DARK TRIAD, ONLINE ACADEMIC TECHNOLOGIES AND ACADEMIC FRAUD
DOI:
https://doi.org/10.13058/raep.2026.v27n1.2771Keywords:
Dark Triad, Academic technologies, Academic fraudAbstract
The creation of revolutionary artificial intelligence technologies that provide students with access, free or paid, to tools for performing academic activities is expanding. In this context, this study analyzes the influence of the Dark Triad traits on the use of academic technologies and academic fraud. To this end, we adopted the theoretical-empirical methodological approach of quantitative evaluation through descriptive statistics, exploratory factor analysis, structural equation modeling and multiple regression. The data were obtained from an online survey applied to 88 business students. The results showed that the Dark Triad personality traits influence the use of online academic technologies, which in turn is associated with academic fraud, with emphasis on narcissism and psychopathy. We also found that business administration students agree on how easy it is for people to take advantage of online assistance resources to carry out academic activities, and that those who have a tendency towards fraud use these technologies when they can. These findings encourage debate among leaders of educational institutions and business educators about actions aimed at reducing students' academic cheating, especially when they are endowed with Dark Triad traits.
Downloads
References
Ahadiat, N., & Gomaa, M. I., (2020). Online accounting education: How to improve security and integrity of students’ performance assessments. Journal of Instructional Pedagogies, 24, 1–14. https://files.eric.ed.gov/fulltext/EJ1263754.pdf
Avelino, B. C., & Lima, G. A. S. F, (2017). Narcissism and Academic Dishonesty. Revista Universo Contábil, 13(3), 58-76.
Barreto, A. M. P., Ávila, F. (2023). Artificial Intelligence in the face of scientific integrity: A study on the misuse of ChatGPT. Revista Direitos Culturais, 18 (45), 91-109. http://dx.doi.org/10.20912/rdc.v18i45.1373
Bashir, H., & Bala, R. (2018). Development and Validation of Academic Dishonesty Scale (ADS): Presenting a Multidimensional Scale. International Journal of Instruction, 11(2), 57-74. https://doi.org/10.12973/iji.2018.1125a
Becker, D. Connolly, J., Lentz, P., & Morrison, J. (2006). Using the business fraud triangle to predict academic dishonesty among business students. Academy of Educational Leadership Journal, 10(1), 37.
Carvalho, F.; & Pimentel, M. (2023). Study and learn with ChatGPT. Revista Educação e Cultura Contemporânea, 20, 1-21. Available at: https://www.researchgate.net/publication/376512760_Estudar_e_aprender_com_o_ChatGPT
Comas-Forgas, R., Lancaster, T., Calvo-Sastre, A., & Sureda-Negre, J. (2021). Exam cheating and academic integrity breaches during the COVID-19 pandemic: An analysis of internet search activity in Spain. Heliyon, 7(10), e08233. DOI: https://doi.org/10.1016/j.heliyon.2021.e08233
Cressey, D. R. (1953). Other people’s money: A study in the social psychology of embezzlement. Free Press.
D’Souza, M. F., & Lima, G. A. S. F. (2018). Career choice: the Dark Triad reveals the interests of accounting students. Journal of Accounting and Organizations, 12. https://doi.org/10.11606/issn.1982-6486.rco.2018.151837
Emerson, D. J., & Smith, K. J. (2022). Student use of homework assistance websites. Accounting Education, 31(3), 273–293. https://doi.org/10.1080/09639284.2021.1971095
Gouvêa, P. E. & Avanço, L. (2006). Ethics and accounting fraud. Journal of Legal and Business Sciences, 7(1), 85-91.
Gouveia, V. V., Monteiro, R. P., Gouveia, R. S. V., Athayde, R. A. A., & Cavalcanti, T. M. (2016). Assessing the dark side of personality: psychometric evidence from the Dark Triad Dirty Dozen. Interamerican Journal of Psychology, 50(3), 420-432.
Greitemeyer, T., & Kastenmüller, A. (2023). HEXACO, the Dark Triad, and Chat GPT: Who is willing to commit academic cheating?. Heliyon, 9(9).
Grossman, A. M., & Johnson, L. R. (2016). Employer perceptions of online accounting degrees. Issues in Accounting Education, 31(1), 91–109. https://doi.org/10.2308/iace-51229
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2009). Multivariate Data Analysis (6 ed.). Bookman.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate Data Analysis. Pearson Education.
Harrison, A., Summers, J., & Mennecke, B. (2018). The effects of the Dark Triad on unethical behavior. Journal of Business Ethics, 153(1), 53–77. https://doi.org/10.1007/s10551-016-3368-3
Jonason, P. K., & Webster, G. D. (2010). The dirty dozen: a concise measure of the dark triad. Psychological assessment, 22(2), 420. https://doi.org/10.1037/a0019265
Jones, D. N., & Paulhus, D. L. (2014). Introducing the short Dark Triad (SD3): a brief measure of dark personality traits. Assessment, 21(1), 28-41. https://doi.org/10.1177/1073191113514105.
Lancaster, T., & Cotarlan, C. (2021). Contract cheating by STEM students through a file sharing website: A Covid-19 pandemic perspective. International Journal for Educational Integrity, 17(1), 1–16. https://doi.org/10.1007/s40979-021-00070-0
Lima, J. (2023). How ChatGPT affects education and university development. Revista Técnica de Tendências em Comunicação Empresarial, 3, 1-9. https://doi.org/10.34630/tth.vi3.5020
McMurtry, K. (2001). E-cheating: Combating a 21st century challenge. Technological Horizons in Education Journal, 29(4), 36.
Oliveira, J. V., & Carvalho, M. J. L. (2022). Traces and portraits of the online press on the use of digital information and communication technologies as tools to support organized crime in Roraima, Brazil. Rev. Dir. Cid., 14(01), 457-493. https://doi.org/10.12957/rdc.2022.64723
Parks-Leduc, L., Guay, R. P., & Mulligan, L. M. (2021). The relationships between personal values, justifications, and academic cheating for business vs. non-business students. Journal of Academic Ethics. 10.1007/s10805-021-09427-z
Paulhus, D. L., & Williams, K. (2002). The Dark Triad of personality: narcissism, Machiavellianism, and psychopathy. Journal of Research in Personality, 36(6), 556-563. https://doi.org/10.1016/S0092-6566(02)00505-6
Phelan, J. (2020). Academic integrity in the age of online learning. Wiley. Accessed March 7, 2024. https://www.wiley.com/en-us/network/education/instructors/teach
Silva, D. S. M., Sé, E. V. G., Lima, V. V., Borim, F. S. A., Oliveira, M. S., & Padilha, R. Q.(2022). Metodologias ativas e tecnologias digitais na educação médica: novos desafios em tempos de pandemia. Revista Brasileira de Educação Médica, 46(2), 1-9, 2022. https://doi.org/10.1590/1981-5271v46.2-20210018.
Smith, K. J., Emerson, D. J., & Mauldin, S. (2021). Online cheating at the intersection of the dark triad and fraud diamond. Journal of Accounting Education, 57, 100753.
Smith, K., Emerson, D., Haight, T., & Wood, B. (2023). An examination of online cheating among business students through the lens of the Dark Triad and Fraud Diamond. Ethics & Behavior, 33(6), 433-460. https://doi.org/10.1080/10508422.2022.2104281
Staats S., Hupp, J. M., Wallace, H. & Gresley, J. (2009) Heroes Don't Cheat: An Examination of Academic Dishonesty and Students' Views on Why Professors Don't Report Cheating. Ethics & Behavior, 19(3), 171-183. https://doi.org/10.1080/10508420802623716
Walker, N., & Holtfreter, K. (2015). Applying criminological theory to academic fraud. Journal of Financial Crime, 22, 48-62. https://doi.org/10.1108/JFC-12-2013-0071
Wilson, M. S., & McCarthy, K. (2011). Greed is good? Student disciplinary choice and self-reported psychopathy. Personality and Individual Differences, 51(7), 873–876. https://doi.org/10.1016/j.paid.2011.07.028
Wolfe, D. T., & Hermanson D. R. (2004). The Fraud Diamond: Considering the Four Elements of Fraud. CPA Journal 74(12), 38-42.
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Márcia Figueredo D'Souza, Camila Viana Brasil, Elisio Marcos Reis
This work is licensed under a Creative Commons Attribution 4.0 International License.
By publishing a manuscript in the journal Administração: Ensino e Pesquisa (RAEP), the authors declare that the work is of their exclusive authorship and therefore assume full responsibility for its content. The authors grant RAEP a non-exclusive rights license to use the work in the following ways:
(1) Sell and / or distribute the work in hard copies or electronic format.
(2) Distribute parts of the work as a whole to promote the journal through the internet and other digital and printed media.
(3) Record and reproduce the work in any format, including digital media.
Authors and readers are permitted to share the material, use it in classes, for presentations and also for other purposes, and to create new knowledge based on any RAEP publication, as long as the due credit is attributed to the original work and the respective author(s), through citations, references, and other means.
The journal adopts preventive measures to identify plagiarism using software designed for this purpose.
RAEP does not charge authors for the article submission nor for the publishing of approved articles.
In line with the journal's policies, each published article will be given a Creative Commons CC-BY 4.0 license.
