams (PLCs) that meet regularly
    19. 19. Making instructional changes
    20. 20. Data access and transparency
    21. 21. Data safety
    22. 22. Technology
    23. 23. Alignment for results
    24. 24. Leadership and support
    25. 25. Professional development
    26. 26. Beliefs
    27. 27. Let’s sum up <ul><li>State test data aren’t very useful </li></ul><ul><li>Teacher feel less positively about school and district DDDM activity than do their administrators </li></ul><ul><li>Significant percentages of teachers are not intersecting with DDDM </li></ul>
    28. 28. Let’s sum up <ul><li>Clear, consistent differential continuum from </li></ul><ul><ul><li>Elementary to middle to secondary </li></ul></ul><ul><ul><li>Meeting AYP to not meeting AYP </li></ul></ul>
    29. 29. Comments
    30. 30. 9 essential elements of data-driven PLCs Frequent formative assessments Professional learning communities rooted in student information Making instructional changes <ul><li>Data safety Data transparency </li></ul><ul><li>Technology Alignment for results </li></ul>Good baseline data Measurable instructional goals
    31. 31. Thank you! <ul><li>www.scottmcleod.net/mespa </li></ul><ul><li>www.scottmcleod.net/contact </li></ul><ul><li>www.schooltechleadership.org </li></ul><ul><li>www.dangerouslyirrelevant.org </li></ul>

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