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      Teachers’ Bias Against the Mathematical Ability of Female, Black, and Hispanic Students

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          Abstract

          Researchers have long endeavored to understand whether teachers’ evaluations of their students’ mathematical ability or performance are accurate or whether their evaluations reveal implicit biases. To disentangle these factors, in a randomized controlled study (N = 390), we examined teachers’ evaluations of 18 mathematical solutions to which gender- and race-specific names had been randomly assigned. Teachers displayed no detectable bias when assessing the correctness of students’ solutions; however, when assessing students’ mathematical ability, biases against Black, Hispanic, and female students were revealed, with biases largest against Black and Hispanic girls. Specifically, non-White teachers’ estimations of students’ mathematical ability favored White students (both boys and girls) over students of color, whereas (primarily female) White teachers’ estimations of students’ mathematical ability favored boys over girls. Results indicate that teachers are not free of bias, and that teachers from marginalized groups may be susceptible to bias that favors stereotype-advantaged groups.

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          Most cited references52

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          Associative and propositional processes in evaluation: an integrative review of implicit and explicit attitude change.

          A central theme in recent research on attitudes is the distinction between deliberate, "explicit" attitudes and automatic, "implicit" attitudes. The present article provides an integrative review of the available evidence on implicit and explicit attitude change that is guided by a distinction between associative and propositional processes. Whereas associative processes are characterized by mere activation independent of subjective truth or falsity, propositional reasoning is concerned with the validation of evaluations and beliefs. The proposed associative-propositional evaluation (APE) model makes specific assumptions about the mutual interplay of the 2 processes, implying several mechanisms that lead to symmetric or asymmetric changes in implicit and explicit attitudes. The model integrates a broad range of empirical evidence and implies several new predictions for implicit and explicit attitude change.
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            Internal and external motivation to respond without prejudice.

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              Penalties for success: reactions to women who succeed at male gender-typed tasks.

              A total of 242 subjects participated in 3 experimental studies investigating reactions to a woman's success in a male gender-typed job. Results strongly supported the authors' hypotheses, indicating that (a) when women are acknowledged to have been successful, they are less liked and more personally derogated than equivalently successful men (Studies 1 and 2); (b) these negative reactions occur only when the success is in an arena that is distinctly male in character (Study 2); and (c) being disliked can have career-affecting outcomes, both for overall evaluation and for recommendations concerning organizational reward allocation (Study 3). These results were taken to support the idea that gender stereotypes can prompt bias in evaluative judgments of women even when these women have proved themselves to be successful and demonstrated their competence. The distinction between prescriptive and descriptive aspects of gender stereotypes is considered, as well as the implications of prescriptive gender norms for women in work settings. (c) 2004 APA
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                Author and article information

                Journal
                Educational Researcher
                Educational Researcher
                American Educational Research Association (AERA)
                0013-189X
                1935-102X
                December 05 2019
                : 0013189X1989057
                Affiliations
                [1 ]University of Southern California, Los Angeles, CA
                [2 ]New York University, New York, NY
                [3 ]Indiana University, Bloomington, IL
                Article
                10.3102/0013189X19890577
                ec23401f-6704-4fcc-af77-f5b0d153c743
                © 2019

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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