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It is well known that women are underrepresented in science. technology engineering and mathematics (STEM) and that their interest declines more steeply over the schooling years. As such, this study uses a STEM identity theoretical framework to examine the effects of early STEM experiences, focusing particularly on experiences that may be more formative for female students. Given that early experiences are a form of capital, the study is also guided by nuanced perspectives on STEM capital and STEM identity capital. The data used were drawn from surveys administered to 15,725 college students. Blocked regression models were utilized and the results indicated a significant effect on STEM identity for students who reported encouragement in STEM from elementary school teachers, using STEM toys/kits, watching STEM-related TV programs or movies, playing STEM computer/video games, and observing or studying stars and other astronomical objects. Negative experiences included baking/cooking/kitchen chemistry and writing about STEM. To examine which of these experiences had long-lasting impact in the face of intervening experiences in middle/high school, controls were provided for middle/high school STEM interest. This indicated early experiences that translated to STEM identity capital in the future. Only observing stars became nonsignificant, while the other early experiences likely contributed to STEM identity capital. The findings highlight early experiences that can be formative for STEM identity years later (i.e., STEM identity capital) despite intervening years of changing STEM interest. As such, the results provide both practical and theoretical insight into understanding the development and maintenance of STEM identity.

This paper expands on knowledge of computing identity by building on what is known about prior identity models in science and mathematics education. The model theorizes three primary sub-constructs that contribute to the development of a computing identity: belief in one's performance/competence, interest, and recognition in computing. Drawing on data from a nationally representative survey of more than 1,700 college students at 22 colleges and universities, the study tested the alignment of the theorized model to the measures on the survey. Confirmatory Factor Analysis was used to validate whether the appropriate measures loaded on the three separate sub-constructs. Criterion-related validity was also established by testing whether the computing identity measures predicted the choice of a computer science career. The results reveal that a computing identity proxy based on the theorized measures was a highly significant predictor of students' computer science and information technology career choice (p < 0.0001). In addition, this work also established criterion-related validity by showing gender differences that had been found by prior work in computing. Finally, the theorized measures were found to be reliable and internally consistent. The educational understanding of computing identities may provide an important tool to help researchers and practitioners improve student persistence in computer science.