AN ANALYSIS OF ALTERNATIVE MODELS FOR FUNDING HANDICAPPED PUPIL TRANSPORTATION.

摘要

The purpose of this study was to determine the most equitable method for distributing funds for the transportation of handicapped children to public schools in the state of Florida. The current Florida pupil transportation formula does not differentiate between regular and special education students.;The current Florida pupil transportation formula and an alternative linear regression model were then tested using three different populations: (a) all students transported, (b) regular students transported, and (c) handicapped students transported. Through Stepwise Regression polynomial variables were added to each of the original models. Density was the independent variable. Cost per pupil transported for each of the three populations became the dependent variable.;The following results were achieved. (1) With all students transported, density is the single best predictor of cost per pupil. (2) The current Florida pupil transportation formula is not the best model to use in predicting cost per pupil transported. (3) Density is a strong predictor of regular student transportation costs but a poor predictor of handicapped student transportation costs.;Results indicate that variation in district costs for special education transportation warrants (1) the study of school transportation management methods; (2) the adoption of state-wide guidelines for promoting efficiency; and (3) an investigation into separate funding for regular and special education transportation.;The present study was undertaken to determine (a) the cost of special education transportation services for districts in Florida and (b) whether the existing formula adequately funded these district costs. A stratified sample of 30 school districts was used as a data base for the study. The following data were gathered from each of the 30 counties for the 1982-83 school year: (1) mileage for regular and handicapped students; (2) total transported membership for both regular and handicapped students; and (3) cost figures for fuel, maintenance, and salaries on all handicapped student buses. From this data, density indices were computed for both regular and handicapped students, as well as cost per pupil transported for the two populations.