Free access to paper on 'Cross‐Validated Prediction of Academic Performance of First‐Year University Students'


  • Author: Statistics Views
  • Date: 15 April 2019

Each week, we select a recently published article and offer either free access or highlight a recent open access publication. This week's is from Educational Measurement: Issues and Practice and is available from the Spring 2019 issue.

Cross‐Validated Prediction of Academic Performance of First‐Year University Students: Identifying Risk Factors in a Nonselective Environment

Eline Meijer, Marc P. H. D. Cleiren, Elise Dusseldorp, Vincent J. C. Buurman, Roel M. Hogervorst and Willem J. Heiser

Educational Measurement: Issues in Practice, Volume 38, Issue 1,Spring 2019, pages 36-47


thumbnail image: Free access to paper on 'Cross‐Validated Prediction of Academic Performance of First‐Year University Students'

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.

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