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Denisa 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
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Preeya P. Mbekeani; Daniel Koretz – AERA Open, 2024
Validity studies of college admissions tests have found that, on average, students who are Black or Hispanic earn lower freshman grade-point averages (FGPAs) than predicted by these test scores. This differential prediction is used as a measure of bias. These studies, however, conflate student and school characteristics. The differential…
Descriptors: African American Students, Hispanic American Students, Grade Point Average, Racial Differences
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Elise Swanson; Tatiana Melguizo; Paco Martorell – AERA Open, 2021
This article estimates the relationship between students' psychosocial and academic outcomes during their first 3 years enrolled at public, 4-year institutions. Our sample comprises students from low-income backgrounds who applied for a competitive scholarship and enrolled at a 4-year public institution. We follow two cohorts of entering students…
Descriptors: Outcomes of Education, Academic Achievement, College Students, Psychological Patterns
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Holzer, Julia; Lüftenegger, Marko; Korlat, Selma; Pelikan, Elisabeth; Salmela-Aro, Katariina; Spiel, Christiane; Schober, Barbara – AERA Open, 2021
In the wake of COVID-19, university students have experienced fundamental changes of their learning and their lives as a whole. The present research identifies psychological characteristics associated with students' well-being in this situation. We investigated relations of basic psychological need satisfaction (experienced competence, autonomy,…
Descriptors: College Students, Student Needs, Competence, Predictor Variables
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Svoboda, Ryan C.; Rozek, Christopher S.; Hyde, Janet S.; Harackiewicz, Judith M.; Destin, Mesmin – AERA Open, 2016
High school students from lower-socioeconomic status (SES) backgrounds are less likely to enroll in advanced mathematics and science courses compared to students from higher-SES backgrounds. The current longitudinal study draws on identity-based and expectancy-value theories of motivation to explain the SES and mathematics and science…
Descriptors: Correlation, Educational Attainment, Parent Background, STEM Education