Latino/Latina/Latinx/Hispanic Learners in North America

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Anderson et al. (2019) pdf

  • Models predicting six-year college graduation
  • Algorithms had higher false positive rates for White students and higher false negative rates for Latino students.

Lee and Kizilcec (2020) [pdf]

  • Model predicting college course grade of median or above
  • Out-of-the-box random forest model violates demographic parity and equality of opportunity for URM(underrepresented minority: American Indian, Black, Hawaiian or Pacific Islander, Hispanic, and Multicultural) than for non-URM students (White and Asian)