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Download full textDenisa Gándara; Hadis Anahideh; Matthew P. Ison; Lorenzo Picchiarini – AERA Open, 2024
Colleges and universities are increasingly turning to algorithms that predict college-student success to inform various decisions, including those related to admissions, budgeting, and student-success interventions. Because predictive algorithms rely on historical data, they capture societal injustices, including racism. In this study, we examine…
Descriptors: Algorithms, Social Bias, Minority Groups, Equal Education
Nicholas Bowman; Christine Logel; Jennifer Lacosse; Elizabeth A. Canning; Katherine T. U. Emerson; Mary C. Murphy – AERA Open, 2023
In the context of continued equity gaps in student success within and beyond STEM, this paper explored the extent to which the representation of underrepresented racial minority (URM) and first-generation college students predict grades in postsecondary STEM courses. The analyses examined 87,027 grades received by 11,868 STEM-interested students…
Descriptors: Minority Group Students, Academic Achievement, Equal Education, College Students
Balzer Carr, Brandon; London, Rebecca A. – AERA Open, 2020
Meeting college students' basic needs is the goal of a new set of student success initiatives that address students' urgent food, housing, or financial hardships in an effort to help them remain and succeed in college. Focusing on one California public university, we describe one such basic needs program, identifying the students who participate,…
Descriptors: Student Needs, College Students, Student Personnel Services, Hunger
