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Download full textRadunzel, Justine – ACT, Inc., 2017
As pushes for increased accountability in higher education continue, postsecondary institutions are interested in identifying early on students who are at-risk of leaving their institution. With this in mind, this study sought to identify incoming first-year student information (such as that available on the ACT student record) that postsecondary…
Descriptors: College Entrance Examinations, At Risk Students, College Preparation, Dropouts
Radunzel, Justine – ACT, Inc., 2016
As pushes for increased accountability in higher education continue, postsecondary institutions are interested in identifying early on students who are at risk of leaving their institution. With this in mind, this study sought to identify incoming first-year student information (such as that available on the ACT student record) that postsecondary…
Descriptors: College Entrance Examinations, At Risk Students, College Preparation, Dropouts
Peer reviewed
Direct linkKomarraju, Meera; Ramsey, Alex; Rinella, Virginia – Learning and Individual Differences, 2013
Identifying the best predictors of academic performance is crucial for postsecondary institutions seeking students with the greatest promise. We investigated the relative strength of standardized test scores (ACT), high school GPA, and non-cognitive, college readiness skills in predicting college GPA. College freshmen (505) completed the 108-item…
Descriptors: Academic Achievement, College Readiness, Intellectual Disciplines, At Risk Students
Anderson, Susannah; Mezuk, Briana – Journal of Adolescence, 2012
This study investigates the relationship between participating in a high school debate program on college-readiness in the Chicago Public School district over a 10-year period. At-risk school students were identified using an index including 8th grade achievement, poverty status, and enrollment in special education. Regression analyses were used…
Descriptors: At Risk Students, Program Effectiveness, Adolescents, Public Schools
Pang, Xiao L.; And Others – 1994
The function of Mantel-Haenszel (MH) and logistic regression (LR) statistics with real data in detecting gender-based differentially functioning items (DIF) was investigated when sample size and criterion variable varied. The data base consisted of the item responses of a population of 183,356 Caucasians to the Math test of the ACT Assessment…
Descriptors: College Entrance Examinations, Foreign Countries, Identification, Item Bias
