This study explores machine learning (ML) approaches for identifying gifted students by integrating academic and socioemotional characteristics from the data collected with the Having Opportunities Promotes Excellence teacher rating scale. By using the Gaussian Mixture Model (GMM) and ML approaches, including support vector machine (SVM) and…

It is very important to identify talented students as soon as they are admitted to college so that appropriate resources are provided and allocated to them to optimize and excel in their education. Currently, this process is labor-intensive and time-consuming, as it involves manual reviews of each student's academic record. This raises the…

Researchers in gifted and talented education (GATE) have increasingly taken on the role of advocating equity and access for minoritized populations. However, subgroups of racially and ethnically diverse students are rarely disaggregated from monolithic racial and ethnic categories. Studies on academic achievement of Asian American and White…

Over the past decade, the National Center for Research on Gifted Education (NCRGE), funded by the Jacob K. Javits Gifted and Talented Students Education Program, has conducted large-scale, multi-method studies to improve equity in the identification of and instructional support for gifted students. NCRGE has identified barriers and promising…

Over the past decade, the National Center for Research on Gifted Education (NCRGE), funded by the Jacob K. Javits Gifted and Talented Students Education Program, has conducted large-scale, multi-method studies to improve equity in the identification of and instructional support for gifted students. NCRGE has identified barriers and promising…

English learners (ELs) are the fastest growing population of students in the United States and currently represent nearly 10% of public school enrollment; however, they also constitute less than 3% of gifted program enrollment in these schools. Although an increasing number of studies explore this underrepresentation, research that specifically…

English learners (ELs) are the fastest-growing population of students in the United States and currently represent nearly 10% of public school enrollment; however, they also constitute less than 3% of gifted program enrollment in these schools. Although an increasing number of studies explore this underrepresentation, research that specifically…

This study investigated the application of item response theory (IRT) to expand the range of ability estimates for gifted (hereinafter referred to as high-achieving) students' performance on an above-level test. Using a sample of fourth- to sixth-grade high-achieving students (N = 1,893), we conducted a study to compare estimates from two…