High-potential students from underresourced rural schools face barriers that reduce options for academic advancement, which widens the excellence gap between them and their more affluent, but similar ability peers. The goal of this study was to investigate the effectiveness of an expanded above-level testing model to identify high-potential rural students for an extracurricular math and science enrichment program. Results from our analyses indicated that a more inclusive talent pool differentiated among high achievers to find greater percentages (13%) of talented students compared with most gifted programs (3% to 5%) or Talent Search programs (5%). Overall, students’ math and science scores were related to a 75% and 50%, respectively, greater odds in being identified for the extracurricular program. Regardless of program participation, all talent pool students increased their math and science achievement; however, there were some significant gender differences.

High-achieving students in economically disadvantaged, rural schools lack access to advanced coursework necessary to pursue science, technology, engineering, and mathematics (STEM) educational and employment goals at the highest levels, contributing to the excellence gap. Out-of-school STEM programming offers one pathway to students' talent development. Using a concurrent triangulation mixedmethods research design, this study was conducted to evaluate the experiences of 78 high-achieving students and their 32 teachers, participating in an extracurricular, school-based, STEM talent development program for rural students from economically disadvantaged communities. Findings suggest that students and teachers expressed satisfaction with program participation and that they thought more creatively and critically about their work. Results also showed that students' perceptions of the mathematics and science activities were significantly different, which informs ways to improve programming for future high-achieving, rural students. These findings expand the literature supporting the use of informal STEM education environments for underserved gifted populations to increase engagement in and access to challenging curricula.

Notes. *Pseudonyms were used to ensure participants' anonymity. ^Data from the National Center for Education Statistics. + Free/Reduced. # The number of different types classes the teacher was responsible for (e.g., Biology, Physics, and Chemistry). Data Collection Baxter and Jack (2008) contend that a primary feature of case study research is employing multiple data sources. Baxter and Jack (2008), Snyder (2012), and Yin (1981) assert that data from multiple sources need to be integrated in data analysis and not analyzed in isolation. Each data source is one piece of a puzzle, and each piece contributes to the researcher's

No abstract