Beyond exams: Investigating AI tool impact on student attitudes, ethical awareness, and academic dishonesty in online college assessments
Jocelyn H. Hua
Abstract
Academic dishonesty in higher education is a growing concern, exacerbated by the increasing use of AI tools in online assessments. This study investigates the relationship between AI tool dependence, ethical awareness, student attitudes, and academic dishonesty among college students. It also explores the moderating effects of demographic factors. Survey data from college students were analyzed using a Generalized Linear Model (GLM) framework for a thorough examination of the complex interplay between the variables while considering the moderating influence of age, gender, type of institution, and technological proficiency. The study reveals that AI tool dependence is prevalent among college students. While students generally hold positive attitudes toward academic integrity, there is variability in the intensity and nature of these attitudes. Moreover, ethical awareness appears limited, highlighting a potential gap between ethical beliefs and behavior. Surprisingly, there is a consistent pattern of positive attitudes toward academic dishonesty. However, these findings are not explored in-depth in this study. Importantly, neither ethical awareness nor student attitudes significantly mediate the relationship between AI tool dependence and academic dishonesty. Demographic factors do not appear to significantly moderate these relationships. In light of these findings, institutions are encouraged to explore the implementation of the AI Dependence Inclusive Course for Transparency Program (AIDICT). This specialized initiative, shaped by the study's insights, enhances ethical education and raises awareness of the ethical implications associated with AI tool usage.
Keywords
academic dishonesty, AI tool dependence, ethical awareness, online college assessments, student attitudes
Author information & Contribution
Jocelyn H. Hua. PhD. Kolehiyo ng Pantukan. Email: hua_jocelyn@yahoo.com
Disclosure statement
No potential conflict of interest was reported by the author(s).
Funding
This work was not supported by any funding.
Institutional Review Board Statement
Data and Materials Availability
The data supporting the findings of this study are available from the corresponding author upon reasonable request.
AI Declaration
Notes
Acknowledgement
References
Ababneh, K. I., Ahmed, K., & Dedousis, E. (2022). Predictors of cheating in online exams among business students during the Covid pandemic: Testing the theory of planned behavior. The International Journal of Management Education, 20(3), 100713. https://doi.org/10.1016/j.ijme.2022.100713
Adama, E.A., Graf, A., Adusei-Asante, K. et al. (2023). COVID-19 and alternative assessments in higher education: implications for academic integrity among nursing and social science students. Int J Educ Integr 19, 8. https://doi.org/10.1007/s40979-023-00129-0
Akgun, S., & Greenhow, C. (2021). Artificial Intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, 2(3), 431–440. https://doi.org/10.1007/s43681-021-00096-7
Al Hadithy Z. A., Al Lawati, A., Al-Zadjali, R., et al. (2023) Knowledge, Attitudes, and Perceptions of Artificial Intelligence in Healthcare Among Medical Students at Sultan Qaboos University. Cureus 15(9): e44887. doi:10.7759/cureus.44887
Alberola-Mulet, I., Iglesias-Martínez, M. J., & Lozano-Cabezas, I. (2021). Teachers’ beliefs about the role of Digital Educational Resources in Educational Practice: A qualitative study. Education Sciences, 11(5), 239. https://doi.org/10.3390/educsci11050239
Alguacil, M., Herranz-Zarzoso, N., Pernías, J.C. et al. (2023). Academic dishonesty and monitoring in online exams: a randomized field experiment. J Comput High Educ. https://doi.org/10.1007/s12528-023-09378-x
Alnajjar, H. A., & Abou Hashish, E. A. (2021). Academic ethical awareness and moral sensitivity of undergraduate nursing students: Assessment and influencing factors. SAGE Open Nursing, 7, 237796082110267. https://doi.org/10.1177/23779608211026715
Alzahrani, L. (2023). Analyzing students’ attitudes and behavior toward Artificial Intelligence Technologies in higher education. International Journal of Recent Technology and Engineering (IJRTE), 11(6), 65–73. https://doi.org/10.35940/ijrte.f7475.0311623
Asirit, L. L., Hua, J. H. & Mendoza, L. (2022). A closer look at neophyte teachers’ instructional competence: A phenomenological study. International Research Journal of Science, Technology, Education, and Management, 2(2).
Basken, P. (2020). Universities say student cheating exploding in Covid era. Time Higher Education
Bin-Nashwan, S.A., Sadallah, M., & Bouteraa, M. (2023). Use of ChatGPT in academia: Academic integrity hangs in the balance. Technology in Society, 75, 102370. https://doi.org/10.1016/j.techsoc.2023.102370
Birks, D. & Clare, J. (2023). Linking artificial intelligence facilitated academic misconduct to existing prevention frameworks. Int J Educ Integr 19, 20 (2023). https://doi.org/10.1007/s40979-023-00142-3
Borenstein, J., & Howard, A. (2020). Emerging challenges in AI and the need for AI Ethics Education. AI and Ethics, 1(1), 61–65. https://doi.org/10.1007/s43681-020-00002-7
Bubaš, G., & Čižmešija, A. (2023). A critical analysis of students’ cheating in online assessment in Higher Education: Post-covid-19 issues and challenges related to conversational artificial intelligence. 2023 46th MIPRO ICT and Electronics Convention (MIPRO). https://doi.org/10.23919/mipro57284.2023.10159826
Burkhard, M. (2022). Student perceptions of AI-powered writing tools: Towards Individualized Teaching Strategies. Proceeedings of the 19th International Conference on Cognition and Exploratory Learning in the Digital Age (CELDA 2022). https://doi.org/10.33965/celda2022_202207l010
Chami, G. (2023, October 22). Artificial Intelligence and academic integrity: Striking a balance. THE Campus Learn, Share, Connect. https://www.timeshighereducation.com/campus/artificial-intelligence-and-academic-integrity-striking-balance
Chan, C.K.Y. & Hu, W. (2023). Students’ voices on generative AI: perceptions, benefits, and challenges in higher education. Int J Educ Technol High Educ 20, 43 (2023). https://doi.org/10.1186/s41239-023-00411-8
Chang, L., Cerimagic, S. & Conejos, S. (2021). Challenges of running online exams and preventing academic dishonestyduring the Covid-19 pandemic. Journal of Learning Development in Higher Education, 22
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. https://doi.org/10.1016/j.heliyon.2021.e08233
Cotton, D., Cotton, P., & Shipway, J. R. (2023). Chatting and Cheating. Ensuring Academic Integrity in the Era of Chatgpt. https://doi.org/10.35542/osf.io/mrz8h
Curtis, G. J. (2022). Trends in plagiarism and cheating prevalence: 1990-2020 and beyond. In D. Rettinger, & T. Bertram Gallant (Eds.), Cheating academic integrity: Lessons from 30 years of research (1 ed., pp. 11-44). Jossey-Bass.
Curtis, G.J. & Tremayne, K. (2021). Is plagiarism really on the rise? Results from four 5-yearly surveys. Studies in Higher Education, 46:9, 1816-1826, DOI: 10.1080/03075079.2019.1707792
Davies, A., & Al sharefeen, R. (2022). Enhancing academic integrity in a UAE safety, security defence emergency management academy – the Covid- 19 response and beyond. Int J Educ Integr 18, 17. https://doi.org/10.1007/s40979-022-00110-3
Doumat, G., Daher, D., Ghanem, N.N. & Khater, B. (2022). Knowledge and attitudes of medical students in Lebanon toward artificial intelligence: A national survey study. Frontiers in Artificial Intelligence. 5:1015418. DOI: 10.3389/frai.2022.1015418.
Eaton, S. (2022). The Academic Integrity Technological Arms Race and its Impact on Learning, Teaching, and Assessment. Canadian Journal of Learning and Technology, 48(2). https://doi.org/10.21432/cjlt28388
Efetie, D. (2021). University faces dramatic increase in academic misconduct over the pandemic. The Commonwealth Times. https://commonwealthtimes.org/2021/09/15/university-faces-dramatic-increase-in-academic-misconduct-over-the-pandemic/
Eke, D.O. (2023). ChatGPT and the rise of generative AI: Threat to academic integrity? Journal of Responsible Technology, 13, 100060. https://doi.org/10.1016/j.jrt.2023.100060
Elkhatat, A.M. (2023). Evaluating the authenticity of ChatGPT responses: a study on text-matching capabilities. Int J Educ Integr 19, 15 (2023). https://doi.org/10.1007/s40979-023-00137-0
Elsalem, L., Al-Azzam, N., Jum’ah, A. & Obeidat, N. (2021). Remote E-exams during Covid-19 pandemic: A cross-sectional study of students’ preferences and academic dishonesty in faculties of medical sciences. Annals of Medicine and Surgery. 62, 326-333. https://doi.org/10.1016/j.amsu.2021.01.054
Erguvan, I.D. (2021). The rise of contract cheating during the COVID-19 pandemic: a qualitative study through the eyes of academics in Kuwait. Lang Test Asia 11, 34 (2021). https://doi.org/10.1186/s40468-021-00149-y
Foltynek, T., Bjelobaba, S., Glendinning, I. et al. (2023). ENAI Recommendations on the ethical use of Artificial Intelligence in Education. Int J Educ Integr 19, 12. https://doi.org/10.1007/s40979-023-00133-4
Fritsch, S.J., Blankenheim, A., Wahl, A., et al. (2022). Attitudes and perception of artificial intelligence in healthcare: A cross-sectional survey among patients. Digital Health. 8. doi:10.1177/20552076221116772
Gamage, K.A.A., Silva, E.K.d. & Gunawardhana, N. (2020). Online Delivery and Assessment during COVID-19: Safeguarding Academic Integrity. Education Sciences. 2020; 10(11):301. https://doi.org/10.3390/educsci10110301
García-Martínez, I., Fernández-Batanero, J. M., Fernández-Cerero, J., & León, S. P. (2023). Analysing the impact of Artificial Intelligence and Computational Sciences on Student Performance: Systematic Review and meta-analysis. Journal of New Approaches in Educational Research, 12(1), 171. https://doi.org/10.7821/naer.2023.1.1240
Ghotbi, N., & Ho, M. T. (2021). Moral Awareness of College Students Regarding Artificial Intelligence. Asian bioethics review, 13(4), 421–433. https://doi.org/10.1007/s41649-021-00182-2
Green, B. P. (2020, August 18). Artificial Intelligence and ethics: Sixteen challenges and opportunities. Markkula Center for Applied Ethics. https://www.scu.edu/ethics/all-about-ethics/artificial-intelligence-and-ethics-sixteen-challenges-and-opportunities/
Hayes, A. F. (2022). Introduction to mediation, moderation, and conditional process analysis, third edition: A regression-based approach. Guilford Press.
Hazra, U. & Priyo, A. (2022). Unethical practices in online classes during COVID-19 pandemic: an analysis of affordances using routine activity theory. Journal of Information, Communication & Ethics in Society, 20 (4), 546-567.
Holden, O. L., Norris, M. E., & Kuhlmeier, V. A. (2021). Academic integrity in online assessment: A research review. Frontiers in Education, 6. https://doi.org/10.3389/feduc.2021.639814
Hylton, K., Levy, Y., & Dringus, L. P. (2016). Utilizing webcam-based proctoring to deter misconduct in online exams. Computers & Education, 92–93, 53–63. https://doi.org/10.1016/j.compedu.2015.10.002
Ives, B., & Cazan, AM. (2023). Did the COVID-19 pandemic lead to an increase in academic misconduct in higher education? High Educ (2023). https://doi.org/10.1007/s10734-023-00996-z
Ivo, J. & Arnold, M. (2022). Online proctored assessment during COVID-19: Has cheating increased? The Journal of Economic Education, 53:4, 277-295, DOI: 10.1080/00220485.2022.2111384
Janke, S., Rudert, S.C. Petersen, A., Fritz, T.M. & Daumiller, M. (2021). Cheating in the wake of COVID-19: How dangerous is ad-hoc online testing for academic integrity? Computers and Education Open, 2, 100055. https://doi.org/10.1016/j.caeo.2021.100055
Jenkins, B. D., Golding, J. M., Le Grand, A. M., Levi, M. M., & Pals, A. M. (2023). When Opportunity Knocks: College Students’ Cheating Amid the COVID-19 Pandemic. Teaching of Psychology, 50(4), 407-419. https://doi.org/10.1177/00986283211059067
Kairu, C. (2020). Students’ Attitude Towards the Use of Artificial Intelligence and Machine Learning to Measure Classroom Engagement Activities. In Proceedings of EdMedia + Innovate Learning (pp. 793-802). Online, The Netherlands: Association for the Advancement of Computing in Education (AACE). Retrieved December 8, 2023 from https://www.learntechlib.org/primary/p/217382/.
Kelly, S., Kaye, S.-A., & Oviedo-Trespalacios, O. (2023). What factors contribute to the acceptance of artificial intelligence? A systematic review. Telematics and Informatics, 77, 101925. https://doi.org/10.1016/j.tele.2022.101925
Kleine, A. K., Kokje, E., Lermer, E., & Gaube, S. (2023). Attitudes Toward the Adoption of 2 Artificial Intelligence-Enabled Mental Health Tools Among Prospective Psychotherapists: Cross-sectional Study. JMIR human factors, 10, e46859. https://doi.org/10.2196/46859
Klimova, B., Pikhart, M., & Kacetl, J. (2023). Ethical issues of the use of AI-driven mobile apps for Education. Frontiers in Public Health, 10. https://doi.org/10.3389/fpubh.2022.1118116
Kooli, C. (2023). Chatbots in education and research: A critical examination of ethical implications and solutions. Sustainability, 15(7), 5614. https://doi.org/10.3390/su15075614
Kwak, Y., Ahn, J. W., & Seo, Y. H. (2022). Influence of AI ethics awareness, attitude, anxiety, and self-efficacy on nursing students’ behavioral intentions. BMC nursing, 21(1), 267. https://doi.org/10.1186/s12912-022-01048-0
Kwon, J. (2023). A Study on Ethical Awareness Changes and Education in Artificial Intelligence Society. Revue d’Intelligence Artificielle, 37 (2), 341-345. https://doi.org/10.18280/ria.370212
Liu, M., Ren, &., Nyagoga, L.M., Stonier, F., Wu, Z. & Yu, L. (2023). Future of education in the era of generative artificial intelligence: Consensus among Chinese scholars on applications of ChatGPT in schools. Future in Educational Research, 1(1), 72-101. https://doi.org/10.1002/fer3.10
Malik, A.A., Hassan, M., Rizwan, M., Mushtaque, I., Lak, T.A. & Hussain, M. (2023). Impact of academic cheating and perceived online learning effectiveness on academic performance during the COVID-19 pandemic among Pakistani students. Front. Psychol. 14:1124095. doi: 10.3389/fpsyg.2023.1124095
Maryon, T., Dubre, V., Elliott, K., Escareno, J., Fagan, M.H., Standridge, E., Lieneck, C. (2022). COVID-19 Academic Integrity Violations and Trends: A Rapid Review. Education Sciences. 12(12):901. https://doi.org/10.3390/educsci12120901
Marzuki, U.W., Rusdin, D., & Indrawati, I. (2023). The impact of AI writing tools on the content and organization of students’ writing: EFL teachers’ perspective, Cogent Education, 10:2, DOI: 10.1080/2331186X.2023.2236469
Mellar, H., Peytcheva-Forsyth, R., Kocdar, S. et al. (2018). Addressing cheating in e-assessment using student authentication and authorship checking systems: teachers’ perspectives. Int J Educ Integr 14, 2. https://doi.org/10.1007/s40979-018-0025-x
Mercer-Mapstone, L., Islam, M., & Reid, T. (2021). Are we just engaging ‘the usual suspects’? challenges in and practical strategies for supporting equity and Diversity in student–staff partnership initiatives. Teaching in Higher Education, 26(2), 227–245. https://doi.org/10.1080/13562517.2019.1655396
Münscher, S. (2022). The relationship between just world belief and wellbeing, cheating behaviors, and academic work behaviors during COVID 19 among university students. Sci Rep 12, 14328. https://doi.org/10.1038/s41598-022-18045-7
Newton, P.M., & Essex, K. (2023). How Common is Cheating in Online Exams and did it Increase During the COVID-19 Pandemic? A Systematic Review. J Acad Ethics (2023). https://doi.org/10.1007/s10805-023-09485-5
OECD. (2020). Remote Online Exams in Higher Education During the COVID-19 Crisis. OECD Publishing.
Oravec, J. (2023). Artificial Intelligence Implications for Academic Cheating: Expanding the Dimensions of Responsible Human-AI Collaboration with ChatGPT and Bard. Jl. of Interactive Learning Research, 34(2), 213-237
Perkins, M. (2023). Academic integrity considerations of AI large language models in the post-pandemic era: Chatgpt and beyond. Journal of University Teaching and Learning Practice, 20(2). https://doi.org/10.53761/1.20.02.07
Rodway, P. & Schepman, A. (2023). The impact of adopting AI educational technologies on projected course satisfaction in university students. Computers and Education: Artificial Intelligence. 5, 100150. https://doi.org/10.1016/j.caeai.2023.100150
Sabra, H.E., Elaal, H., Sobhy, K., & Bakr, M. (2023). Utilization of Artificial Intelligence in Health Care: Nursesꞌ Perspectives and Attitudes. MNJ, 8(1), 253 – 268
Sallam, M., Salim, N.A., Barakat, M., Al-Mahzoum, K., Al-Tammemi, A.B., Malaeb, D., Hallit, R., & Hallit, S. (2023). Assessing Health Students’ Attitudes and Usage of ChatGPT in Jordan: Validation Study. JMIR Med Educ, 9:e48254
doi: 10.2196/48254
San, S., Silivanh, S., & Phannalath, V. (2023). An investigation of academic dishonesty among undergraduates in four universities in Laos: Critical analysis of students’ final reports. International Journal of Multidisciplinary Research and Analysis, 06(03). https://doi.org/10.47191/ijmra/v6-i3-05
Schulz, P.J., Lwin, M.O., Kee, K.M., Goh, W.W.B., Lam, T.Y.T. & Sung, J.J.Y. (2023) Modeling the influence of attitudes, trust, and beliefs on endoscopists’ acceptance of artificial intelligence applications in medical practice. Front. Public Health. 11:1301563. doi: 10.3389/fpubh.2023.1301563
Scott, I.A., Carter, S.M., & Coiera, E. (2021). Exploring stakeholder attitudes towards AI in clinical practice. BMJ Health & Care Informatics 2021; 28:e100450. doi: 10.1136/bmjhci-2021-100450
Seo, K., Tang, J., Roll, I. et al. (2021). The impact of artificial intelligence on learner–instructor interaction in online learning. Int J Educ Technol High Educ 18, 54. https://doi.org/10.1186/s41239-021-00292-9
Shariffuddin, S.A., Ibrahim, I., Shaaidi, W., Syukor, F. & Hussain, J. (2022). Academic Dishonesty in Online Assessment from Tertiary Students’ Perspective. International Journal of Advanced Research in Education and Society, 4 (2), 75-84
Shih, P.K, Lin, C.H., Wu, L.Y. & Yu, C.C. (2021). Learning Ethics in AI—Teaching Non-Engineering Undergraduates through Situated Learning. Sustainability. 2021; 13(7):3718. https://doi.org/10.3390/su13073718
Siregar, F.H., Hasmayni, B. & Lubis, A.H. (2023). The Analysis of Chat GPT Usage Impact on Learning Motivation among Scout Students. International Journal of Research and Review, 10 (7)
Stoesz, B.M., Quesnel, M. & De Jaeger, A.E. (2023). Student perceptions of academic misconduct amongst their peers during the rapid transition to remote instruction. Int J Educ Integr 19, 14 (2023). https://doi.org/10.1007/s40979-023-00136-1
Sumakul, D.Y.G., Abdul Hamied, F. & Sukyadi, D. (2021). Students’ Perceptions of the Use of AI in a Writing Class. Advances in Social Science, Education and Humanities Research, volume 624 67th TEFLIN International Virtual Conference & the 9th ICOELT 2021 (TEFLIN ICOELT 2021)
Sweeney, S. (2023). Who wrote this? Essay mills and assessment – Considerations regarding contract cheating and AI in higher education. The International Journal of Management Education, 21(2), 100818. https://doi.org/10.1016/j.ijme.2023.100818
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425. https://doi.org/10.2307/30036540
Wahab, R. A., Mansor, N., Halid, S., & Rahman, R. A. (2022). The Impact of Covid-19 on Academic Dishonesty: Malaysian Evidence. International Journal of Academic Research in Accounting Finance and Management Sciences, 12(2), 176–185.
Yang, C., Chen, A., & Chen, Y. (2021). College students’ stress and health in the COVID-19 pandemic: The role of academic workload, separation from school, and fears of contagion. PLOS ONE, 16(2). https://doi.org/10.1371/journal.pone.0246676
Yazici, S., Durak, H.Y., Dunya, B.A. & Senturk, B. (2022). Online versus face-to-face cheating: The prevalence of cheating behaviours during the pandemic compared to the pre-pandemic among Turkish University students. Journal of Computer Assisted Learning, 39 (1), 231-254. https://doi.org/10.1111/jcal.12743
Yilmaz, R. & Yilmaz, F. (2023). The effect of generative artificial intelligence (AI)-based tool use on students’ computational thinking skills, programming self-efficacy and motivation. Computers and Education: Artificial Intelligence, 2(3), 100147. https://doi.org/10.1016/j.caeai.2023.100147
Zvereva, E. (2023). Digital Ethics in higher education: Modernizing moral values for effective communication in Cyberspace. Online Journal of Communication and Media Technologies, 13(2). https://doi.org/10.30935/ojcmt/13033
Cite this article:
Hua, J.H. (2023). Beyond exams: Investigating AI tool impact on student attitudes, ethical awareness, and academic dishonesty in online college assessments. International Journal of Educational Management and Development Studies, 4 (4), 160-185. https://doi.org/10.53378/353030
License:
This work is licensed under a Creative Commons Attribution (CC BY 4.0) International License.
Find this article in:
Most read articles
- A narrative exploration of romantic experiences and ideal relationship standards among Filipino Gen Z
- Students’ exposure to social media and their radical involvement on the societal issues in the Philippines
- Exploring the factors influencing commuters’ satisfaction and the use of public utility buses in Quezon City, Philippines
- Life-saving skills in the community: An assessment of basic life support and first aid knowledge in a selected barangay in the Philippines
- Decoding love signs: The role of perceived relational red flags in mate selection criteria among Filipino young adults
- Emotional intelligence and leadership efficacy of university student leaders
- Dress code policy adherence and self-discipline of university students
- A phenomenological study of online gambling behaviors among Filipino working professionals
- Filipino attitude and perception on Subscriber Identity Module (SIM) Card Registration Act
- Binge watching and mental well-being: Study on emerging adults