
Why women perform better in college than admission scores would predict: Exploring the roles of conscientiousness and course-taking patterns.
Author(s) -
Heidi N. Keiser,
Paul R. Sackett,
Nathan R. Kuncel,
Thomas Brothen
Publication year - 2016
Publication title -
journal of applied psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.522
H-Index - 284
eISSN - 1939-1854
pISSN - 0021-9010
DOI - 10.1037/apl0000069
Subject(s) - conscientiousness , psychology , aptitude , personality , trait , multilevel model , cognition , big five personality traits , developmental psychology , social psychology , statistics , extraversion and introversion , mathematics , neuroscience , computer science , programming language
Women typically obtain higher subsequent college GPAs than men with the same admissions test score. A common reaction is to attribute this to a flaw in the admissions test. We explore the possibility that this underprediction of women's performance reflects gender differences in conscientiousness and college course-taking patterns. In Study 1, we focus on using the ACT to predict performance in a single, large course where performance is decomposed into cognitive (exam and quiz scores) and less cognitive, discretionary components (discussion and extra credit points). The ACT does not underpredict female's cognitive performance, but it does underpredict female performance on the less cognitive, discretionary components of academic performance, because it fails to measure and account for the personality trait of conscientiousness. In Study 2, we create 2 course-difficulty indices (Course Challenge and Mean Aptitude in Course) and add them to an HLM regression model to see if they reduce the degree to which SAT scores underpredict female performance. Including Course Challenge does result in a modest reduction of the gender coefficient; however, including Mean Aptitude in Course does not. Thus, differences in course-taking patterns is a partial (albeit small) explanation for the common finding of differential prediction by gender.