Content Analysis of Textbooks via Natural Language Processing: Findings on Gender, Race, and Ethnicity in Texas U.S. History Textbooks

Autor/inn/en	Lucy, Li; Demszky, Dorottya; Bromley, Patricia; Jurafsky, Dan
Titel	Content Analysis of Textbooks via Natural Language Processing: Findings on Gender, Race, and Ethnicity in Texas U.S. History Textbooks
Quelle	In: AERA Open, 6 (2020) 3, (27 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2332-8584
Schlagwörter	Textbooks; United States History; History Instruction; Textbook Content; Minority Groups; Hispanic Americans; Whites; Racial Bias; Ethnicity; African Americans; Females; Stereotypes; Political Issues; Counties; Social Bias; Gender Bias; Artificial Intelligence; Vocabulary; Texas + Suchen Sie Ihr Suchwort? Textbook; Text book; Schulbuch; Lehrbuch; History lessons; Geschichtsunterricht; Lehrbuchtext; Ethnische Minderheit; Hispanic; Hispanoamerikaner; White; Weißer; Racial discrimination; Rassismus; Ethnizität; Afroamerikaner; Weibliches Geschlecht; Klischee; Politischer Faktor; Geschlechterstereotyp; Künstliche Intelligenz; Wortschatz
Abstract	Cutting-edge data science techniques can shed new light on fundamental questions in educational research. We apply techniques from natural language processing (lexicons, word embeddings, topic models) to 15 U.S. history textbooks widely used in Texas between 2015 and 2017, studying their depiction of historically marginalized groups. We find that Latinx people are rarely discussed, and the most common famous figures are nearly all White men. Lexicon-based approaches show that Black people are described as performing actions associated with low agency and power. Word embeddings reveal that women tend to be discussed in the contexts of work and the home. Topic modeling highlights the higher prominence of political topics compared with social ones. We also find that more conservative counties tend to purchase textbooks with less representation of women and Black people. Building on a rich tradition of textbook analysis, we release our computational toolkit to support new research directions. (As Provided).
Anmerkungen	SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: http://sagepub.com
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2022/1/01