Exploring Bias in Math Teachers’ Perceptions of Students’ Ability by Gender and Race/Ethnicity

Riegle‐Crumb, Catherine; Humphries, Melissa

doi:10.1177/0891243211434614

Cited by 182 publications

(114 citation statements)

References 44 publications

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“…These results are consistent with recent evidence suggesting that some teachers stigmatize female students, particularly in math courses (Lavy & Sand, 2015;Riegle-Crumb & Humphries, 2012).…”

supporting

confidence: 82%

Who Believes in Me? The Effect of Student-Teacher Demographic Match on Teacher Expectations

2015

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. www.econstor.eu The Institute for the Study of Labor (IZA) in Bonn is a local and virtual international research center and a place of communication between science, politics and business. IZA is an independent nonprofit organization supported by Deutsche Post Foundation. The center is associated with the University of Bonn and offers a stimulating research environment through its international network, workshops and conferences, data service, project support, research visits and doctoral program. IZA engages in (i) original and internationally competitive research in all fields of labor economics, (ii) development of policy concepts, and (iii) dissemination of research results and concepts to the interested public. Terms of use: Documents in D I S C U S S I O N P A P E R S E R I E SIZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author. Teachers are an important source of information for traditionally disadvantaged students. However, little is known about how teachers form expectations and whether their expectations are systematically biased. We investigate whether student-teacher demographic mismatch affects high school teachers' expectations for students' educational attainment. Using a student fixed effects strategy that exploits expectations data from two teachers per student, we find that non-black teachers of black students have significantly lower expectations than do black teachers. These effects are larger for black male students and math teachers. Our findings add to a growing literature on the role of limited information in perpetuating educational attainment gaps.JEL Classification: I24, D84, J15, J16

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supporting

confidence: 82%

Who Believes in Me? The Effect of Student-Teacher Demographic Match on Teacher Expectations

2015

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“…These results are consistent with recent evidence suggesting that some teachers stigmatize female students, particularly in math courses (Lavy and Sand 2015;Riegle-Crumb and Humphries 2012).…”

Section: Datasupporting

confidence: 82%

Who Believes in Me? The Effect of Student-Teacher Demographic Match on Teacher Expectations

Gershenson¹,

Holt²,

Papageorge³

2015

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Teachers are an important source of information for traditionally disadvantaged students. However, little is known about how teachers form expectations and whether they are systematically biased. We investigate whether student-teacher demographic mismatch affects high school teachers' expectations for students' educational attainment. Using a student fixed effects strategy that exploits expectations data from two teachers per student, we find that nonblack teachers of black students have significantly lower expectations than do black teachers. These effects are larger for black male students and math teachers. Our findings add to a growing literature on the role of limited information in perpetuating educational attainment gaps. JEL Classification Codes: I24; D84; J15; J16

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“…Recent studies indicate that the teaching environment of math is important for this achievement pattern (Riegle-Crumb and Humphries, 2012;Pope and Sydnor, 2010;Niederle and Vesterlund, 2010). As a consequence, there may be a lost pool of talent among girls with high math abilities.…”

Section: Introductionmentioning

confidence: 99%

Math and Gender: Is Math a Route to a High-Powered Career?

Joensen

Nielsen

2013

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes.You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. licence. www.econstor.eu The Institute for the Study of Labor (IZA) in Bonn is a local and virtual international research center and a place of communication between science, politics and business. IZA is an independent nonprofit organization supported by Deutsche Post Foundation. The center is associated with the University of Bonn and offers a stimulating research environment through its international network, workshops and conferences, data service, project support, research visits and doctoral program. IZA engages in (i) original and internationally competitive research in all fields of labor economics, (ii) development of policy concepts, and (iii) dissemination of research results and concepts to the interested public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated D I S C U S S I O N P A P E R S E R I E SIZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author. There is a large gender gap in advanced math coursework in high school that many believe exists because girls are discouraged from taking math courses. In this paper, we exploit an institutional change that reduced the costs of acquiring advanced high school math to determine if access is, in fact, the mechanism -in particular for girls at the top of the math ability distribution. By estimating marginal treatment effects of acquiring advanced math qualifications, we document substantial beneficial wage effects from encouraging even more females to opt for these qualifications. Our analysis suggests that the beneficial effect comes from accelerating graduation and attracting females to high-paid or traditionally maledominated career tracks and to CEO positions. Our results may be reconciled with experimental and empirical evidence suggesting there is a pool of unexploited math talent among high ability girls that may be retrieved by changing the institutional set-up of math teaching. ...

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Exploring Bias in Math Teachers’ Perceptions of Students’ Ability by Gender and Race/Ethnicity

Cited by 182 publications

References 44 publications

Who Believes in Me? The Effect of Student-Teacher Demographic Match on Teacher Expectations

Who Believes in Me? The Effect of Student-Teacher Demographic Match on Teacher Expectations

Who Believes in Me? The Effect of Student-Teacher Demographic Match on Teacher Expectations

Math and Gender: Is Math a Route to a High-Powered Career?

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