For decades, underperformance has been a serious concern in both developing and developed countries. Because students progress from elementary to middle to high schools in an educational system, it is important to pinpoint where in the system underperformance occurs. Without a good understanding of patterns of relationships among schools of different levels, strategies to correct underperformance may not be effective. For example, strategies targeting middle schools may not work well if the root of the problem of inadequate learning is not in middle school but rather in elementary school. This research attempts to initiate a line of studies that seek sound methodology to pinpoint underperformance in educational system. This type of research is critical for educational policymaking to prevent the waste of valuable resources (e.g., funds, labors) resulting from the implementation of unsound recommendations and increase the confidence of schools, districts, and states in adopting sound ones.

Different methodological approaches can be considered for the task of pinpointing underperformance in educational system. Corresponding to data segregation or aggregation, there are analysis and synthesis approaches to examine progression of performance from elementary to middle to high schools. The objective of this research is to test the analysis approach with the educational system of Kentucky, United States as a special case. Specifically, this research uses data from Kentucky’s Commonwealth Accountability Testing System (CATS) (2008) to profile school districts in Kentucky to identify relational patterns of performance among elementary, middle, and high schools within each school district.

The theory of action for this research is based on the input-process-output (IPO) model of school effects (see Teddie & Reynolds, 2000). Early research findings on school effects (Coleman et al., 1966) suggested that variables which could be manipulated, such as per-student expenditures and the nature of the curriculum, had very small effects when compared with the effects of family background. It led to the pessimistic conclusion that schools do not make a difference and provoked four decades of research on school effects based on the IPO model of school effects. Recent advances in statistical modelling, data analysis, and the measurement of schooling outcomes (Ma & Ma, 2005) and the inclusion of a wide range of variables related to classroom practice and school climate (Brand, Felner, Shim, Seitsinger, & Dumas, 2003) have led to a general agreement that schools do provide “added value” to educational outcomes (Opdenakker & Van Damme, 2006).

The premise of the IPO model of school effects is that students bring into their schools different individual and family characteristics as well as different cognitive and affective conditions; schools then channel or process students with differing background into different categories of schooling outcomes such as performance, attitude, and aspiration. In doing so, schools also fall into different categories of schooling outcomes in accordance to characteristics of their schooling processes. Researchers who use this model carefully control the characteristics of student background, examine the distribution of outcomes across schools, and identify salient school contextual and climatic characteristics that process students into different categories of outcomes.

Brand, S., Felner, R., Shim, M., Seitsinger, A., & Dumas, T. (2003). Middle school improvement and reform: Development and validation of a school-level assessment of climate, cultural pluralism, and school safety. Journal of Educational Psychology, 95, 570-588. Coleman, J. S., Campbell, E. Q., Hobson, C. J., McPartland, J., Mood, A. M., Wienfield, F. D., & York, R. L. (1966). Equality of educational opportunity. Washington, DC: US Government Printing Office. Ma, L., & Ma, X. (2005). Estimating correlates of growth between mathematics and science achievement via a multivariate multilevel design with latent variables. Studies in Educational Evaluation, 31, 79-98. Opdenakker, M. C., & Van Dammer, J. (2000). The importance of identifying levels in multilevel analysis: An illustration of ignoring top or intermediate levels in school effectiveness research. School Effectiveness and School Improvement, 11, 103-130. Teddlie, C., & Reynolds, D. (Eds.). (2000). The international handbook of school effectiveness research. London: Falmer.