The principal role in data-driven decision making: Using case-study data to develop multi-mediator models of educational reform

School Effectiveness and School Improvement

Volumn 23, Issue 2, 2012, Pages 179-201

  Levin, James A ^a   Datnow, Amanda ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

data use; educational reform; principal leadership

Indexed keywords

EID: 84859599443     PISSN: 09243453     EISSN: 17445124     Source Type: Journal    
DOI: 10.1080/09243453.2011.599394     Document Type: Article

References (36)

1. Abrahamson, D. and Wilensky, U. Piaget? Vygotsky? I'm game: Agent-based modeling for psychology research. Paper presented at the annual meeting of the Jean Piaget Society. June. Vancouver: Canada.
2. Abrahamson, D., Wilensky, U. and Levin, J. Agent-based modeling as a bridge between cognitive and social perspectives on learning. Paper presented at the Annual Meeting of the American Educational Research Association. April. Chicago: IL.
3. Berman, P. and McLaughlin, M. W. 1978. Federal programs supporting educational change, Vol. VIII: Implementing and sustaining motivation, Santa Monica, CA: RAND Corporation.
4. Blikstein, P., Abrahamson, D. and Wilensky, U. The classroom as a complex adaptive system: An agent-based framework to investigate students' emergent collective behaviors. Proceedings of the International Conference for the Learning Sciences, ICLS2008. Edited by: Kanselaar, G., van Merriënboer, J., Kirschner, P. and de Jong, T. pp.312-313. Utrecht, The Netherlands: ISLS.
5. Butler, L. 2009. Charter schools, data use, and the 21st century (Unpublished doctoral dissertation), University of Southern California: Los Angeles, CA.
6. Coburn, C. E. 2001. Collective sense-making about reading: How teachers mediate reading policy in their professional communities. Educational Evaluation and Policy Analysis, 23: 145-170.
7. Coburn, C. E. 2006. Framing the problem of reading instruction: Using frame analysis to uncover the micro-processes of policy implementation. American Educational Research Journal, 43: 343-379.
8. Creemers, B. P.M. and Kyriakides, L. 2008. The dynamics of educational effectiveness, London, UK: Routledge.
9. Datnow, A., Hubbard, L. and Mehan, H. 2002. Extending educational reform: From one school to many, London, UK: Routledge Falmer Press.
10. Datnow, A. and Park, V. 2009. "Conceptualizing policy implementation: Large-scale reform in an era of complexity". In Handbook of education policy research, Edited by: Sykes, G., Schneider, B. and Plank, D. 348-361. New York, NY: Routledge.
11. Datnow, A., Park, V. and Kennedy, B. 2008. Acting on data: How urban high schools use data to inform instruction, Los Angeles, CA: Center on Educational Governance, USC Rossier School of Education. Retrieved from http://www.newschools.org/files/ActingonData.pdf
12. Datnow, A., Park, V. and Wohlstetter, P. 2007. Achieving with data: How high performing districts use data to improve instruction for elementary school students, Los Angeles, CA: Center on Educational Governance, USC Rossier School of Education. Retrieved from http://www.newschools.org/files/AchievingWithData.pdf
13. Earl, L. and Katz, S. 2006. Leading schools in a data rich world, Thousand Oaks, CA: Corwin Press.
14. Ehren, M. C.M. and Visscher, A. J. 2008. The relationships between school inspections, school characteristics and school improvement. British Journal of Educational Studies, 56: 205-227.
15. Firestone, W. A., Fitz, J. and Broadfoot, P. 1999. Power, learning, and legitimation: Assessment implementation across levels in the United States and the United Kingdom. American Educational Research Journal, 36: 759-793.
16. Hamilton, L., Halverson, R., Jackson, S., Mandinach, E., Supovitz, J. and 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. Retrieved from http://ies.ed.gov/ncee/wwc/pdf/practiceguides/dddm_pg_092909.pdf
17. Hubbard, L., Mehan, H. and Stein, M. K. 2006. Reform as learning: School reform, organizational culture, and community politics in San Diego, New York, NY: Routledge Falmer Press.
18. Ikemoto, G. S. and Marsh, J. A. 2007. "Cutting through the "data driven" mantra: Different conceptions of data-driven decision making". In Evidence and decision making: 106th yearbook of the National Society for the Study of Education, Edited by: Moss, P. A. 105-131. Malden, MA: Blackwell.
19. Kerr, K. A., Marsh, J. A., Ikemoto, G. S., Darilek, H. and Barney, H. 2006. Strategies to promote data use for instructional improvement: Actions, outcomes, and lessons from three urban school districts. American Journal of Education, 112: 496-520.
20. Mandinach E. B. Honey M. 2008 Data driven school improvement: Linking data and learning. New York, NY Teachers College Press
21. Markarian, B. 2009. Holding on and holding out: Why some teachers resist the move toward data driven decision making (Unpublished doctoral dissertation), University of Southern California: Los Angeles, CA.
22. McLaughlin, M. W. 1987. Learning from experience: Lessons from policy implementation. Educational Evaluation and Policy Analysis, 9: 171-178.
23. Mehan, H. 1992. Understanding inequality in schools: The contribution of interpretive studies. Sociology of Education, 65: 1-20.
24. Schildkamp, K. and Teddlie, C. 2008. School performance feedback systems in the USA and in The Netherlands: A comparison. Educational Research and Evaluation, 14: 255-282.
25. Spillane, J. P., Reiser, B. J. and Reimer, T. 2002. Policy implementation and cognition: Reframing and refocusing implementation research. Review of Educational Research, 72: 387-431.
26. Supovitz, J. and Klein, V. 2003. Mapping a course for improved student learning: How innovative schools systematically use student performance data to guide improvement, Philadelphia, PA: Consortium for Policy Research in Education.
27. Supovitz, J. and Taylor, B. S. 2003. The impact of standards-based reform in Duval County, Florida, 1999-2002., Philadelphia, PA: Consortium for Policy Research in Education.
28. Togneri, W. and Anderson, S. 2003. Beyond islands of excellence: What districts can do to improve instruction and achievement in all schools., Washington, DC: Learning First Alliance.
29. Tyack, D. and Cuban, L. 1995. Tinkering toward Utopia: A century of public school reform, Cambridge, MA: Harvard University Press.
30. Ward-Roberts, V. 2009. Does data driven decision making matter for African American students? (Unpublished doctoral dissertation), University of Southern California: Los Angeles, CA.
31. Wayman, J. C. 2005. Involving teachers in data-driven decision making: Using computer data systems to support teacher inquiry and reflection. Journal of Education for Students Placed At Risk, 10: 295-308.
32. Wilensky, U. 1999. NetLogo, Evanston, IL: Center for Connected Learning and Computer-Based Modeling, Northwestern University. Retrieved from http://ccl.northwestern.edu/netlogo
33. Wohlstetter, P., Datnow, A. and Park, V. 2008. Creating a system for data-driven decision-making: Applying the principal-agent framework. School Effectiveness and School Improvement, 19: 239-259.
34. Wu, P. 2009. Do we really understand what we are talking about? A study examining the data literacy capacities and needs of school leaders (Unpublished doctoral dissertation), Los Angeles, CA: University of Southern California.
35. Yin, R. 2008. Case study research: Design and methods, Beverly Hills, CA: Sage.
36. Young, V. M. 2006. Teacher's use of data: Loose coupling, agenda setting, and team norms. American Journal of Education, 112: 521-548.