National and International Examination

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Baker et al. (2020) pdf

  • Model predicting student graduation and SAT scores for military-connected students
  • For prediction of graduation, algorithms applying across population resulted an AUC of 0.60, degrading from their original performance by 70% or 71% towards chance.
  • For prediction of SAT scores, algorithms applying across population resulted in a Spearman's ρ of 0.42 and 0.44, degrading a third from their original performance to chance.

Li et al. (2021) pdf

  • Model predicting student achievement on the standardized examination PISA
  • Inaccuracy of the U.S.-trained model was greater for students from countries with lower scores of national development (e.g. Indonesia, Vietnam, Moldova)

Sulaiman & Roy (2022) [1]

  • Models predicting whether a law student will pass the bar exam (to practice law)
  • Compared White and non-White students
  • Models not applying fairness constraints performed significantly worse for White students in terms of ABROCA
  • Models applying fairness constraints performed equivalently for White and non-White students