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How can colleges use predictive algorithms equitably? A conversation with Dr. Denisa Gándara

IHEP Institute for Higher Education Policy

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.

Literacy 147
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Student Success, Retention, and Employability – Getting Digital in a High Tech, High Touch Environment

Eric Stoller on Academic Advising

Student Success. Student engagement is everything when it comes to student success. Admissions professionals, academics, academic advisors, career services representatives, tutors, alumni officers, etc. The more engaged a student is during their university experience, the more successful they will be.

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Digital Engagement – How Technology Enhances the Student Experience

Eric Stoller on Academic Advising

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.

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Advising, Counseling, Mentoring and Teaching Black Males in Secondary and Postsecondary Settings

Diverse: Issues in Higher Education

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.).

Advising 321