Who is Missing and Who is Found? Comparing Multiple Measures, Universal Consideration, and Differing Norms for Gifted Identification

Underrepresentation of diverse learners in gifted education may be partly due to methods used in identification procedures. Problems with current practices include a reliance on teacher referral before identification measures are administered, using national norms, and using “and” rather than “or” rules for multiple measures. This descriptive study of 2017-2019 data from multiple achievement tests examines how using achievement tests with differing norms results in a different talent pool compared to current multiple-criteria identification methods. Results indicate that as norms become more local, the demographics of high-achieving students more closely match the statewide demographics. Although there is a large area of overlap, using the current multiple-criteria method and using computer-adaptive achievement tests for universal consideration results in each method finding students not identified using the other approach. The results suggest the need for a more robust approach to identification and the need to align carefully identification and services.