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Cross‐Validated Prediction of Academic Performance of First‐Year University Students: Identifying Risk Factors in a Nonselective Environment
Author(s) -
Meijer Eline,
Cleiren Marc P. H. D.,
Dusseldorp Elise,
Buurman Vincent J. C.,
Hogervorst Roel M.,
Heiser Willem J.
Publication year - 2018
Publication title -
educational measurement: issues and practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.158
H-Index - 52
eISSN - 1745-3992
pISSN - 0731-1745
DOI - 10.1111/emip.12204
Subject(s) - attrition , bachelor , psychology , multivariate statistics , academic achievement , medical education , multivariate analysis , attribution , path analysis (statistics) , mathematics education , applied psychology , computer science , social psychology , medicine , dentistry , archaeology , machine learning , history
Early prediction of academic performance is important for student support. The authors explored, in a multivariate approach, whether pre‐entry data (e.g., high school study results, preparative activities, expectations, capabilities, motivation, and attitude) could predict university students’ first‐year academic performance. Preregistered applicants for a bachelor's program filled out an intake questionnaire before study entry. Outcome data (first‐year grade point average, course credits, and attrition) were obtained 1 year later. Prediction accuracy was assessed by cross‐validation. Students who performed better in preparatory education, followed a conventional educational path before entering, and expected to spend more time on a program‐related organization performed better during their first year at university. Concrete preuniversity behaviors were more predictive than psychological attributions such as self‐efficacy. Students with a “love of learning” performed better than leisure‐oriented students. The intake questionnaire may be used for identifying up front who may need additional support, but is not suitable for student selection.