Concordance of Gifted Education Policy and Practices at the State, District, and Local Levels

Abstract

Gifted education policies vary across the United States. Previous studies have demonstrated a disconnect between these policies at state and district levels, but alignment of school-level practices with state and/or district policies is unknown. To further examine these relationships, we examined via qualitative document analysis state and district-level gifted policies and district and school-level reported practices in two states’ gifted services. Although state and district policies reflected fairly close alignment with recommended practices, district and school reported practices reflected only partial alignment. We discuss implications of these findings for gifted programs and policy at the state and local levels.

Effect of Demographic Variables on the Accuracy of Teacher

“…32.2024.454 are greater than the average score such traits in teaching the literary subjects. As presented in table (12), there are statistically significant differences, which mean that there is an effect of the number of years of experience among teachers on their aacuracy of their nomination of gifted students in which the observed level of significance (Sig) is less than the theoretical level of significance of 0.05 for all behavioral traits scores among gifted students, as well as the total score. The results indicates that teachers with experience arranged from 5 years to less than 10 years have higher average traits scores than those with less experience (less than 5 years), and also higher than those with more than 10 years of experience.…”

A Pragmatic Analysis of How North Carolina School Districts Aim to Differentiate for Gifted High School Students

“…Coding district plans as we did could be replicated and expanded to explore correlations or differences between the number of codes represented in a district plan with a variety of variables such as student demographics, percentage of students identified as gifted, type of district (e.g., rural, city, town, suburb), or accountability data (e.g., testing data; Hodges, 2020). Future studies could focus on the connection between financial data, available resources, and implementation of the AIG Plans (Brodersen et al, 2022; Hodges, 2020). We also recommend that other researchers consider investigating other NC regions’ AIG Plans to identify additional promising or unique practices and their effects on gifted high school students.…”