Black/African-American Learners in North America

Kai et al. (2017) pdf

• Models predicting student retention in an online college program
• J48 decision trees achieved much lower Kappa and AUC for Black students than White students
• JRip decision rules achieved almost identical Kappa and AUC for Black students and White students

Hu and Rangwala (2020) pdf

• Models predicting if a college student will fail in a course
• Multiple cooperative classifier model (MCCM) model was the best at reducing bias, or discrimination against African-American students, while other models (particularly Logistic Regression and Rawlsian Fairness) performed far worse
• The level of bias was inconsistent across courses, with MCCM prediction showing the least bias for Psychology and the greatest bias for Computer Science

Anderson et al. (2019) pdf

• Models predicting six-year college graduation
• Performance for African-American students comparable to performance for students in other races.

Christie et al. (2019)

Ramineni & Williamson (2018) [pdf]

• Revised automated scoring engine for assessing GSE essay
• Relative weakness in content and organization by African American test takers resulted in lower scores than Chinese peers who wrote longer.