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      Mitigating gender bias in student evaluations of teaching

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          Abstract

          Student evaluations of teaching are widely believed to contain gender bias. In this study, we conduct a randomized experiment with the student evaluations of teaching in four classes with large enrollments, two taught by male instructors and two taught by female instructors. In each of the courses, students were randomly assigned to either receive the standard evaluation instrument or the same instrument with language intended to reduce gender bias. Students in the anti-bias language condition had significantly higher rankings of female instructors than students in the standard treatment. There were no differences between treatment groups for male instructors. These results indicate that a relatively simple intervention in language can potentially mitigate gender bias in student evaluation of teaching.

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          Most cited references 16

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          Mental contamination and mental correction: unwanted influences on judgments and evaluations.

          We define mental contamination as the process whereby a person has an unwanted response because of mental processing that is unconscious or uncontrollable. This type of bias is distinguishable from the failure to know or apply normative rules of inference and can be further divided into the unwanted consequences of automatic processing and source confusion, which is the confusion of 2 or more causes of a response. Mental contamination is difficult to avoid because it results from both fundamental properties of human cognition (e.g., a lack of awareness of mental processes) and faulty lay beliefs about the mind (e.g., incorrect theories about mental biases). People's lay beliefs determine the steps they take (or fail to take) to correct their judgments and thus are an important but neglected source of biased responses. Strategies for avoiding contamination, such as controlling one's exposure to biasing information, are discussed.
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            Stereotypes and prejudice: Their automatic and controlled components.

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              What’s in a Name: Exposing Gender Bias in Student Ratings of Teaching

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                15 May 2019
                2019
                : 14
                : 5
                Affiliations
                [1 ] Department of Political Science, Iowa State University, Ames, Iowa, United States of America
                [2 ] Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, Iowa, United States of America
                [3 ] Department of Natural Resource Ecology and Management, Iowa State University, Ames, Iowa, United States of America
                Rice University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Article
                PONE-D-19-00552
                10.1371/journal.pone.0216241
                6519786
                31091292
                © 2019 Peterson et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Figures: 2, Tables: 4, Pages: 10
                Product
                Funding
                The authors received no specific funding for this work.
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                All files necessary to replicate the results are available from the Harvard Dataverse ( https://doi.org/10.7910/DVN/AB4ZAV).

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