Examining Black girls’ mathematics and science dispositions using large-scale assessment and survey data: A QuantCrit framework

Early exposure to mathematics and science is vital for fostering interest in STEM. However, gender and racial inequities are embedded barriers within education systems, particularly affecting young Black girls. This study draws from a QuantCrit framework, combining advanced statistical methods and C...

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Bibliographic Details
Main Authors: Thao T. Vo, Shenghai Dai, Brian F. French
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Methods in Psychology
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Online Access:http://www.sciencedirect.com/science/article/pii/S2590260124000249
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Summary:Early exposure to mathematics and science is vital for fostering interest in STEM. However, gender and racial inequities are embedded barriers within education systems, particularly affecting young Black girls. This study draws from a QuantCrit framework, combining advanced statistical methods and Critical Race Theory (CRT) to explore Black girls’ mathematics and science dispositions. Latent Profile Analysis is used to explore unique, characterized groups of Black girls based on their confidence, interest, value, and motivation toward STEM topics. Each profile is examined with distal achievement outcomes and opportunity-to-learn factors. Implications of this race-focused work are discussed.
ISSN:2590-2601