Although much has been written about the potential benefits of effective data use in schools, considerably less attention has been paid to how schools make sense of the data generated from performance-based accountability measures. This article explores schools’ usage of state test data, the intensity of data use, and the perceived utility of state test data. Our findings uncover nuanced differences in school data use and reveal a key disconnect in the assumptions of performance-based accountability systems, wherein schools may faithfully use state data to inform improvement efforts while fundamentally questioning the validity of the data itself.
Booher-JenningsJ. (2005). Below the bubble: “Educational triage” and the Texas accountability system. American Educational Research Journal, 42, 231-268.
2.
CoburnC. E.TalbertJ. E. (2006). Conceptions of evidence use in school districts: Mapping the terrain. American Journal of Education, 112, 469-495.
3.
DembroskyJ.PaneJ.BarneyH.ChristinaR. (2005, December). Data decision making in southwestern Pennsylvania school districts (pp. 1-59). Pittsburgh, PA: RAND Education.
4.
DoyleD. P. (2003, September). Data-driven decision-making: Is it the mantra of the month or does it have staying power?T.H.E. Journal, 30(10), 19-21.
5.
EarlL. M.KatzS. (2006). Leading schools in a data-rich world. Thousand Oaks, CA: Corwin Press.
6.
Education Commission on the States. (2002). Data-driven decision making (No Child Left Behind Issue Brief, Report: GP-02-10). Denver, CO: Author.
7.
Farley-RippleE. N. (2008). Accountability, evidence, and school district decision-making. Available from ProQuest Dissertations and Theses Database. (Accession Order No. 3328555)
8.
FeldmanJ.TungR. (2001). Using data-based inquiry and decision making to improve instruction. ERS Spectrum, 19, 10-19.
9.
FinniganK. S.DalyA. J.CheJ. (2012, May). The acquisition and use of evidence districtwide. Paper presented at American Educational Research Association (AERA), Vancouver, British Columbia, Canada.
10.
GallagherL.MeansB.PadillaC. (2008). Teachers’ use of student data systems to improve instruction: 2005 to 2007. Washington, DC: U.S. Department of Education, Office of Planning, Evaluation and Policy Development.
11.
GoertzM. E.OlahL. N.RigganM. (2009). From testing to teaching: The use of interim assessments in classroom instruction. Philadelphia, PA: The Consortium for Policy Research in Education.
12.
HaertelE. H.HermanJ. L. (2005). A historical perspective on validity arguments for accountability testing. In HermanJ. L.HaertelE. H. (Eds.), Uses and misuses of data for educational accountability and improvement (pp. 1-34). Chicago, IL: National Society for the Study of Education.
13.
HamiltonL. S.BerendsM.StecherB. M. (2005). Teachers’ responses to standards-based accountability. Santa Monica, CA: RAND.
14.
HermanJ.GribbonsB. (2001). Lessons learned in using data to support school inquiry and continuous improvement: Final report to the Stuart Foundation. Los Angeles: University of California.
15.
KerrK. A.MarshJ. A.IkemotoG. S.DarilekH.BarneyH. (2006). Strategies to promote data use for instructional improvement: Actions, outcomes, and lessons from three urban districts. American Journal of Education, 112, 496-520.
16.
LinnR. (2005). Issues in the design of accountability systems. In HermanJ. L.HaertelE. H. (Eds.), Uses and misuses of data for educational accountability and improvement (pp. 78-98). Chicago, IL: National Society for the Study of Education.
17.
MarshJ. A.PaneJ. F.HamiltonL. A. (2005). Making sense of data-driven decision making in education (RAND Education Occasional Paper). Available from http://www.rand.org
18.
MarshJ. A.RobynA. (2006). School and district responses to the No Child Left Behind Act (RAND Working Paper, WR-382-EDU). Santa Monica, CA: RAND. Available from http://www.rand.org
19.
MasonS. A. (2002). Turning data into knowledge: Lessons from six Milwaukee public schools. Madison: Wisconsin Center for Education Research.
20.
MassellD. (2001). The theory and practice of using data to build capacity: State and local strategies and their effects. In FuhrmanS. H. (Ed.), From the capitol to the classroom: Standards-based reform in the states (pp. 148-169). Chicago, IL: The University of Chicago Press.
21.
O’DayJ. (2002). Complexity, accountability, and school improvement. Harvard Educational Review, 73(3), 1-37.
StecherB. M.EpsteinS.HamiltonL. S.MarshJ. A.RobynA.McCombsJ. S.. . . NaftelS. (2008). Pain and gain: Implementing No Child Left Behind in three states, 2004-2006. Santa Monica, CA: RAND. Available from http://www.rand.org
24.
StringfieldS. (1994). A model of elementary school effects. In ReynoldsD.CreemersB. P. M.NesselrodtP. S.SchafferE. C.StringfieldS.TeddlieC. (Eds.), Advances in school effectiveness research and practice (pp. 153-187). Oxford, UK: Pergamon Press.
25.
StringfieldS.ReynoldsD.SchafferE. (2001, January). Fifth-year results from the high reliability schools project. Symposium presented at the meeting of the International Congress for School Effectiveness and Improvement, Toronto, Ontario, Canada.
26.
SupovitzJ. A.KleinV. (2003). Mapping a course for improved student learning: How innovative schools systematically use student performance data to guide improvement. Philadelphia, PA: The Consortium for Policy Research in Education.
27.
SymondsK. W. (2003). After the test: How schools are using data to close the achievement gap. San Francisco, CA: Bay Area School Reform Collaborative.
28.
TeddlieC.ReynoldsD. (2000). The international handbook of school effectiveness research. London, England: Falmer.
29.
WaymanJ. G.StringfieldS. (2006). Data use for school improvement: School practices and research perspectives. American Journal of Education, 112, 463-468.
