Scoring the Big Five for longitudinally assessed academic achievement predictiveness: Manifest, correlated-factors model, and bifactor modeling across multiple contexts

Georg Krammer; Julie Aitken Schermer; Corinna Koschmieder; Richard Goffin; Nhung Hendy

doi:10.1111/ijsa.12500

Scoring the Big Five for longitudinally assessed academic achievement predictiveness: Manifest, correlated-factors model, and bifactor modeling across multiple contexts

Georg Krammer, Julie Aitken Schermer, Corinna Koschmieder, Richard Goffin, Nhung Hendy

Institute of Business and Vocational Education

Research output: Contribution to journal › Article › peer-review

Original language	English
Article number	e12500
Number of pages	23
Journal	International Journal of Selection and Assessment
Volume	33
Issue number	1
DOIs	https://doi.org/10.1111/ijsa.12500
Publication status	Published - 2024

Fields of science

502052 Business administration
503 Educational Sciences
503002 Applied education
503007 Didactics
503014 Subject didactics of social sciences
503030 Business education
501016 Educational psychology
501003 Occupational psychology
501011 Cognitive psychology
603102 Epistemology
503001 General education
503005 Vocational education
503006 Educational research
503025 School pedagogy

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1111/ijsa.12500

Cite this

@article{5bb38ce8008d41e4a19c991a01550c9d,

title = "Scoring the Big Five for longitudinally assessed academic achievement predictiveness: Manifest, correlated-factors model, and bifactor modeling across multiple contexts",

author = "Georg Krammer and Schermer, \{Julie Aitken\} and Corinna Koschmieder and Richard Goffin and Nhung Hendy",

year = "2024",

doi = "10.1111/ijsa.12500",

language = "English",

volume = "33",

journal = "International Journal of Selection and Assessment",

issn = "1468-2389",

publisher = "Wiley",

number = "1",

}

Scoring the Big Five for longitudinally assessed academic achievement predictiveness: Manifest, correlated-factors model, and bifactor modeling across multiple contexts. / Krammer, Georg; Schermer, Julie Aitken; Koschmieder, Corinna et al.
In: International Journal of Selection and Assessment, Vol. 33, No. 1, e12500, 2024.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Scoring the Big Five for longitudinally assessed academic achievement predictiveness: Manifest, correlated-factors model, and bifactor modeling across multiple contexts

AU - Krammer, Georg

AU - Schermer, Julie Aitken

AU - Koschmieder, Corinna

AU - Goffin, Richard

AU - Hendy, Nhung

PY - 2024

Y1 - 2024

UR - https://www.scopus.com/pages/publications/85205910049

U2 - 10.1111/ijsa.12500

DO - 10.1111/ijsa.12500

M3 - Article

SN - 1468-2389

VL - 33

JO - International Journal of Selection and Assessment

JF - International Journal of Selection and Assessment

IS - 1

M1 - e12500

ER -

Scoring the Big Five for longitudinally assessed academic achievement predictiveness: Manifest, correlated-factors model, and bifactor modeling across multiple contexts

Fields of science

UN SDGs

Access to Document

Other files and links

Cite this