The effect of absence from elementary school on student performance as measured by standardized achievement tests
The purpose of the study was to determine what relationship, if any, existed between student absence from school and student performance on standardized achievement tests. The study was designed to provide statistical data for educators and others interested in efforts to improve public education.Subjects of the study were students from a large school district in northern Indiana. Students included in the study were selected from those enrolled in the identified school corporation four consecutive years, from 1983-84 (grade 2) through 1986-87 (grade 5). A one-third representative sample of 500 subjects was selected from the total eligible population of 1,505 studentsData collected regarding the subjects of the study included sex, race, IQ scores, percentile ranks from subtest scores on the Iowa Test of Basic Skills and the California Achievement Test for grades 2 and 3 and grades 4 and 5 respectively, and the total number of days absent from school for the school years 1983-84 through 1986-87.Achievement subtest scores were converted from percentile ranks to normalized standard deviation zscores. Absence rates were also converted to z-scores for statistical comparison.The hypothesis stated in null form was: No relationship exists between student absence from school and student performance on standardized achievement tests at the elementary school level. Path analysis, or causal analysis, a special application of regression analysis, was the technique used to test the hypothesis. Achievement test performance was predicted from a weighted combination of independent variables and control variables. Predicted achievement test performance was compared to observed achievement test performance to determine whether absence could account for any variation between the two scores.Small but significant relationships were identified in simple correlations pertaining to the data for grade 5. The significant correlations were not maintained, however, when all control variables were computed into the regression analysis equation. The null hypothesis was not rejected.