Portability of Predictive Academic Performance Models: An Empirical Sensitivity Analysis

Jose Luis Arroyo-Barrigüete, Susana Carabias-López, Tomas Curto-González and Adolfo Hernández
Additional contact information
Jose Luis Arroyo-Barrigüete: Department of Quantitative Methods, Pontifical University of Comillas, 28015 Madrid, Spain
Susana Carabias-López: Department of Quantitative Methods, Pontifical University of Comillas, 28015 Madrid, Spain
Tomas Curto-González: Department of Quantitative Methods, Pontifical University of Comillas, 28015 Madrid, Spain
Adolfo Hernández: Department of Financial and Actuarial Economics and Statistics, Faculty of Commerce and Tourism, Complutense University of Madrid, 28040 Madrid, Spain

Mathematics, 2021, vol. 9, issue 8, 1-15

Abstract: The portability of predictive models of academic performance has been widely studied in the field of learning platforms, but there are few studies in which the results of previous evaluations are used as factors. The aim of this work was to analyze portability precisely in this context, where preceding performance is used as a key predictor. Through a study designed to control the main confounding factors, the results of 170 students evaluated over two academic years were analyzed, developing various predictive models for a base group (BG) of 39 students. After the four best models were selected, they were validated using different statistical techniques. Finally, these models were applied to the remaining groups, controlling the number of different factors with respect to the BG. The results show that the models’ performance varies consistently with what was expected: as they move away from the BG (fewer common characteristics), the specificity of the four models tends to decrease.

Keywords: mathematics education; university teaching; academic success; quantitative research; predictive models; portability (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/9/8/870/pdf (application/pdf)
https://www.mdpi.com/2227-7390/9/8/870/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:9:y:2021:i:8:p:870-:d:536540

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().