Liang, Haiying;
Mao, Xu;
Reiss, Michael J;
(2025)
Personality traits measured by the HEXACO personality inventory and the dark triad predict university students' attitudes and misconduct behaviors related to generative artificial intelligence.
Scientific Reports
, 15
, Article 41787. 10.1038/s41598-025-25744-4.
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Abstract
This study investigates how personality traits, specifically those measured by the HEXACO Personality Inventory and the Dark Triad, predict university students’ attitudes toward generative artificial intelligence (GAI) and their engagement in GAI-related academic misconduct. The first objective was to develop and validate a Chinese-language scale to measure students’ attitudes toward GAI in academic contexts. The newly developed GAI Attitudes Scale was tested for psychometric properties, showing high internal consistency (Cronbach’s α = 0.92) and reliability. In the second part of the study, hierarchical linear regression analyses explored the relationship between personality traits and both GAI attitudes and misconduct behaviors. Findings indicated that Extraversion and Openness to Experience were significant positive predictors of favorable GAI attitudes. Regarding misconduct behaviors, Honesty-Humility, Agreeableness, and Conscientiousness were significant negative predictors, while Narcissism and Psychopathy were significant positive predictors. Notably, GAI attitudes did not provide additional predictive value for misconduct beyond personality traits. Taken together, the findings demonstrate that personality traits are central to understanding both the adoption and misuse of GAI in academic contexts, providing important insights for fostering ethical engagement with emerging technologies.
| Type: | Article |
|---|---|
| Title: | Personality traits measured by the HEXACO personality inventory and the dark triad predict university students' attitudes and misconduct behaviors related to generative artificial intelligence |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1038/s41598-025-25744-4 |
| Publisher version: | https://doi.org/10.1038/s41598-025-25744-4 |
| Language: | English |
| Additional information: | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Curriculum, Pedagogy and Assessment |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10219613 |
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