Autonomy and Academic Dishonesty: Exploring the Mediating Role of Trust in ChatGPT
DOI:
https://doi.org/10.62843/jssr.v6i1.699Keywords:
Autonomy, Academic Dishonesty, Trust, ChatGPT, Artificial Intelligence, Researchers, Algorithms, PakistanAbstract
The integration of AI tools like ChatGPT in higher education has sparked worries about academic honesty and reliance on AI. The use of artificial intelligence (AI) tools like ChatGPT in educational settings has created concerns about academic integrity and dependency on AI. This research explored the relationship between autonomy and academic dishonesty as a mediator in the relationship between trust in ChatGPT. The research design used in this study was quantitative with a cross sectional design. Data were collected from 230 researchers working in educational institutes in Karachi and Islamabad, Pakistan through standardized questionnaires. The results show that there are strong positive correlations between academic dishonesty and autonomy (r = 0.98, p < .01), and between trust in ChatGPT and autonomy (r = 0.90, p < .01). Trust in ChatGPT is positively correlated with academic dishonesty (r = 0.95, p < 0.01) and partially mediated the relationship between autonomy and academic dishonesty. The results indicated that promoting independence and academic freedom might help curb academic dishonesty by minimizing excessive use of AI tools. The study emphasizes the need for self-directed learning and ethical utilization of AI in universities.
References
Abdaoui, M. (2018). Deterring Plagiarism In Higher Education: A model of integrity and autonomy in academic research. مجلة آفاق علمية, 374. https://doi.org/10.35554/1697-000-016-020
Akbulut, Y., Şendağ, S., Birinci, G., Kılıçer, K., Şahin, M. C., & Odabaşı, H. F. (2008). Exploring the types and reasons of Internet-triggered academic dishonesty among Turkish undergraduate students: Development of Internet-Triggered Academic Dishonesty Scale (ITADS). Computers & Education, 51(1), 463–473. https://doi.org/10.1016/j.compedu.2007.06.003
Bei, E., Mavroidis, I., & Giossos, Y. (2020). Development of a Scale for Measuring the Learner Autonomy of Distance Education Students. European Journal of Open, Distance and E-Learning, 22(2), 133–144. https://doi.org/10.2478/eurodl-2019-0015
Bolin, A. U. (2004). Self-Control, Perceived Opportunity, and Attitudes as Predictors of Academic Dishonesty. The Journal of Psychology, 138(2), 101–114. https://doi.org/10.3200/jrlp.138.2.101-114
D’Agostino, S. (2023). Academics work to detect ChatGPT and other AI writing. https://www.insidehighered.com/news/2023/01/20/academics-work-detect-chatgpt-and-other-ai-writing
Deng, J., & Lin, Y. (2023). The Benefits and Challenges of ChatGPT: An Overview. Frontiers in Computing and Intelligent Systems, 2(2), 81–83. https://doi.org/10.54097/fcis.v2i2.4465
Dowling, M., & Lucey, B. (2023). ChatGPT for (Finance) research: The Bananarama Conjecture. Finance Research Letters, 53, 103662. https://doi.org/10.1016/j.frl.2023.103662
Ellahi, A., Mushtaq, R., & Bashir Khan, M. (2013). Multi campus investigation of academic dishonesty in higher education of Pakistan. International Journal of Educational Management, 27(6), 647–666. https://doi.org/10.1108/ijem-03-2012-0039
Faucher, D., & Caves, S. (2009). Academic dishonesty: Innovative cheating techniques and the detection and prevention of them. Teaching and Learning in Nursing, 4(2), 37–41. https://doi.org/10.1016/j.teln.2008.09.003
Gao, C. A., Howard, F. M., Markov, N. S., Dyer, E. C., Ramesh, S., Luo, Y., & Pearson, A. T. (2022). Comparing scientific abstracts generated by ChatGPT to original abstracts using an artificial intelligence output detector, plagiarism detector, and blinded human reviewers. BioRxiv. https://doi.org/10.1101/2022.12.23.521610
Guerrero-Dib JG, Portales L, Heredia-Escorza Y (2020) Impact of academic integrity on workplace ethical behavior. International Journal for Educational Integrity 16(1) 1–18. https://doi.org/10.1007/s40979-020-0051
Gulati, S., Sousa, S., & Lamas, D. (2019). Design, development and evaluation of a human-computer trust scale. Behaviour & Information Technology, 38(10), 1004-1015. https://doi.org/10.1080/0144929X.2019.1656779
Ipek, Z. H., Gozum, A. C., Papadakis, S., & Kallogianakis, M. (2023). Educational applications of the ChatGPT AI system: A systematic review research. Educational Process: International Journal, 12(3), 26–55. https://doi.org/10.22521/edupij.2023.123.2
Irfan, A., Abbas, N., Shahid, M. S., Ashraf, J., & Asif, A. (2025). Smartphone addiction and academic procrastination in university students: psychological wellbeing as a moderator. Qualitative Research Journal for Social Studies, 2(2), 973-983. https://doi.org/10.63878/qrjs133
Khan, P., Shahid, M. S., & Majid, H. A. (2024). Mediating role of online social connectedness in smartphone addiction and online relationship among young adults. Gomal University Journal of Research, 40(3), 327-336. https://doi.org/10.51380/gujr-40-03-05
Khan, U. P. (2018). Academic dishonesty: A menace to the education system. Daily Times. https://dailytimes.com.pk/309482/academic-dishonesty-a-menace-to-the-education-system/
Krou, M. R., Fong, C. J., & Hoff, M. A. (2020b). Achievement Motivation and Academic Dishonesty: A Meta-Analytic Investigation. Educational Psychology Review. https://doi.org/10.1007/s10648-020-09557-7
Kusuma, A. N. (2022a). The state of self-regulated learning and academic dishonesty of undergraduate students during online learning. Psychological Research and Intervention, 5(1), 19–27. https://doi.org/10.21831/pri.v5i1.49441
Levine, J., & Pazdernik, V. (2018). Evaluation of a four-prong anti-plagiarism program and the incidence of plagiarism: a five-year retrospective study. Assessment & Evaluation in Higher Education, 43(7), 1094-1105. https://doi.org/10.1080/02602938.2018.1434127
McCabe, D. L., & Treviño, L. K. (1993). Academic dishonesty: honor codes and other contextual influences. The Journal of Higher Education, 64(5), 522. https://doi.org/10.2307/2959991
McCabe, D. L., & Treviño, L. K. (1997). Individual and Contextual Influences on Academic Dishonesty: a multicampus investigation. Research in Higher Education, 38(3), 379–396. https://doi.org/10.1023/a:1024954224675
McCabe, D. L., Treviño, L. K., & Butterfield, K. D. (2001). Cheating in academic institutions: A decade of research. Ethics &Behavior, 11(3), 219-232. https://doi.org/10.1207/S15327019EB1103_2
McKnight, D. H., & Chervany, N. L. (2001). Trust and distrust definitions: one bite at a time. In Lecture notes in computer science (pp. 27–54). https://doi.org/10.1007/3-540-45547-7_3
Motloba, P. D. (2018). Understanding of the principle of Autonomy (Part 1). South African Dental Journal, 73(6). https://doi.org/10.17159/2519-0105/2018/v73no5a7
Müller, V. C. (2020). Ethics of Artificial Intelligence and Robotics. ResearchGate. https://www.researchgate.net/publication/340435326_Ethics_of_Artificial_Intelligence_and_Robotics
Nazir, M. S., Aslam, M. S., & Nawaz, M. M. (2011). Can Demography Predict Academic Dishonest Behaviors of Students? A Case of Pakistan. International Education Studies, 4(2). https://doi.org/10.5539/ies.v4n2p208
Nazir, M., Pakistan, L., & Aslam, M. (2009). On The Relationship Of Demography And Academic Dishonest Behaviors Of Students. Semantic Scholar. https://www.semanticscholar.org/paper/On-The-Relationship-Of-Demography-And-Academic-Of-Nazir-Pakistan/5c5d76c3460ca893e8bda11635bae657822c2ec4
Roth, G., & Assor, A. (2012). The costs of parental pressure to express emotions: Conditional regard and autonomy support as predictors of emotion regulation and intimacy. Journal of Adolescence, 35(4), 799–808. https://doi.org/10.1016/j.adolescence.2011.11.005
Rudolph, J., Tan, S., & Tan, S. (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education? Journal of Applied Learning and Teaching, 6(1), 1-22. https://doi.org/10.37074/jalt.2023.6.1.9
Schraw, G., Olafson, L., Kuch, F., Lehman, T., Lehman, S., & McCrudden, M. T. (2007a, January 1). 4 - Interest and Academic Cheating (E. M. Anderman & T. B. Murdock, Eds.). ScienceDirect: Academic Press. https://www.sciencedirect.com/science/article/abs/pii/B978012372541750005X
Shahid, M. S., Bashir, S., & Fatima, S. (2024). Social media addiction and aggression in Pakistani young adults: Social connectedness as a moderator. Journal of Professional & Applied Psychology, 5(3), 424-433. https://doi.org/10.52053/jpap.v5i3.308
Shen, Y., Heacock, L., Elias, J., Hentel, K. D., Reig, B., Shih, G., & Moy, L. (2023). ChatGPT and other large language models are double-edged swords. Radiology, 230163. https://doi.org/10.1148/radiol.230163
Soenens, B., & Vansteenkiste, M. (2005). Antecedents and Outcomes of Self-Determination in 3 Life Domains: The Role of Parents’ and Teachers’ Autonomy Support. Journal of Youth and Adolescence, 34(6), 589–604. https://doi.org/10.1007/s10964-005-8948-y
Waldock, W. J., Lam, G., Baptista, A., Walls, R., & Sam, A. H. (2025). Which curriculum components do medical students find most helpful for evaluating AI outputs?. BMC Medical Education, 25(1), 195. https://doi.org/10.1186/s12909-025-06735-5
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Copyright in the Journal of Social Sciences Review is retained by the author(s). Authors also grant any third party the right to use the article freely as long as its integrity is maintained and its original authors, citation details and publisher are identified.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
JSSR's Editorial Board shares the vision of providing free access to information, education, and science for everyone, thus promoting its content through an OPEN ACCESS POLICY, fulfilling the DOAJ definition of open access. The JSSR adheres to an Open Access and Copyright Licensing Policy based on the belief that making research freely accessible to the public promotes greater global knowledge sharing.
The JSSR uses the Creative Commons Attribution-NonCommercial 4.0 International License. The authors who apply and publish in JSSR consent to abide by the copyright policy set out in the Creative Commons 4.0 license (Attribution-NonCommercial 4.0 International license).
- Copyright in the Journal of Social Sciences Review is retained by the author(s).
- Authors also grant any third party the right to use the article freely as long as its integrity is maintained and its original authors, citation details and publisher are identified.
While "By 'open access' to this literature, we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself."
