Is There Bias in Alternatives to Standardized Tests? An Investigation into Letters of Recommendation

Autor/inn/en	Dalal, Dev K.; Randall, Jason G.; Cheung, Ho Kwan; Gorman, Brandon C.; Roch, Sylvia G.; Williams, Kevin J.
Titel	Is There Bias in Alternatives to Standardized Tests? An Investigation into Letters of Recommendation
Quelle	In: International Journal of Testing, 22 (2022) 1, S.21-42 (22 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Dalal, Dev K.) ORCID (Cheung, Ho Kwan)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1530-5058
DOI	10.1080/15305058.2021.2019751
Schlagwörter	College Admission; Letters (Correspondence); Graduate Study; College Applicants; Gender Bias; Racial Bias; STEM Education; Masters Degrees; Doctoral Degrees; Grade Point Average; College Entrance Examinations; Graduate Record Examinations + Suchen Sie Ihr Suchwort? Hochschulzugang; Hochschulzulassung; Zulassung; Brief; Aufbaustudium; Graduiertenstudium; Hauptstudium; College applications; Studienbewerber; Geschlechterstereotyp; Racial discrimination; Rassismus; STEM; Doctoral degree; Doktorgrad; Aufnahmeprüfung
Abstract	Individuals concerned with subgroup differences on standardized tests suggest replacing these tests with holistic evaluations of unstructured application materials, such as letters of recommendation (LORs), which they posit show less bias. We empirically investigate this proposition that LORs are bias-free, and argue that LORs might actually invite systematic, race and gender subgroup differences in the content and evaluation of LORs. We text analyzed over 37,000 LORs submitted on behalf of over 10,000 graduate school applicants. Results showed that LOR content does differ across applicants. Furthermore, we see some systematic gender, race, and gender-race intersection differences in LOR content. Content of LORs also systematically differed between degree programs (S.T.E.M. vs. non-S.T.E.M.) and degree sought (doctoral vs. masters). Finally, LOR content alone did not predict an appreciable amount of variance in offers of admission (the first barrier to increasing diversity and inclusion in graduate programs). Our results, combined with past research on LOR content bias, highlight concerns that LORs can be biased against marginalized groups. We conclude with suggestions for reducing potential bias in LOR and for increasing diversity in graduate programs. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01