Interventions to promote data use: An introduction

Teachers College Record

Volumn 114, Issue 11, 2012, Pages

  Turner, Erica O ^a   Coburn, Cynthia E ^b  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84875081577     PISSN: 01614681     EISSN: 14679620     Source Type: Journal    
DOI: None     Document Type: Article

References (66)

1. Armstrong, J., & Anthes, K. (2001). How data can help: Putting information to work to raise student achievement. American School Board Journal, 188(11), 38-41.
2. Bernhardt, V. L. (1998). Data analysis for comprehensive schoolwide improvement. Larchmont, NY: Eye on Education.
3. Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education, 5(1), 7-74.
4. Booher-Jennings, J. (2005). Below the bubble: "Educational triage" and the Texas accountability system. American Educational Research Journal, 42, 231-268.
5. 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.
6. Burch, P., & Hayes, T. (2009). The role of private firms in data-based decision making. In T. J. Kowalski & T. J. Lasley, II (Eds.), Handbook of data-based decision making in education (pp. 54-71). New York: Routledge.
7. Carnoy, M., & Loeb, S. (2002). Does external accountability affect student outcomes? A cross-state analysis. Educational Evaluation and Policy Analysis, 24, 305-331.
8. Christman, J., Neild, R., Bulkley, K., Blanc, S., Liu, R., Mitchell, C., & Travers, E. (2009). Making the most of interim assessment data. Lessons from Philadelphia. Philadelphia, PA: Research for Action.
9. Coburn, C. E. (2010). The Partnership for District Change: The challenges of evidence use in a major urban district. In C. E. Coburn & M. K. Stein (Eds.), Research and practice in education: Building alliances, bridging the divide (pp. 167-182). New York, NY: Rowman & Littlefield.
10. Coburn, C. E., Honig, M. I., & Stein, M. K. (2009). What's the evidence on districts' use of evidence? In J. Bransford, D. J. Stipek, N. J. Vye, L. Gomez, & D. Lam (Eds.), Educational improvement: What makes it happen and why? (pp. 67-86). Cambridge, MA: Harvard Educational Press.
11. Coburn, C. E., Toure, J., & Yamashita, M. (2009). Evidence, interpretation, and persuasion: Instructional decision making in the district central office. Teachers College Record, 111(4), 1115-1161.
12. Coburn, C. E., & Turner, E. O. (2012a). Putting the "use" back in data use: An outsider's contribution to the measurement community's conversation about data use. Measurement: Interdisciplinary Research and Perspectives, 9(4), 227-234.
13. Coburn, C. E., & Turner, E. O. (2012b). Research on data use: A framework and analysis. Measurement: Interdisciplinary Research and Perspectives, 9(4), 173-206.
14. Copland, M. (2003). Leadership of inquiry: Building and sustaining capacity for school improvement. Educational Evaluation and Policy Analysis, 25, 375-395.
15. Daly, A. J. (2012). Data, dyads, and dynamics: Exploring data use and social networks in educational improvement. Teachers College Record, 114(11).
16. Data Quality Campaign. (2011). States could empower stakeholders to make education decisions with data . . . but they haven't yet. Retrieved from http://www.dataqualitycampaign.org/files/DFA2011%20Mini%20report%20findings%20Dec1.pdf
17. Datnow, A., Park, V., & Wohlstetter, P. (2007). Achieving with data: How high-performing school systems use data to improve instruction for elementary stu dents. Los Angeles, CA: University of Southern California, Center on Educa tional Governance.
18. Dee, T. S., & Jacob, B. (2009) The impact of No Child Left Behind on student achievement. NBER Working Paper. Cambridge, MA: National Bureau of Economic Research.
19. Earl, L. M. (2007). Leadership for evidence-informed conversations. In L. M. Earl & H. Timperley (Eds.), Professional learning conversations: Challenges in using evidence for improvement (pp. 43-52). Dordrecht, The Netherlands: Springer.
20. Englert, R. M., Kean, M. H., & Scribner, J. D. (1977). Politics of program evaluation in large city school districts. Education and Urban Society, 9(4), 429-450.
21. Fuchs, L. S., & Fuchs, D. (1986). Effects of systematic formative evaluation: A meta-analysis, Exceptional Children, 53, 199-208.
22. Gottfried, M., Ikemoto, G., Orr, N., & Lemke, C. (2011). What four states are doing to support local data-driven decision-making: policies, practices, and programs (Issues & Answers Report, REL 2012-No. 118). Washington, DC: U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, Regional Educational Laboratory Mid-Atlantic. Retrieved from http://ies.ed.gov/ncee/edlabs
23. Hallett, T. (2010). The myth incarnate: Recoupling processes, turmoil, and inhabited institutions in an urban elementary school. American Sociological Review, 75(1), 52-74.
24. Halverson, R., Grigg, J., Prichett, R., & Thomas, C. (2007). The new instruc tional leadership: Creating data-driven instructional systems in schools. Journal of School Leadership, 17(2), 158-193.
25. Hamilton, L., Halverson, R., Jackson, S., Mandinach, E., Supovitz, J. A., & Wayman, J. C. (2009). Using student achievement data to support instructional decision making (No. NCEE 2009-4067). Washington, DC: National Center for Educational Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education.
26. Henig, J. R. (2012). The politics of data use. Teachers College Record, 114(11).
27. Honig, M. I., & Coburn, C. E. (2008). Evidence-based decision making in school district central offices: Toward a research agenda. Educational Policy, 22(4), 578-608.
28. Honig, M. I., Copland, M. A., Rainey, L., Lorton, J. A., & Newton, M. (2010). Central office transformation for district-wide teaching and learning improvement. Seattle, WA: Center for the Study of Teaching and Policy.
29. Horn, I. S., & Little, J. W. (2010). Attending to problems of practice: Routines and resources for professional learning in teachers' workplace interactions. American Educational Research Journal, 47(1), 181-217.
30. Hout, M., & Elliott, S. W. (Eds.). (2011). Incentives and test-based accountability in public education. Board on Testing and Assessment, Division of Behavioral and Social Sciences and Education, National Research Council. Washington, DC: National Academies Press.
31. Ikemoto, G. S., & Honig, M. I. (2010). Tools to deepen practitioners' engagement with research: The case of the Institute for Learning. In C. E. Coburn & M. K. Stein (Eds.), Research and practice in education: Building alliances, bridging the divide (pp. 93-108). New York, NY: Rowman & Littlefield.
32. 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: National Society for the Study of Education.
33. 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, 1258-1287.
34. Jennings, J. L. (2012). The effects of accountability system design on teachers' use of test score data. Teachers College Record, 114(11).
35. Kennedy, M. M. (1982). Working knowledge and other essays. Cambridge, MA: The Huron Institute.
36. Kennedy, M. M. (1984). How evidence alters understanding and decisions, Educational Evaluation and Policy Analysis, 6(3), 207-226.
37. Kerr, K. A., Marsh, J. A., Ikemoto, G. S., & Barney, H. (2006). Strategies to promote data use for instructional improvement: Actions, outcomes, and lessons from three urban districts. American Journal of Education, 112(4), 496-520.
38. Knapp, M. S., Swinnerton, J. A., Copland, M. A., & Monpas-Huber, J. (2006). Data informed leadership in education. Seattle, WA: Center for the Study of Teaching and Learning.
39. Lasky, S., Schaffer, G., & Hopkins, T. (2008). Learning to think and talk from evidence: Developing system-wide capacity for learning conversations. In L. M. Earl & H. Timperley (Eds.), Professional learning conversations: Challenges in using evidence for improvement (pp. 95-108). Springer.
40. Little, J. W., & Curry, M. W. (2008). Structuring talk about teaching and learning: The use of evidence in protocol-based conversation. In L. M. Earl & H. Timperley (Eds.), Professional learning conversations: Challenges in using evidence for improvement (pp. 29-42). Springer.
41. Little, J. W., Gearhart, M., Curry, M., & Kafka, J. (2003). "Looking at student work" for teacher learning, teacher community, and school reform. Phi Delta Kappan, 83(5), 184-192.
42. Love, N. B., Stiles, K. E., Mundry, S. E., & DiRanna, K. (Eds.) (2008). The data coach's guide to improving learning for all students: Unleashing the power of collaborative inquiry. Thousand Oaks, CA: Corwin Press.
43. Marsh, J. A. (2012). Interventions promoting educators' use of data: Research insights and gaps. Teachers College Record, 114(11).
44. Marsh, J A., Pane, J. F., & Hamilton, L. S. (2006). Making sense of data-driven de cision making in education: Evidence from recent RAND research (OP-170). Santa Monica, CA: RAND Corporation.
45. Means, B., Padilla, C., DeBarger, A., & Bakia, M. (2009). Implementing data-informed decision making in schools: Teacher access, supports and use. Report prepared for U.S. Department of Education, Office of Planning, Evaluation and Policy Development. Prepared by SRI International, Menlo Park, CA.
46. Means, B., Padilla, C., & Gallagher, L. (2010). Use of education data at the local level from accountability to instructional improvement. Report prepared for U.S. Department of Education, Office of Planning, Evaluation and Policy Development. Prepared by SRI International, Menlo Park, CA.
47. National Center for Education Statistics. (n.d.). 20 states win grants for longitudinal data systems. Retrieved from http://nces.ed.gov/programs/slds/fy09arra_announcement.asp
48. Nichols, B. W., & Singer, K. P. (2000). Developing data mentors. Educational Leadership, 57(5), 34-37.
49. Petrides, L., & Nodine, T. (2005). Anatomy of school system improvement: Performance-driven practices in urban school districts. San Francisco, CA: Institute for the Study of Knowledge Management in Education and New Schools Venture Fund.
50. Roderick, M. (2012). Drowning in data but thirsty for analysis: Commentary on "Interventions to Promote Data Use." Teachers College Record, 114(11).
51. Simmons, W. (2012). Data as a lever for improving instruction and student achievement. Teachers College Record, 114(11).
52. Smylie, M. A., & Corcoran, T. B. (2009). Nonprofit organizations and the promotion of evidence- based practice in education. In J. D. Bransford, D. J. Stipek, N. J. Vye, L. M. Gomez, & D. Lam (Eds.), The role of research in educational improvement (pp. 111-136). Cambridge, MA: Harvard Education Press.
53. Snipes, J., Doolittle, F., & Herlihy, C. (2002). Foundations for success: Case studies of how urban school systems improve student achievement. Washington, DC: Council of Great City Schools.
54. Stecher, B., Hamilton, L., & Gonzalez, G. (2003). Working smarter to leave no child behind: Practical insights for school leaders. Santa Monica, CA: RAND Education.
55. Supovitz, J. A. (2006). The case for district-based reform: Leading, building, and sustaining school improvement. Cambridge, MA: Harvard Education Press.
56. Supovitz, J. A. (2012). Getting at student understanding-The key to teachers' use of test data. Teachers College Record, 114(11).
57. Supovitz, J., & Klein, V. (2003). Mapping a course for improved student learning: How innovative schools use student performance data to guide improvement. Philadelphia, PA: Consortium for Policy Research in Education.
58. Symonds, K. W. (2004). After the test: Closing the achievement gaps with data. Naperville, IL: Learning Points Associates, and Bay Area School Reform Collaborative.
59. Timperley, H. (2008). Evidence-informed conversations making a difference to student achievement. In L. M. Earl & H. Timperley (Eds.), Professional learning conversations: Challenges in using evidence for improvement. (pp. 69-80). Dordrecht, The Netherlands: Springer.
60. U.S. Department of Education. (2009). Race to the Top program: Executive summary. Retrieved from: http://www2.ed.gov/programs/racetothetop/executive-summary.pdf
61. Wayman, J. C., Conoly, K., Gasko, J., Stringfield, S. (2008). Supporting equity inquiry with student data computer systems. In E. B. Mandinach & M. Honey (Eds.), Linking data and learning (pp. 171-190). New York, NY: Teachers College Press.
62. Wayman, J. C., & Stringfield, S. (2006). Technology-supported involvement of entire faculties in examination of student stat for instructional improvement. American Journal of Education 112(4), 549-571.
63. Wayman, J. C., Stringfield, S., & Yakimowski, M. (2004). Software enabling school improvement through analysis of student data. Baltimore, MD: Center for Research on the Education of Students Placed at Risk, Johns Hopkins University.
64. Weinbaum, E. (2009). Learning about Assessment. An evaluation of a ten-state effort to build assessment capacity in high schools. Philadelphia, PA: Consortium for Policy Research in Education.
65. Weiss, J. A. (2012). Data for improvement, data for accountability. Teachers College Record, 114(11).
66. Young, V. M., & Kim, D. H. (2010). Using assessments for instructional improvement: A literature review. Education Policy Analysis Archives, 18(19), 1-36.