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    FEATURE ARTICLE

    What The Right Data Can Do

    Find sources that can help tailor learning to each educator's needs

    By Learning Forward
    Categories: Collaboration
    April 2013
    Learning Forward’s Data standard advocates using data from a variety of sources and types — including student, educator, and system data — to plan, assess, and evaluate professional learning. This presents several challenges, beginning with the emphasis on a variety of sources and types. The pressures of No Child Left Behind have focused American educators on academic student data from large-scale, high-stakes tests —usually connected to school improvement plans that must be developed where Adequate Yearly Progress is not met. Rarely are those data connected directly to plans for professional learning. A second area of challenge relates to what I knew and articulated forcefully about my students, but was slow to discover about my staff when I became a principal: They don’t all need the

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    Authors

    Edie Holcomb

    Edie Holcomb (elholcomb@aol.com) is a consultant and author of Data Dynamics:  Aligning Teacher Team, School, and District Efforts (Solution Tree, 2012).

    Types of Data

    Student

    Academic: Large-scale, common, formative.

    Nonacademic: Attendance, discipline.

    Perceptual: Surveys, focus groups.

    Educator

    Preparation, experience, certification, participation, perceptual.

    System

    Professional learning record, school improvement plans.

    Ways To Differentiate

    • What.
    • How much.
    • What kind.
    • Where and when.
    • Who presents and coaches.

    References

    Bush, R.N. (1984). Effective staff development. In Far West Laboratory for Educational Research and Development, Making our schools more effective: Proceedings of three state conferences (NIE Grant No. 80-0103; pp. 223-240). San Francisco, CA: Far West Laboratory for Educational Research and Development.

     

    Clotfelter, C.T., Ladd, H.F., & Vigdor, J.L. (2007, November). Teacher credentials and student achievement in high school: A cross-subject analysis with student fixed effects (Working Paper No. 13617). Cambridge, MA: National Bureau of Economic Research.

     

    Hall, G.E. & Hord, S.M. (2001). Implementing change: Patterns, principles, and potholes. Boston, MA: Allyn & Bacon.

     

    Hirsh, S. (2009). Foreword. In J. Killion & P. Roy, Becoming a learning school (pp. 5-6). Oxford, OH: NSDC.

     

    Holcomb, E.L. (2007). Students are stakeholders, too! Including every voice in authentic high school reform. Thousand Oaks, CA: Corwin Press.

     

    Holcomb, E.L. (2012). Data dynamics: Aligning teacher team, school, and district efforts. Bloomington, IN: Solution Tree.

     

    Ingersoll, R. (2008, November). Core problems: Out-of-field teaching persists in key academic courses and high-poverty schools. Washington, DC: The Education Trust.

     

    Marzano, R.J. (2007). The art and science of teaching: A comprehensive framework for effective instruction. Alexandria, VA: ASCD.

    Marzano, R.J. (2010). A focus on teaching. In R.J. Marzano (Ed.), On excellence in teaching (pp. 1-4). Bloomington, IN: Solution Tree.


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    Learning Forward is the only professional association devoted exclusively to those who work in educator professional development. We help our members plan, implement, and measure high-quality professional learning so they can achieve success with their systems, schools, and students.


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