The passage of ESSA in 2015 created a novel mandate for States to develop school accountability systems that use alternative measures of school quality beyond test scores. This created an opportunity for States to be innovative and make new forms of data available that could potentially lead to new strategies for improving schools. This study explored early experiments in alternative accountability measures in two urban districts. Drawing on interviews, documents, and observations gained through participant research, this study highlights the variable types of data the models made available to stakeholders and how those differences suggest different theories of change for improving schools. The findings highlight how different ways of specifying school quality point to different ideas about what schools should be responsible for improving.
BrykA. S., & HermansonK. L. (1993). Educational indicator systems: Observations on their structure, interpretation, and use. Review of Research in Education, 19, 451–484.
2.
ChildressS., HigginsM., IsimaruA., & TakahaskiS. (2010). Managing for results at the New York City department of education. In O'DayJennifer, BitterCatherine, & GomezLouis (Eds.), Education Reform in New York City (87–108). Cambridge, MA: Harvard Education Press.
3.
CoburnC. E. (2005). The role of non-system actors in the relationship between policy and practice: The case of reading instruction in California. Educational Evaluation and Policy Analysis, 27(1), 23–52.
4.
Darling-HammondL., & AscherC. (1991). Creating accountability in big city schools systems.New York, NY: Report for OERI: Teachers College, National Center for Restructuring Education, Schools and Teaching.
5.
Darling-HammondL., & SynderJ. (2015). Accountability for resources and outcomes: An introduction. Education Policy Analysis Archives, 23(20), 1–9.
6.
ElmoreR. F., AbelmannC. H., & FuhrmanS. H. (1996). The new accountability in state education reform: From process to performance. In LaddHelen (Ed.), Holding schools accountable: Performance-based reform in education (65–98). Washington, D.C: The Brookings Institution.
7.
ElmoreR. F. (2004). School reform from the inside out: Policy, practice, and performance.Cambridge, MA: Harvard Education Press.
8.
FinnC. E. (2002). Real accountability in K-12 education: The marriage of Ted and Alice. In Williamson EversM., & WahlbergHerbert J. (Eds.), School Accountability.Stanford, CA: Hoover Institution Press.
9.
FirestoneW. A., & GonzalezR. A. (2007). Chapter 6 culture and processes affecting data use in school districts. Yearbook of the National Society for the Study of Education, 106(1), 132–154.
10.
FullanM., & BoyleA. (2014). Big-city school reforms: Lessons from New York, Toronto & London.New York, NY: Teachers College Press.
11.
GorenP. (2012). Data, data, and more data—what's an educator to do?American Journal of Education, 118(2), The Practice of Data Use (February 2012), 233–237.
12.
HanushekE., & RaymondM. E. (2002). Sorting out accountability systems. In EversWilliamson M., & WalbergHerbert J. (Eds.), School accountability (75–104). Stanford University, CA: Hoover Institution Press.
13.
IkemotoG. S., & MarshJ. A. (2007). Chapter 5 cutting through the “data-driven” mantra: Different conceptions of data-driven decision making. Yearbook of the National Society for the Study of Education, 106(1), 105–131.
14.
JeraldC. D. (2012). On her majesty's school inspection service.Washington D.C: Education Sector Reports.
15.
KaneT. J., & StaigerD. O. (2002). The promise and pitfalls of using imprecise school accountability measures. Journal of Economic Perspectives, 16(4), 91–114.
16.
KleinJ. (2014). Lessons of hope: How to fix our schools.New York, NY: Harper Collins.
17.
LinnR. L. (2000). Assessments and accountability. Educational Researcher, 29(2), 4–16.
18.
LittleJ. W. (2010). Teachers' accounts of classroom experience as a resource for professional learning and instructional decision making. Evidence and Decision Making. In MossPamela (Ed.), The National Society for the Study of Education (217–240). MA: Blackwell Publishing.
19.
LittleJ. W. (2012). Understanding data-use practice among teachers: The contribution of micro process studies. American Journal of Education, 118(2), 143–166.
20.
MarshJ. A., PaneJ. F., & HamiltonL. S. (2006). Making sense of data-driven decision making in education: Evidence from recent RAND research. Occasional Paper 170. Santa Monica, CA: Rand Corporation.
21.
MikuleckyM., & ChristieK. (2014). Rating states, grading schools: What parents and experts say states should consider to make school accountability systems meaningful.Denver, CO: Education Commission of the States, May 2014.
22.
MilesM. B., HubermanA. M., & SaldanaJ. (2014). Qualitative data analysis: A methods sourcebook.Thousand Oaks, CA: Sage Publication.
23.
MurnaneR. J. (1987). Improving education indicators and economic indicators: Same problem?Educational Evaluation and Policy Analysis, 9(2), 101–116.
24.
NewmannF. M., KingM. B., & RigdonM. (1997). Accountability and school performance: Implications from restructuring schools. Harvard Educational Review, 67(1), 41–65.
NYCDOE Quality Review updates meeting June 16, 2010 at 131 Livingston Street, NY.
27.
OakesJ. (1989). What educational indicators? The case for assessing the school context. Educational evaluation and policy analysis, 11(2), 181–199.
28.
O'DayJ. A. (2004). Complexity, accountability, and school improvement. In FuhrmanSusan H., & ElmoreRichard F. (Eds.), Redesigning accountability systems for education (15–45). New York, NY: Teachers College Press.
29.
RichP. M., & JenningsJ. L. (2015). Choice, information, and constrained options: School transfers in a stratified educational system. American Sociological Review, 80(5), 1069–1098.
SpillaneJ. P. (2010). Data in practice: Conceptualizing the data-based decision-making phenomena. In MossPamela (ed.), The National Society for the Study of Education (217–240). MA: Blackwell Publishing, 113–141.
32.
StecherB., HamiltonL., & GonzalezG. (2003). Working smarter to leave no child behind: Practical insights for school leaders. RAND White Paper ISBN: 0-8330-347.
33.
WeissC. H. (1998). Evaluation, 2nd ed.Upper Saddle River, NJ: Prentice Hall.
34.
YinR. K. (1994). Case study research–design and methods. Applied Social Research Method Series, 5, Sage: London.
