Most of the low-performing schools and students are in urban districts where poverty is high, where large proportions of students have limited English proficiency, and where students perform poorly on achievement tests. Moreover, urban districts face numerous challenges, including attracting teachers to their schools and optimizing their hiring, transfer, and retention policies so that they bring the best available teachers to the classroom setting. What’s now needed is an understanding of how schools differ on the qualifications of their teachers and the mechanisms driving these differences. In this article, the authors use the Detroit metropolitan region as a case study in order to (a) determine whether there is teacher sorting across schools and districts, and (2) identify which schools and districts have the least qualified teachers.
AaronsonD.BarrowL.SandersW. (2003). Teachers and student achievement in the Chicago public high schools (Working Paper Series No. WP 02-28). Chicago: Federal Reserve Bank of Chicago.
AllenM. (2003). Eight questions on teacher preparation: What does the research say?Denver, CO: Education Commission of the States.
4.
BettsJ. R.RuebenK. S.DanenbergA. (2000). Equal resources, equal outcomes?The distribution of school resources and student achievement in California. Retrieved from http://www.ppic.org/content/pubs/R_200JBR.pdf.
5.
BoydD.GoldhaberD.LankfordH.WycoffJ. (2007). The effect of certification and preparation on teacher quality. Excellence in the Classroom, 17, 45-69.
6.
Darling-HammondL. (2000). Teacher quality and student achievement: A review of state policy evidence. Education Policy Analysis Archives, 8(1). Retrieved from http://epaa.asu.edu/epaa/v8n1/.
EhrenbergR. G.BrewerD. J. (1994). “Do school and teacher characteristics matter? Evidence from high school and Beyond.”Economics of Education Review, 13, 1-17.
9.
FenstermacherG.RichardsonV. (2005). On making determinations of quality teaching. Teachers College Record, 107(1), 186-213.
10.
FergusonR. F. (1991). Paying for public education: New evidence on how and why money matters. Harvard Journal on Legislation, 28, 465-498.
11.
FergusonR. (1998). Teachers’ perceptions and expectations and the Black-White test score gap. In JencksC.PhillipsM. (Eds.), The Black-White test score gap (pp. 273-317). Washington, DC: Brookings Institution Press.
12.
FergusonR. F.LaddH. F. (1996). How and why money matters: An analysis of Alabama schools. In LaddH. F. (Ed.), Holding schools accountable: Performance-based reform in education (pp. 265-298). Washington, DC: Brookings Institution Press.
13.
FetlerM. (1999). High school staff characteristics and mathematics test results. Education Policy Analysis Archives, 7(9), 1-19.
14.
FreedmanP. (2002). Memo to Wendy Kopp, President, Teach for America, re: Laczko, Kerr Berliner study.
15.
GoeL. (2007). The link between teacher quality and student outcomes: A research synthesis. Washington, DC.: National Comprehensive Center for Teacher Quality.
16.
GoldhaberD.2002. The Mystery of Good Teaching: Surveying the Evidence on Student Achievement and Teachers’ Characteristics. Education Next, 2(1), 50 -55.
17.
GoldhaberD. (2006). National Board teachers are more effective, but are they in the classrooms where they’re needed most?Education Finance and Policy, 1, 372-382.
18.
GoldhaberD. (2007). Can teacher quality be effectively assessed? National Board certification as a signal of effective teaching. Review of Economics and Statistics, 89, 134-151.
19.
GoldhaberD.BrewerD. J. (2000). Does teacher certification matter? High school certification status and student achievement. Educational Evaluation and Policy Analysis, 22, 129-145.
20.
GoldhaberD.BrewerD. J.AndersonD. (1999). A three-way error components analysis of educational productivity. Education Economics, 7, 199-208.
21.
HanushekE. A. (1986). The economics of schooling: Production and efficiency in public schools. Journal of Economic Literature, 24, 1141-1177.
22.
HanushekE. A. (1992). The trade-off between child quantity and quality. Journal of Political Economy, 100, 84.
23.
HanushekE. A. (1997). Assessing the effects of school resources on student performance: An update. Educational Evaluation and Policy Analysis, 19, 141-64.
24.
HillH. C. (2007). Mathematical knowledge of middle school teachers: Implications for the No Child Left Behind policy initiative. Educational Evaluation and Policy Analysis, 29, 95-114.
25.
HillH. C.LubienskiS. T. (2007). Teachers’ mathematics knowledge for teaching and school context: A study of California teachers. Educational Policy, 21, 747-768.
26.
ImaiK. (2002). Comments on Laczko-Kerr, I. and Berliner, D. C. The effectiveness of Teach for America and other under-certified teachers on student academic achievement: A case of harmful public policy. Cambridge, MA: Harvard University, Department of Government.
27.
JacobB. A. (2007). The challenges of staffing urban schools with effective teachers. Excellence in the Classroom, 17, 129-155.
28.
KellerB. (2005). Actual measures of “highly qualified teachers” just beginning to come to light across nation. Education Week, 25(15), 6 and 8-9.
29.
KoskiW. S.HorngE. L. (2007). Curbing or facilitating inequality? Law, collective bargaining, and teacher assignment among schools in California. Retrieved from http://www.ppic.org/
30.
Laczko-KerrI.BerlinerD. C. (2002). The effectiveness of “Teach for America” and other under-certified teachers on students academic achievement: A case of harmful public policy. Education Policy Analysis Archives, 10(37). Retrieved from http://olam.ed.asu.edu/epaa.
31.
LaddH. F. (2007). Teacher labor markets in developed countries. Excellence in the Classroom, 17, 201-219.
32.
LankfordH.LoebS.WyckoffJ. (2002). Teacher sorting and the plight of urban schools: A descriptive analysis. Education Evaluation and Policy Analysis, 24, 37-62.
33.
LoebS.ReiningerM. (2004). Public policy and teacher labor markets: What we know and why it matters. East Lansing: Education Policy Center at Michigan State University.
34.
MonkD. H. (1994). Subject area preparation of secondary mathematics and science teachers and student achievement. Economics of Education Review, 13, 125-145.
35.
MurnaneR. J.PhillipsB. R. (1981). Learning by doing, vintage and selection: Three pieces of the puzzle relating teaching experience and teaching performance, Economics of Education Review, 1, 453-465.
36.
NoellG. H. (2006). Value added assessment of teacher preparation (Annual Report). Baton Rouge: Louisiana State University.
37.
NyeB.KonstantopoulosS.HedgesL. V. (2004). How large are teacher effects?Educational Evaluation and Policy Analysis, 26, 237-257.
38.
PhelpsJ. L.AddonizioM. F. (2006). How much do schools and districts matter? A production function approach to school accountability. Educational Considerations, 33(2), 51-62.
39.
RivkinS. G.HanushekE. A.KainJ. F. (2005). Teachers, schools, and academic achievement. Econometrica, 73, 417-458.
40.
RockoffJ. E. (2004). The impact of individual teachers on students’ achievement: Evidence from panel data. American Economic Review, 94, 247-252.
41.
SackJ. L. (2005). Point system available to earn “qualified” status. Education Week, 25(10), 16.
42.
SandersW.HornP. (1994). The Tennessee Value-Added Assessment System (TVAAS): Mixed methodology in educational assessment. Journal of Personnel Evaluation in Education, 8(1), 299-311.
43.
StraussR. P.SawyerE. A. (1986). Some new evidence on teacher and student competencies. Economics of Education Review, 5, 41-48.
44.
StrutchensM.LubienskiS. T.McGrawR.WestbrookS. K. (2004). NAEP findings regarding race/ethnicity: Students’ performance, school experiences, attitudes/beliefs and family influences. In KloostermanP.LesterF. K.Jr. (Eds.), Results and interpretations of the 1990 through 2000 mathematics assessments of the National Assessment of Educational Progress (pp. 269-304). Reston, VA: NCTM.
45.
ThumY. M. (2003). Measuring progress toward a goal estimating teacher productivity using a multivariate multilevel model for value-added analysis. Sociological Methods & Research, 32, 153-207.
46.
WayneA. J.YoungsP. (2003). Teacher characteristics and student achievement gains: A review. Review of Educational Research, 73(1), 89-122.
