The Effects of School Location on Math and Science Achievement Trends: A Primer on Growth Modeling in Education Policy Research

The effect of school location on math and science learning is currently an important policy issue in the United States and in other countries, such as Australia. The present paper uses a 5-year series of math and science achievement data from the state of Kentucky to determine the effects of school location on learning in these subject areas. Adopting an organizational assessment approach, I show how growth models may be used to estimate achievement trends. I also demonstrate methods for discovering two important sources of invalidity in growth models: regression artifacts and spuriousness. Failure to account for these sources of invalidity may lead to erroneous policy conclusions. Two examples of growth models are provided—a linear model and a nonlinear model. The results of these analyses do not support the common contention that there is a rural achievement gap in math and science. One implication of these findings is that, if policymakers wish to enhance math learning, they will accomplish this more effectively by interventions and programs that increase the motivation and opportunity to learn among low-income students, regardless of school location. Because current U.S. education policy is focused on documenting “adequate yearly progress” in schools, growth modeling is likely to become the preferred methodology of policy researchers

Do Contextual Effects Bias Kentucky School District Accountability Index Scores?

Kentucky’s system of high-stakes accountability raises the question: Should teachers and school administrators be held accountable for student test results if the scores are influenced by external factors over which these educators have no control? The goal of the present study is to investigate if such external factors, or “contextual effects,” bias the accountability index scores. The issue is important because school districts, schools, and educators should be assessed in a fair manner. The focus of the study is on the Kentucky school district accountability index scores for the 1992-94 and 1994-96 biennia. District scores, rather than school scores, were chosen as the focus because more suitable measures of contextual effects are available for school districts than for schools. Three contextual effects are considered: (1) median household income in the district, (2) teen birth rate, and (3) rural-metropolitan differences among districts

Parent Resources and High School Quality in the Context of the Rural Gap in Postsecondary Educational Attainment

The goal of the present study is to explain the effects of parent resources and secondary school quality in bringing about these patterns in the context of the rural gap in higher educational attainment. Using a nationally representative data set that tracks individual student careers in high school and beyond (which NELS provides) lays a strong empirical foundation for the investigation of this topic

Expenditures Streams and School Improvement in Kentucky: Does Money Matter?

Every Kentucky public school is expected to achieve the goal of proficiency on the State\u27s Accountability Index by the year 2014. Many schools may not reach the proficiency goal in time without a broad, multifaceted approach to enhance educational outcomes. A strategy to optimize the allocation of school district funds may contribute to this goal. Previous studies have attempted to answer the question does money matter? for raising school performance, but to date the findings have proven inconsistent. One reason for this might be that most of these studies have used a global measure of monetary resources, such as total per pupil expenditure. The present study explores the possibility that expenditures earmarked for different purposes - termed \u27expenditure streams\u27 - may reveal that financial allocations can make a difference

Edward B. Reeves Papers

MS005-201

A Demonstration of ‘Regression Toward the Mean’

This paper provides a brief discussion and demonstration of regression toward the mean, a subtle statistical artifact that appears in the effort to measure change. Regression toward the mean frequently arises in educational assessment when repeated testing is used to determine achievement growth among students or schools at the extremes of the achievement distribution. This statistical artifact is important because it can lead to erroneous inferences about what is causing the observed changes in test scores. The demonstration makes use of Kentucky Core Content Test data

The Effects of School Location on Math and Science Achievement Trends: A Primer on Growth Modeling in Education Policy Research

The effect of school location on math and science learning is currently an important policy issue in the United States and in other countries, such as Australia. The present paper uses a 5-year series of math and science achievement data from the state of Kentucky to determine the effects of school location on learning in these subject areas. Adopting an organizational assessment approach, I show how growth models may be used to estimate achievement trends. I also demonstrate methods for discovering two important sources of invalidity in growth models: regression artifacts and spuriousness. Failure to account for these sources of invalidity may lead to erroneous policy conclusions. Two examples of growth models are provided—a linear model and a nonlinear model. The results of these analyses do not support the common contention that there is a rural achievement gap in math and science. One implication of these findings is that, if policymakers wish to enhance math learning, they will accomplish this more effectively by interventions and programs that increase the motivation and opportunity to learn among low-income students, regardless of school location. Because current U.S. education policy is focused on documenting “adequate yearly progress” in schools, growth modeling is likely to become the preferred methodology of policy researchers

A Test of Three Sociological Explanations of High School Completion

Data from the National Education Longitudinal Study of 1988-1994 are analyzed with logistic regression to test three sociological explanations of high school completion. The first explanation, derived from meritocracy theory, holds that educational credentials are won by academically deserving students. Thus, students who demonstrate better cognitive skills and make better grades are more likely to receive a high school diploma. The second explanation, derived from social reproduction theory, hypothesizes that high school graduation depends on the resources within the student’s family, such as family income and parent’s education level. Students from more advantaged families are more likely to graduate. The third explanation, taken from social bond theory, proposes that social attachments, commitments, and time involvement related to school activities bind the student to normative expectations of the school and increase the probability of graduation. Social attachments that alienate the students from school have the opposite effect. The results of the analyses find unequivocal support for the social reproduction and social bond explanations. Meritocracy theory garners no support. Practical implications of the findings are discussed

Regional Disparities in Kentucky Academic Index Scores

Recent newspaper articles by columnist Bill Bishop in the Lexington Herald-Leader point to persistent regional disparities in achievement in Kentucky public schools. In spite of a mandate to create educational equality, the Kentucky Education Reform Act (KERA) has not eliminated inequalities in school performance scores and the problem may even be getting worse according to Mr. Bishop. The objective of the present study is to determine what disparities exist among Kentucky’s eight Service Center Regions. The analysis uses school Academic Index scores, from 1992-93 to 1996-97, averaged by region. The regional averages (or means) are compared descriptively along with the statistical application of pairwise multiple comparisons. The study’s findings show that regional disparities in Academic Index scores clearly exist. These disparities are probably owing, at least in part, to contextual effects such as ruralmetropolitan differences and socioeconomic influences. A goal of KERA should be to narrow the gap between the schools in different regions. To assess the accomplishment of this goal, it will be useful to regularly monitor disparities in the gains that regions achieve in their scores over time. The present analysis concludes that after five years, schools in the eight Service Regions have generally kept pace with one another. Thus, although greater equality is still an unrealized ideal under KERA, improvement has taken place with little evidence thus far of a “widening gap” between the higher- and lower-scoring regions. Another five years of data should tell if a widening gap between the regions has become a persistent problem

A Spacial Analysis of Contextual Effects on Education Accountability in Kentucky

The Kentucky Education Reform Act of 1990 mandated changes in the methods of funding education in Kentucky. The newly adopted methods of funding primary and secondary schools have brought questions of accountability to the forefront in Kentucky\u27s tests of achievement, called KIRIS tests. These methods, however, ignore the geographical context for teachers, schools, and school districts. At this time, the accountability movement has given little attention to how much socioeconomic context influences educational outcomes. Furthermore, there is almost no recognition in the research literature that socioeconomic factors are spatially distributed and thus can be subjected to geographic analysis. The purpose of this investigation is to show how such an analysis might be done using Kentucky accountability results. This study analyzes spatial patterns of recent KIRIS scores using regression methods. An examination has been made of the residuals from the regression analysis for spatial autocorrelation using Moran\u27s I. Results indicate that including contextual effects as explanatory variables reduces the spatial autocorrelation and provides a more reliable measure of school and school district performance