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Wolniak, Gregory C.; Muskens, Marjolein – Research in Higher Education, 2021
The study focuses on the phenomenon of "undermatching" in relation to the development of noncognitive attributes during the first year of college. Particular attention is paid to examining the role of first-generation college student status in moderating these relationships. The analyses utilize longitudinal data from the Netherlands (N…
Descriptors: Foreign Countries, College Freshmen, First Generation College Students, Student Motivation
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Denner, Jill; Potter, Susan; Anderson, Pamela; Torres, David – Research in Higher Education, 2023
There is persistent underrepresentation of female and ethnic and racial minority students in computing. While community colleges provide a unique opportunity to increase diversity in computing fields, many students do not persist. This study aims to understand the factors that predict students' momentum--completion of a certificate, degree, or…
Descriptors: Disproportionate Representation, Females, Minority Group Students, Racial Differences
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Ampaw, Frim D.; Jaeger, Audrey J. – Research in Higher Education, 2012
Doctoral programs have high dropout rates of 43% representing the highest among all post-baccalaureate programs. Cross sectional studies of doctoral students' retention have showed the importance of financial aid in predicting degree completion. These studies however, do not estimate the labor market's effect on doctoral student retention and…
Descriptors: Dropout Rate, Doctoral Programs, Labor Market, Predictor Variables
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Thompson, Mark E. – Research in Higher Education, 1976
The effectiveness of the Student Attitude Inventory (SAI) in predicting college success was examined. The SAI contains 47 items that identify students on the basis of (1) motivation, (2) study methods, (3) examination technique, and (4) lack of distractions toward academic work. (Editor/LBH)
Descriptors: Academic Achievement, Foreign Countries, Higher Education, Predictor Variables
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Margrain, Susan A. – Research in Higher Education, 1978
Recent literature on student characteristics and their predictive potential for academic achievement is reviewed. The results are often contradictory, and generally account for little variance beyond that accounted for by tests of intellectual ability. The usefulness of the cluster analysis approach is demonstrated. (Author/LBH)
Descriptors: Academic Achievement, Cluster Analysis, College Students, Higher Education