The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
A Critical Analysis of Students’ Cheating in Online Assessment in Higher Education: Post-COVID-19 Issues and Challenges Related to Conversational Artificial Intelligence
Abstract
The latest advances in conversational artificial intelligence (CAI) systems that are available to the general public have intensified the debate on cheating in online assessment in higher education. The issue of cheating in online assessment in the educational context had already been given significant attention owing to school closures (lockdown periods) during the COVID-19 pandemic and the consequent transition from on-site to online teaching and assessment. In our paper we present statistical data on cheating in online courses and academic dishonesty in general, as well as an overview of motives for and methods of cheating reported in the literature, with a focus on the period of the COVID-19 pandemic. Recommendations are also provided regarding the use of specific techniques and tools to prevent cheating in online exams. Since plagiarism is an important problem in academic assessment the potential misuses of CAI in higher education are also briefly analyzed. This paper comprises a synthesis of related review papers and meta studies with reports of empirical research findings, as well as the experiences of the authors of the paper.
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
Traditional plagiarism detection tools, such as Turnitin, are ineffective in identifying AI-generated content, often yielding false positives or negatives.
“Studies have revealed that traditional plagiarism detection tools, such as Turnitin, are ineffective in identifying AI-gen -erated content, often yielding false positives or negatives [ 31, 60, 85, 89, 90 ].”
From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [85]
The use of multimodal assessment techniques, including project-based assessments, live problem-solving activities, and peer evaluations, has been identified as an effective strategy for fostering student accountability and reducing AI misuse.
“The use of multimodal assess -ment techniques, including project-based assessments, live problem-solving activities, and peer evaluations, has also been identified as an effective strategy for fostering student accountability and reducing AI misuse [ 85, 103 ].”
From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [85]
The ability to generate polished AI-driven responses has contributed to increasing submission of work that students do not create, undermining the authenticity of assessments.
“The ability to generate pol -ished AI-driven responses has also contributed to the increasing submission of work that students do not create, thus undermining the authenticity of assessments [ 68, 72, 85, 86].”
From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [85]
Citations
Cites
Chatting and cheating: Ensuring academic integrity in the era of ChatGPT
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024) · Innovations in Education and Teaching International · doi:10.1080/14703297.2023.2190148 · Cited by 3,087
Chatting and Cheating. Ensuring academic integrity in the era of ChatGPT
Cotton, D., Cotton, P., & Shipway, J. R. (2023) · doi:10.35542/osf.io/mrz8h · Cited by 3,079
Perkins, M. (2023) · Journal of University Teaching and Learning Practice · doi:10.53761/1.20.02.07 · Cited by 839
FACTORS ASSOCIATED WITH CHEATING AMONG COLLEGE STUDENTS: A Review
Whitley, B. E. (1998) · Research in Higher Education · doi:10.1023/a:1018724900565 · Cited by 782
Academic Integrity in Online Assessment: A Research Review
Holden, O. L., Norris, M. E., & Kuhlmeier, V. A. (2021) · Frontiers in Education · doi:10.3389/feduc.2021.639814 · Cited by 310 · cited 1×
“The study that is presented here presents a more contemporary analysis of research and addresses in more detail the period of the COVID-19 pandemic when compared to similar reviews of research papers published before the COVID-19 pandemic (i.e.: [37]).”
ResultA systematic review of research on cheating in online exams from 2010 to 2021
Noorbehbahani, F., Mohammadi, A., & Aminazadeh, M. (2022) · Education and Information Technologies · doi:10.1007/s10639-022-10927-7 · Cited by 236
When Opportunity Knocks: College Students' Cheating Amid the COVID-19 Pandemic
Jenkins, B. D., Golding, J. M., Le Grand, A. M., Levi, M. M., & Pals, A. M. (2023) · Teaching of Psychology · doi:10.1177/00986283211059067 · Cited by 85
Flagged first, then by citations
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Cited by
Sorted by citations
Ncube, P. D. N., Dzvapatsva, G. P., Matobobo, C., & Ranga, M. M. (2026) · AI and Ethics · doi:10.1007/s43681-025-00871-w · Cited by 31
“The use of multimodal assess - ment techniques, including project-based assessments, live problem-solving activities, and peer evaluations, has also been identified as an effective strategy for fostering student accountability and reducing AI misuse [ 85, 103 ].”
Metadata
- Authors
- Bubaš, G., & Čižmešija, A.
- Affiliations
- University of Zagreb (HR)
- Venue
- 2023 46th MIPRO ICT and Electronics Convention (MIPRO)
- Publisher
- IEEE
- Published
- 2023-05-22
- Pages
- 905-910
- OpenAlex
- W4382562204
- Cited by
- 10
- References
- 7
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 3 · 2023: 1
- FWCI
- 2.51
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Convention on Information and Communication Technology, Electronics and Microelectronics (publishedVersion)
- Topics
- Social Sciences › Education › Academic integrity and plagiarism
- Social Sciences › Education › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Keywords
- academic dishonesty, online assessment, conversational AI, online examinations, COVID-19 pandemic, plagiarism, cheating prevention, higher education, online learning
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