Kansas metropolitan location and high school size as variables in low income low achievement correlations

Abstract

Educators have realized that low-income students have a higher probability of lower achievement than students from a higher SES background and that these low-income students may very well continue into the cycle of poverty. The purpose of this study was to refine our understanding of the relationships between low-income student status and low income academic achievement in Kansas high schools. This study explored high school low income, low reading, low mathematics, low science achievement correlations among three metropolitan locations and four sizes of high schools. The dependent variables were the school building rates of low income and the school building rates of low achievement. The independent variables were school location and school size. The data was retrieved from the Kansas State Board of Education website. The three metropolitan areas studied were the Wichita, the Topeka-Lawrence and the Greater Kansas City Metropolitan Areas. The four sizes of high schools studied were the 6A-, 5A-, 4A-, and 3A-sized high schools. There were seven research questions in this study. All the research questions were non-directional except for research question #2. Correlation coefficients, standard deviation scores, range scores, frequency scores, intercorrelations, coefficient of determinations, partial correlations and ANCOVA scores were used to analyze the data. The major conclusions for each research questions were: (1) the unsatisfactory + basic scores of all three low achievement areas (reading, mathematics and science) were the most consistent representation of low achievement. (2) in the three metropolitan areas, where income differences were greater, low income and low achievement correlations were greater. Where income differences were smaller, low income and low achievement correlations were smaller. (3) smaller schools did not have the better school results. (4) the low reading, mathematics and science correlations had different magnitudes depending on the group. Either low mathematics or low science achievement produced the largest correlations with low income in all seven groups. (5) the smaller standard deviation and range scores may have contributed to the smaller correlations in metropolitan area 2 and the 4A-sized high schools. Findings in the frequency distributions have reinforced the standard deviation and range results. (6) low mathematics and low science achievement were as important as low reading achievement. (7) the lowachievement rates (adjusted for low-income rates) did not differ much across the subject areas when the seven subgroups were considered. The idea of building smaller schools was not supported by the findings.