| Summary |
This study examined relationships between specific data on students referred for and placed in the exceptional children's program. The context is a rural North Carolina county and included 206 records of K - 6th graders spanning academic years 2007-08, 08-09 and 09-10. The kindergarten entrance ages of students were divided into categories of on time, early and late entrants. Redshirted students were also included. Both Pearson Product Moment correlations and a logistic regression model of analysis were employed as these statistical measurements allowed the researcher to examine variables and their relationships that served to predict likelihood of outcomes related to placement. When referring students for testing, statistically significant relationships were determined between a student's race and age at referral (r = .152), a student's race and his/her low socioeconomic status (r = -.226), a student's age at kindergarten entry and the age at which he/she is referred for testing (r = .182) and a student's age at kindergarten entry and number of retentions (r = -.162). When determining placement into the exceptional children's program, statistically significant relationships were determined with gender ([beta] = -.684) and number of in grade retentions ([beta]= .705). Practically significant findings, although not statistically significant, that may prove beneficial for practitioners, included the predictability between a student's race and the likelihood for placement ([beta] = -.351 for black students). Considering kindergarten entrance age, early entrants are predicted to be placed in the exceptional children's program at a much higher rate than other entrants ([beta] = .993). |
| General note | Presented to the faculty of the Department of Educational Leadership. |
| General note | Advisor: James McDowelle. |
| General note | Title from PDF t.p. (viewed Jan. 24, 2013). |
| Dissertation note | Ed.D. East Carolina University 2012. |
| Bibliography note | Includes bibliographical references. |
| Technical details | System requirements: Adobe Reader. |
| Technical details | Mode of access: World Wide Web. |
