Asian/Asian-American Learners in North America

Christie et al. (2019) pdf

• Models predicting student's high school dropout
• The decision trees showed little difference in AUC among White, Black, Hispanic, Asian, American Indian and Alaska Native, and Native Hawaiian and Pacific Islander.

Bridgeman et al. (2009) pdf

• Automated scoring models for evaluating English essays, or e-rater
• E-rater gave significantly higher score for 11th grade essays written by Asian American and Hispanic students, particularly, Hispanic female students
• The score difference between human rater and e-rater was significantly smaller for 11th grade essays written by White and African American students
• E-rater gave slightly lower score for GRE essays (argument and issue) written by Black test-takers while e-rated scores were higher for Asian test-takers in the U.S

Lee and Kizilcec (2020) [[1](https://arxiv.org/pdf/2007.00088.pdf) pdf]

• Models predicting college success (or median grade or above)
• Random forest algorithms performed significantly worse for underrepresented minority students (URM; American Indian, Black, Hawaiian or Pacific Islander, Hispanic, and Multicultural) than non-URM students (White and Asian)
• The fairness of the model, namely demographic parity and equality of opportunity, as well as its accuracy, improved after correcting the threshold values from 0.5 to group-specific values