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Riley N. Loria; Edgar I. Sanchez – ACT Education Corp., 2024
Effectively predicting academic success is essential for providing students with the resources they need to succeed in their careers and for matching individuals to postsecondary institutions that suit their needs. Despite evidence for ACT scores as meaningful predictors of both first-year grade point average (FYGPA) and degree completion, little…
Descriptors: College Entrance Examinations, Predictive Validity, Time to Degree, Models
Tucker, Leslie; McKnight, Oscar – Journal of College Student Retention: Research, Theory & Practice, 2019
This study assessed the feasibility of using precollege success indicators to identify at-risk students at a large 4-year public research university in the Midwest. Retention data from students who participated in an established student success program were examined. The findings affirm that the initial admissions assessment identifying at-risk…
Descriptors: Validity, Academic Achievement, College Students, At Risk Students
Davison, Mark L.; Semmes, Robert; Huang, Lan; Close, Catherine N. – Educational and Psychological Measurement, 2012
Data from 181 college students were used to assess whether math reasoning item response times in computerized testing can provide valid and reliable measures of a speed dimension. The alternate forms reliability of the speed dimension was .85. A two-dimensional structural equation model suggests that the speed dimension is related to the accuracy…
Descriptors: Computer Assisted Testing, Reaction Time, Reliability, Validity
Harmston, Matt T. – Association for Institutional Research (NJ1), 2004
This study was intended to serve as an example of cross-validating results from student persistence prediction models that employed commonly available pre-college student characteristics. The study investigated whether the accuracy of predicting student persistence would vary because of the use of present-year vs. previous-year parameters on…
Descriptors: Academic Persistence, College Freshmen, Prediction, Models

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