Hilliard, A;
Kazim, E;
Bitsakis, T;
Leutner, F;
(2022)
Measuring Personality through Images: Validating a Forced-Choice Image-Based Assessment of the Big Five Personality Traits.
Journal of Intelligence
, 10
(1)
, Article 12. 10.3390/jintelligence10010012.
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Abstract
Selection methods are commonly used in talent acquisition to predict future job performance and to find the best candidates, but questionnaire-based assessments can be lengthy and lead to candidate fatigue and poor engagement, affecting completion rates and producing poor data. Gamification can mitigate some of these issues through greater engagement and shorter testing times. One avenue of gamification is image-based tests. Although such assessments are starting to gain traction in personnel selection, few studies describing their validity and psychometric properties exist. The current study explores the potential of a five-minute, forced-choice, image-based assessment of the Big Five personality traits to be used in selection. Study 1 describes the creation of the image pairs and the selection of the 150 best-performing items based on a sample of 300 respondents. Study 2 describes the creation of machine-learning-based scoring algorithms and tests of their convergent and discriminate validity and adverse impact based on a sample of 431 respondents. All models showed good levels of convergent validity with the IPIP-NEO-120 (openness r =.71, conscientiousness r =.70, extraversion r =.78, agreeableness r =.60, and emotional stability r =.70) and were largely free from potential adverse impact. The implications for recruitment policy and practice and the need for further validation are discussed.
| Type: | Article |
|---|---|
| Title: | Measuring Personality through Images: Validating a Forced-Choice Image-Based Assessment of the Big Five Personality Traits |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3390/jintelligence10010012 |
| Publisher version: | https://doi.org/ 10.3390/jintelligence10010012 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third-party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| UCL classification: | UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science UCL > Provost and Vice Provost Offices > UCL BEAMS UCL |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10144488 |
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