Parallel Session Proceedings »
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3.2.13 Identifying Diverse Gifted Students in Large U.S. Urban Districts
This presentation will focus on multiple models for identifying gifted and talented learners and the data indicating the effectiveness of each in equitably identifying historically underrepresented populations in urban public school districts including universal screening, the use of local norms, and reliance on teacher referrals (Ford, 2015; Gallagher & Gallagher, 2013; Zhbanova, Rule, & Stichter, 2013). Data will also be presented from Baltimore City schools comparing the impact of universal screening at second grade versus kindergarten, as well as pilot data from two initiatives to increase identification: nonverbal analogies lessons prior to testing and using a spatial battery as an alternative identification measure. Data from each utilize a quasi-experimental design with control groups to provide implications for potential correlations of the identification impacts from each pilot.
Further, the presenters will highlight services that work in Baltimore City including Individualized Learning Plans for all gifted and advanced learners that take a strengths-based approach to goal design, with at least one of each student’s goals focusing on an interest-based, rigorous problem or project based learning opportunity, the use of gifted-level supplemental curricula (Jacob’s Ladder, Mentoring Mathematical Minds, William and Mary Math and Science Units), and long term projects such as National History Day and the Morgan State Science Fair.
Finally, presenters will discuss how their approach in Baltimore City Public Schools has begun to change the narrative around gifted in a place where many people thought they did not exist. This approach includes comprehensive professional development, a grassroots school-based site recruitment process, leveraging community partnerships (University of Maryland School of Medicine and the Johns Hopkins Center for Talented Youth), and the completion of the state award portfolio process.