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New research reveals that algorithms commonly used by institutions to predict student success may be racially biased against Black and Latinx students. When a model predicts that Black or Latinx students are more likely to fail, how users interpret that information depends on their racial consciousness and data literacy.
Student Success. Student engagement is everything when it comes to student success. Admissions professionals, academics, academicadvisors, career services representatives, tutors, alumni officers, etc. The more engaged a student is during their university experience, the more successful they will be.
The creative and imaginative ways in which we make meaning, offer services, engage, and even make predictions for future success are all predicated on a variety of technology-based solutions. It’s essentially a built-in experiential digital literacy program. Student Information Systems and Predictive Analytics. Being Human.
Some of the topics include literacy and math, advising Black male engineering majors, socio-emotional development, leadership, community college experiences, Black male veterans, athletes in P-12 and higher education, and the recruitment and retention of Black males in educator preparation programs. Hines and E.C. Fletcher (Eds.).
They work to help students navigate college, build peer networks, connect with staff, connect with faculty, provide different types of training, including financial literacy, all sorts of really wonderful types of supports wraparound supports that are not commonly found. And if they do that, then certainly AANAPISIs would be in that group.
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