How are we approaching data-informed practice? Development of the Survey of Data Use and Professional Learning

  • Jo Beth Jimerson


As in international schooling contexts, talk about data-driven practice has become ubiquitous in schooling dialogues in the USA, and with the pending reauthorization of the No Child Left Behind Act (the main driver of increased data use in American schools), educators in the USA should expect even greater calls for formalized data use. Yet, the field lacks readily accessible tools that allow school district leaders and evaluators to examine educator perceptions related to data-informed practice. This paper outlines the process used in the development, testing, and validation of one instrument that district leaders and evaluators may use to learn more about the ways in which data are used and perceived in their respective contexts. Potential applications as well as limitations of the instrument are outlined.


Educational data use Data-driven decision making Educational data use Continuous improvement School improvement Survey construction Professional learning for data use 



The author wishes to acknowledge and graciously thank Dr. Judy Groulx and the late Dr. Sherrie Reynolds, faculty mentors at TCU whose encouragement and assistance greatly strengthened this work. The author also thanks Dr. Annie Nguyen for her assistance and insights during the preparation of the manuscript.


  1. Anderson, S., Leithwood, K., & Strauss, T. (2010). Leading data use in schools: organizational conditions and practices at the school and district levels. Leadership and Policy in Schools, 9(3), 292–327. doi: 10.1080/15700761003731492/.CrossRefGoogle Scholar
  2. Berliner, D. (2013). Problems with value-added evaluations of teachers? Let me count the ways! The Teacher Educator 48(3), 2013)Google Scholar
  3. Booher-Jennings, J. (2005). Below the bubble: “Educational triage” and the Texas accountability system. American Educational Research Journal, 42(2), 231–268.CrossRefGoogle Scholar
  4. Boudett, K. P., City, E. A., & Murnane, R. J. (Eds.). (2005). Data Wise: a step-by-step guide to using assessment results to improve teaching and learning. Cambridge, MA: Harvard Education Press.Google Scholar
  5. Brown, C. (2014). Advancing policy makers’ expertise in evidence-use: a new approach to enhancing the role research can have in aiding educational policy development. Journal of Educational Change, 15(1), 19–36.CrossRefGoogle Scholar
  6. Brown, C. & Rogers, S. (2014). Knowledge creation as an approach to facilitating evidence informed practice: examining ways to measure the success of using this method with early years practitioners in Camden (London). Journal of Educational Change, early online publication, DOI 10.1007/s10833-014-9238-9Google Scholar
  7. Cho, V., & Wayman, J. C. (2014). Districts’ efforts for data use and computer data systems: the role of sensemaking in system use and implementation. Teachers College Record, 116(2), 1–45.Google Scholar
  8. Coburn, C. E., Honig, M. I., & Stein, M. K. (2009). What’s the evidence on districts’ use of evidence? In J. D. Bransford, D. J. Stipek, N. J. Vye, L. M. Gomez, & D. Lam (Eds.), The role of research in educational improvement (pp. 67–87). Cambridge: Harvard Education Press.Google Scholar
  9. Copland, M. (2003). Leadership of inquiry: building and sustaining capacity for school improvement. Educational Evaluation and Policy Analysis, 25(4), 375–395.CrossRefGoogle Scholar
  10. Creswell, J. W. (2003). Research design: qualitative, quantitative, and mixed methods approaches (2nd ed.). Thousand Oaks, CA: SAGE.Google Scholar
  11. Daly, A. (2009). Rigid response in an age of accountability: the potential of leadership and trust. Educational Administration Quarterly, 45(2), 168–216.CrossRefGoogle Scholar
  12. Darling-Hammond, L., Wei, R. C., Andree, A., Richardson, N., & Orphanos, S. (2009). Professional learning in the learning profession: a status report on teacher development in the United States and abroad. Dallas, TX: National Staff Development Council.Google Scholar
  13. Datnow, A. (2006). Connections in the policy chain: the “co-construction” of implementation in comprehensive school reform. In M. I. Honig (Ed.), New directions in education policy implementation (pp. 105–124). New York: SUNY Press.Google Scholar
  14. Desimone, L. M., & LeFloch, K. C. (2004). Are we asking the right questions? Using cognitive interviews to improve surveys in education research. Educational Evaluation and Policy Analysis, 26(1), 1–22.CrossRefGoogle Scholar
  15. Desimone, L. M., Porter, A. C., Garet, M. S., Yoon, K. S., & Birman, B. F. (2002). Effects of professional development on teachers’ instruction: results from a three-year longitudinal study. Educational Evaluation and Policy Analysis, 24(2), 81–112.CrossRefGoogle Scholar
  16. DuFour, R., Eaker, R., & DuFour, R. (Eds). (2005). On common ground: the power of professional learning communities (pp. 7–29). Bloomington, IN: Solution TreeGoogle Scholar
  17. Earl, L. M., & Katz, S. (2006). Leading schools in a data-rich world: harnessing data for school improvement. Thousand Oaks, CA: Corwin.Google Scholar
  18. Elmore, R. F. (2004). School reform from the inside out: policy, practice, and performance. Cambridge, MA: Harvard University Press.Google Scholar
  19. Fullan, M. (2007). The New Meaning of Educational Change (4th ed.). New York: Teachers College Press.Google Scholar
  20. Groves, R. M., Fowler, F. J., Couper, M. P., Lepkowski, J. M., Singer, E., & Tourangeau, R. (2009). Survey Methodology (2nd ed.). Hoboken, New Jersey: John Wiley & Sons.Google Scholar
  21. Guskey, T. R., & Yoon, K. S. (2009). What works in professional development? Phi Delta Kappan, 90(7), 495–500.CrossRefGoogle Scholar
  22. Hamilton, L., Halverson, R., Jackson, S., Mandinach, E., Supovitz, J., & Wayman, J. (2009). Using student achievement data to support instructional decision making (NCEE 2009–4067). Washington, DC: National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education.Google Scholar
  23. Honig, M. I. (2006). Complexity and policy implementation: challenges and opportunities for the field. In M. I. Honig (Ed.), New directions in education policy implementation (pp. 105–124). New York: SUNY Press.Google Scholar
  24. Ikemoto, G. S., & Marsh, J. A. (2007). Cutting through the “data-driven” mantra: different conceptions of data-driven decision making. In P. A. Moss (Ed.), Evidence and decision making (pp. 105–131). Malden, MA: Blackwell.Google Scholar
  25. Ingram, D., Louis, K. S., & Schroeder, R. G. (2004). Accountability policies and teacher decision making: barriers to the use of data to improve practice. Teachers College Record, 106(6), 1258–1287.CrossRefGoogle Scholar
  26. Jimerson, J. B., & McGhee, M. (2013). Leading inquiry in schools: examining mental models of data-informed practice. Current Issues in Education, 16(1), 1–20. Retrieved from Scholar
  27. Jimerson, J. B., & Wayman, J. C. (2015). Professional learning for using data: examining teacher needs and supports. Teachers College Record, 117(4), 1–36.Google Scholar
  28. Johnson, B., & Christensen, L. (2013). Educational research: quantitative, qualitative, and mixed approaches. Thousand Oaks, CA: Sage Publications.Google Scholar
  29. Katz, S., & Dack, L. A. (2014). Towards a culture of inquiry for data use in schools: breaking down professional learning barriers through intentional interruption. Studies in Educational Evaluation, 42, 35–40.CrossRefGoogle Scholar
  30. Kennedy, B. L., & Datnow, A. (2011). Student involvement and data-driven decision making: developing a new typology. Youth & Society, 43(4), 1246–1271.CrossRefGoogle Scholar
  31. Kerr, K. I., Marsh, J. A., Ikemoto, G. S., Darilek, H., & Barney, H. (2006). Strategies to promote data use for instructional improvement: actions, outcomes, and lessons from three urban districts. American Journal of Education, 112(August), 496–520.CrossRefGoogle Scholar
  32. Louis, K. S. (2007). Trust and improvement in schools. Journal of Educational Change, 8, 1–24.CrossRefGoogle Scholar
  33. Louis, K. S., Leithwood, K., Wahlstrom, K. L., Anderson, S. E., Michlin, M., Mascall, B., Gordon, M., Strauss, T., Thomas, E., & Moore, S. (2010). Learning from leadership: investigating the links to improved student learning (final report of research findings). New York, NY: The Wallace Foundation.Google Scholar
  34. Mandinach, E. B. (2012). A perfect time for data use: using data-driven decision making to inform practice. Educational Psychologist, 47(2), 71–85.CrossRefGoogle Scholar
  35. Mandinach, E. B., & Gummer, E. S. (2013). A systemic view of implementing data literacy in educator preparation. Educational Researcher, 42(1), 30–37.CrossRefGoogle Scholar
  36. Mandinach, E. B., & Jackson, S. S. (2012). Transforming teaching and learning through data-driven decision making (Classroom insights from educational psychology series). Thousand Oaks, CA: Corwin.CrossRefGoogle Scholar
  37. Marsh, J.A., Pane, J.F., & Hamilton, L.S. (2006). Making sense of data-driven decision making: evidence from Recent RAND research.
  38. Marsh, J. A., McCombs, J. S., & Martorell, F. (2010). How instructional coaches support data-driven decision making: policy implementation and effects in Florida middle schools. Educational Policy, 24(6), 872–907.CrossRefGoogle Scholar
  39. Marsh, J. A., Farrell, C. C., & Bertrand, M. (2014). Trickle-down accountability: how middle school teachers engage students in data use. Educational Policy. doi: 10.1177/0895904814531653.Google Scholar
  40. Means, B., Padilla, C., DeBarger, A., & Bakia, M. (2009). Implementing data-informed decision-making in schools—Teacher access, supports and use. Washington, D.C.: U.S. Department of Education Office of Planning, Evaluation and Policy Development.Google Scholar
  41. Means, B., Chen, E., DeBarger, A., & Padilla, C. (2011). Teachers’ ability to use data to inform instruction: challenges and supports. Washington, CD: U.S. Department of Educat5ion, office of Planning, Evaluation, and Policy Development.Google Scholar
  42. Militello, M., Bass, L., Kackson, K. T., & Wang, Y. (2013). How data are used and misused in schools: perceptions from teachers and principals. Education Sciences, 3, 98–120.CrossRefGoogle Scholar
  43. National Forum on Education Statistics [NFES]. (2012). Forum Guide to Taking Action with Education Data. (NFES 2013–801). U.S. Department of Education. Washington, DC: National Center for Education StatisticsGoogle Scholar
  44. Olsen, B., & Sexton, D. (2009). Threat rigidity, school reform, and how teachers view their work inside current education policy contexts. American Educational Research Journal, 46(1), 9–44.CrossRefGoogle Scholar
  45. Park, V., & Datnow, A. (2009). Co-constructing distributed leadership: district and school connections in data-driven decision-making. School Leadership and Management, 29(5), 477–494.CrossRefGoogle Scholar
  46. Rallis, S. F., & Rossman, G. B. (2012). The research journey. New York: Guilford Press.Google Scholar
  47. Saunders, L. (2014). “Decoro, Sprezzatura, Grazia”-A creative metaphor for teaching and teachers’ learning today? Professional Development Today, 16(2), 12–20.Google Scholar
  48. Schildkamp, K., & Kuiper, W. (2010). Data-informed curriculum reform: which data, what purposes, and promoting and hindering factors. Teaching and Teacher Education, 26, 482–496.CrossRefGoogle Scholar
  49. Schildkamp, K., & Teddlie, C. (2008). School performance feedback systems in the USA and in The Netherlands: a comparison. Educational Research and Evaluation, 14(3), 255–282.CrossRefGoogle Scholar
  50. Senge, P. M. (2006). The fifth discipline: the art & practice of the learning organization. New York: Currency Doubleday.Google Scholar
  51. Shen, J., & Cooley, V. E. (2008). Critical issues in using data for decision-making. International Journal of Leadership in Education, 11(3), 319–329.CrossRefGoogle Scholar
  52. Supovitz, J. (2012). Getting at student understanding—The key to teachers’ use of data. Teachers College Record 114(11)Google Scholar
  53. Supovitz, J. A., & Klein, V. (2003). Mapping a course for improved student learning: how innovative schools systematically use student performance data to guide improvement. Philadelphia: Consortium for Policy Research in Education- University of Pennsylvania.Google Scholar
  54. Valli, L., & Buese, D. (2007). The changing roles of teachers in an era of high-stakes accountability. American Educational Research Journal, 44(3), 519–558.CrossRefGoogle Scholar
  55. Verhaeghe, G., Vanhoof, J., Valcke, M., & Van Petegem, P. (2010). Using school performance feedback: perceptions of primary school principals. School Effectiveness and School Improvement: An International Journal of Research, Policy and Practice, 21(2), 167–188.CrossRefGoogle Scholar
  56. Wayman, J. C. (2013). Leading data use: pre-service course for principals and superintendents. The Journal of Educational Research & Policy Studies, 13(2), 6–13.Google Scholar
  57. Wayman, J. C., & Cho, V. (2009). Preparing educators to effectively use student data systems. In T. J. Kowalski & T. J. Lasley (Eds.), Handbook on data-based decision-making in education (pp. 89–104). New York: Routledge.Google Scholar
  58. Wayman, J. C., & Jimerson, J. B. (2014). Teacher needs for data-related professional learning. Studies in Educational Evaluation, 42, 25–34.CrossRefGoogle Scholar
  59. Wayman, J. C., & Stringfield, S. (2006). Technology supported involvement of entire faculties in examination of student data for instructional improvement. American Journal of Education, 112, 549–571.Google Scholar
  60. Wayman, J. C., Cho, V., & Johnston, M. T. (2007). The data-informed district: a district-wide evaluation of data use in the Natrona County School District. Austin: The University of Texas.Google Scholar
  61. Wayman, J.C., Cho, V., & Shaw, S. (2009). Survey of Educator Data Use. Unpublished documentGoogle Scholar
  62. Wayman, J. C., Cho, V., Jimerson, J. B., Spikes, D. D. (2012a). District-Wide Effects on Data Use in the Classroom. Education Policy Analysis Archives, 20 (25). Retrieved [date], from
  63. Wayman, J. C., Jimerson, J. B., & Cho, V. (2012b). Organizational considerations in establishing the data-informed district. School Effectiveness and School Improvement, 23(2), 159–178.Google Scholar
  64. Wayman, J. C., Spring, S. D., & Lemke, M. A., Lehr, M.D. (2012c). Using data to inform practice: effective principal leadership strategies. Paper presented at the 2012 Annual Meeting of the American Educational Research Association, Vancouver, CanadaGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Texas Christian UniversityFort WorthUSA

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