Improving prediction through machine learning: The relation between conscientiousness and academic achievement

Chernikova, O; FRANZEN, Patrick; Arens, A.K.; NIEPEL, Christoph; Stadler, M.; KELLER, Ulrich; FISCHBACH, Antoine; GREIFF, Samuel

doi:10.1027/1015-5759/a000896

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Improving prediction through machine learning: The relation between conscientiousness and academic achievement

Chernikova, O; FRANZEN, Patrick; Arens, A.K. et al.

2025 • In European Journal of Psychological Assessment

Peer Reviewed verified by ORBi Dataset

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https://hdl.handle.net/10993/64915

DOI
10.1027/1015-5759/a000896

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Keywords :

machine learning; conscientiousness; academic success; predictive modeling; psychological assessment

Abstract :

[en] In psychological assessment, gauging the impact of personality traits on academic outcomes is vital. Many studies explore the relation between academic achievement and traits like conscientiousness but prioritize description over prediction. Addressing this gap by focusing on actual prediction can refine assessment methodologies and deepen theoretical understanding. Our study focuses on predicting the influence of conscientiousness facets on standardized test scores using various machine learning strategies. Data from N = 7,949 Luxembourgish Grade 9 students showed a gradient boosting model with item-level predictors outperformed traditional linear regression (R2 = .123 vs. R2 = .077). This model revealed both linear and nonlinear ties between conscientiousness facets and achievement. Our findings accentuate conscientiousness’s underestimated predictive power for academic success and advocate for machine learning as a pivotal tool in psychological testing, particularly for outcome prediction.

Research center :

Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Luxembourg Centre for Educational Testing (LUCET)
Ludwig-Maximilian University of Munich, Germany
DIPF | Leibniz Institute for Research and Information in Education, Germany
Institute of Medical Education, LMU University Hospital, LMU Munich, Germany
Technical University Munich & Centre for International Student Assessment, Germany

Disciplines :

Education & instruction

Author, co-author :

Chernikova, O

FRANZEN, Patrick

Arens, A.K.

NIEPEL, Christoph ; University of Luxembourg

Stadler, M.

KELLER, Ulrich ; University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > LUCET

FISCHBACH, Antoine

GREIFF, Samuel

External co-authors :

yes

Language :

English

Title :

Improving prediction through machine learning: The relation between conscientiousness and academic achievement

Publication date :

13 May 2025

Journal title :

European Journal of Psychological Assessment

ISSN :

1015-5759

eISSN :

2151-2426

Publisher :

Hogrefe and Huber Publishers, Boston, United States - Massachusetts

Peer reviewed :

Peer Reviewed verified by ORBi

Focus Area :

Educational Sciences

Additional URL :

https://econtent.hogrefe.com/doi/abs/10.1027/1015-5759/a000896?journalCode=jpa

Name of the research project :

R-AGR-3214 - IRP17 - enhanCe - GREIFF Samuel

Data Set :

Synthetic data and supplementary material

Available on ORBilu :

since 13 May 2025

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