The Interactive Relationship between Selected Demographic and Leadership Characteristics of Public Elementary School Principals and Their Special-Education Responsibilities and Placement Decisions

There is considerable research to suggest that school principals are a significant influence on the amount and quality of services to handicapped children, but there are limited data that identify characteristics associated with their special-education involvement levels and placement decisions. The purpose of this study was to identify and analyze demographic and leadership characteristics of urban elementary-school principals (N = 166) that are associated with their (a) responsibility levels in 27 key special-education functions and (b) placement decisions for children with various kinds and degrees of handicapping conditions. The identification of those characteristics associated with school principals\u27 special-education performance levels could have special significance for their initial screening, training, certification, and consequent employment. Subjects. The subjects were 147 school principals and 19 assistant principals from public elementary schools in the nine Wisconsin cities with SMSA populations greater than 50,000. Subjects\u27 participation was obtained by mailing 313 postcard-enclosed invitations to principals or their designees to participate in a study investigating the current role of principals in the administration of special-education programs. Willing invitees were sent the Leadership Opinion Questionnaire (LOQ), the Rucker-Gable Educational Programming Scale (RGEPS), a special-education responsibility checklist (SERC), and a demographic questionnaire. Nonparticipants included 10.5 refusals and 42 schools that were excluded due to school closings, shared principalships, or incomplete data. Procedure. Six major hypotheses were tested that investigated demographic and IOQ responses with RGEPS and SERC responses, using Pearson correlation coefficients. Additional statistical analysis included: t-tests for difference of means between subpopulations, analysis of variance between subpopulations, Chi-Square tests for statistical independence of respondents and nonrespondents, and interscale correlations