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Autor/inn/enCherner, Todd; Fegely, Alex; Mitchell, Chrystine; Gleasman, Cory
TitelAddressing Implicit Bias in Educator Preparation Programs through Search Engines: An Alternative to Implicit Association Tests
QuelleIn: Journal of Technology and Teacher Education, 28 (2020) 4, S.639-663 (25 Seiten)
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1059-7069
SchlagwörterTeacher Education Programs; Social Attitudes; Preservice Teachers; Social Bias; Search Engines; Negative Attitudes; Cultural Differences; Racial Bias; Ethnicity; Social Influences; Preservice Teacher Education; Minority Groups; Socioeconomic Status; Educational Attainment; Political Issues; Student Attitudes; Misconceptions; Visual Stimuli; Gender Bias; Stereotypes
AbstractImplicit bias is an important area of study in the field of education because it permeates schools, and it can severely affect the experiences students have in the classroom. Historically, scholars have used implicit association tests to identify implicit bias in pre-service teachers, but they have not addressed the role technology plays in it. Through an input-output framework designed for bias, this mixed methods study tests a strategy for using search engine results to increase pre-service teachers' awareness of implicit bias. This study explains the strategy's design and purpose in detail before discussing the results and sharing implications for teacher educators. (As Provided).
AnmerkungenAssociation for the Advancement of Computing in Education. P.O. Box 719, Waynesville, NC 28786. Tel: 828-246-9558; Fax: 828-246-9557; e-mail: info@aace.org; Web site: http://www.aace.org
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2024/1/01
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