Abstract
Using multiple admission tools in university admission procedures is common practice. This is particularly useful if different admission tools uniquely select different subgroups of students who will be successful in university programs. A signal-detection approach was used to investigate the accuracy of Secondary School grade point average (SSGPA), an admission test score (ACS) and a non-cognitive score (NCS) in uniquely selecting successful students. This was done for three consecutive first year cohorts of a broad psychology program. Each applicant’s score on SSGPA, ACS or NCS alone - and on seven combinations of these scores, all considered separate ‘admission tools’ - was compared at two different (medium and high) cut-off scores (criterion levels). Each of the tools selected successful students who were not selected by any of the other tools. Both sensitivity and specificity were enhanced by implementing multiple tools. The signal-detection approach distinctively provided useful information for decisions on admission instruments and cut-off scores.
Highlights
Admission committees of selective university programs need information on the accuracy of admission tools and on the selection outcomes that result from them
Admission test Cognitive Score (ACS) is a snapshot measurement of academic achievement compared to secondary school grade point average (SSGPA)—ACS being based on one week of program-specific “studying for a week” and SSGPA on 5 years of secondary education
Such work samples in admission of psychology students have been found to be predictive of academic achievement in the program (Visser et al, 2012; Niessen et al, 2016)
Summary
Admission committees of selective university programs need information on the accuracy of admission tools and on the selection outcomes that result from them. The literature on admission and selection at universities focuses primarily on predicting academic achievement in terms of grade point averages, retention and study length. Research into predictors other than secondary school grade point average (SSGPA)—which is far from accurate—is still work in progress, and a “gold standard” has not yet been conceived (Richardson et al, 2012; Schripsema et al, 2014, 2017; Shulruf and Shaw, 2015; Makransky et al, 2016; Patterson et al, 2016; Pau et al, 2016; Sladek et al, 2016; Yhnell et al, 2016; Wouters et al, 2017). Program- and institution specific work samples appear promising valuable predictors of academic achievement in addition to past academic achievement (Niessen et al, 2016; Stegers-Jager, 2017; van Ooijen-van der Linden et al, 2017)
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