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      A Longitudinal Study of How Quality Mentorship and Research Experience Integrate Underrepresented Minorities into STEM Careers

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          Abstract

          This longitudinal study examines how undergraduate research experience and quality mentorship experiences in college predict the growth of scientific efficacy, identity, and values. Results also show how growth trajectories predict students who stay in STEM, pursue medical/health degrees, or leave STEM careers 4 years after graduation.

          Abstract

          African Americans, Latinos, and Native Americans are historically underrepresented minorities (URMs) among science, technology, engineering, and mathematics (STEM) degree earners. Viewed from a perspective of social influence, this pattern suggests that URMs do not integrate into the STEM academic community at the same rate as non-URM students. Estrada and colleagues recently showed that Kelman’s tripartite integration model of social influence (TIMSI) predicted URM persistence into science fields. In this paper, we longitudinally examine the integration of URMs into the STEM community by using growth-curve analyses to measure the development of TIMIS’s key variables (science efficacy, identity, and values) from junior year through the postbaccalaureate year. Results showed that quality mentorship and research experience occurring in the junior and senior years were positively related to student science efficacy, identity, and values at that same time period. Longitudinal modeling of TIMSI further shows that, while efficacy is important, and perhaps a necessary predictor of moving toward a STEM career, past experiences of efficacy may not be sufficient for maintaining longer-term persistence. In contrast, science identity and values do continue to be predictive of STEM career pathway persistence up to 4 years after graduation.

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          Missing data: our view of the state of the art.

          Statistical procedures for missing data have vastly improved, yet misconception and unsound practice still abound. The authors frame the missing-data problem, review methods, offer advice, and raise issues that remain unresolved. They clear up common misunderstandings regarding the missing at random (MAR) concept. They summarize the evidence against older procedures and, with few exceptions, discourage their use. They present, in both technical and practical language, 2 general approaches that come highly recommended: maximum likelihood (ML) and Bayesian multiple imputation (MI). Newer developments are discussed, including some for dealing with missing data that are not MAR. Although not yet in the mainstream, these procedures may eventually extend the ML and MI methods that currently represent the state of the art.
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            A threat in the air. How stereotypes shape intellectual identity and performance.

            C Steele (1997)
            A general theory of domain identification is used to describe achievement barriers still faced by women in advanced quantitative areas and by African Americans in school. The theory assumes that sustained school success requires identification with school and its subdomains; that societal pressures on these groups (e.g., economic disadvantage, gender roles) can frustrate this identification; and that in school domains where these groups are negatively stereotyped, those who have become domain identified face the further barrier of stereotype threat, the threat that others' judgments or their own actions will negatively stereotype them in the domain. Research shows that this threat dramatically depresses the standardized test performance of women and African Americans who are in the academic vanguard of their groups (offering a new interpretation of group differences in standardized test performance), that it causes disidentification with school, and that practices that reduce this threat can reduce these negative effects.
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              A Theory of Cultural Values and Some Implications for Work

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                Author and article information

                Contributors
                Role: Monitoring Editor
                Journal
                CBE Life Sci Educ
                CBE Life Sci Educ
                CBE-LSE
                CBE-LSE
                lse
                CBE Life Sciences Education
                American Society for Cell Biology
                1931-7913
                Spring 2018
                : 17
                : 1
                : ar9
                Affiliations
                []Department of Social and Behavioral Sciences, University of California, San Francisco, San Francisco, CA 94118
                []Department of Learning Sciences and Human Development, West Virginia University, Morgantown, WV 26506
                [§ ]Department of Psychology, California State University San Marcos, San Marcos, CA 92096
                Author notes
                *Address correspondence to: Mica Estrada ( mica.estrada@ 123456ucsf.edu ).
                Article
                CBE.17-04-0066
                10.1187/cbe.17-04-0066
                6007776
                29351912
                b479c7e2-f9c9-4b56-a00c-6d5be36aaaf7
                © 2018 M. Estrada et al. CBE—Life Sciences Education © 2018 The American Society for Cell Biology. “ASCB®” and “The American Society for Cell Biology®” are registered trademarks of The American Society for Cell Biology.

                This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License.

                History
                : 17 April 2017
                : 17 October 2017
                : 19 October 2017
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                Education
                Education

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