AI chatbots: A disguised enemy for academic integrity?
Open accessAbstract
The widespread popularity of ChatGPT and other AI chatbots has sparked debate within the scientific community, particularly regarding their impact on academic integrity among students. While several studies have examined AI's role in education, a significant gap remains concerning how AI chatbot usage affects students’ perceptions of academic integrity. This study aims to address this gap through rigorous quantitative techniques to explore the dynamics of student interactions with AI chatbots and assess whether this engagement diminishes academic integrity in higher education. Using a non-experimental design, the research investigates the causal relationship between AI chatbot usage and academic integrity, focusing on eight latent variables identified in the literature. A stratified sampling technique was employed to collect a representative sample of 594 participants via a 5-point Likert scale survey from four Southern Asian countries. The dataset underwent extensive statistical analysis using Structural Equation Modeling (SEM) techniques. The findings establish significant links between motivations for using AI chatbots and a decline in academic integrity. The study identifies a behavioral link between academic integrity and pedagogical limitations, highlighting traditional classroom-based pedagogy as the most impactful factor influencing students’ motivation to engage with AI chatbots. This research not only quantitatively addresses ethical concerns related to AI in academia but also offers insights into user behavior by assigning distinct weights to post-usage behavioral factors, differentiating it from earlier studies that treated these factors equally.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Oral examinations create opportunities for real-time interaction and spontaneous reasoning, making them resistant to AI impersonation.
“Oral examinations, meanwhile, create opportunities for real-time interaction and spontaneous reasoning, making them resistant to AI impersonation (Aladsani, 2025; Niloy et al., 2024; Ou et al., 2024).”
From Six Institutional Intervention Areas to Support Ethical and Effective Student Use of Generative AI in Higher Education: A Narrative Review (2026) · cites this paper as Niloy et al., 2024
Cites
Statistical Power Analysis for the Behavioral Sciences
Cohen, J. (2013) · doi:10.4324/9780203771587 · Cited by 25,373 · see citing works
A primer on partial least squares structural equation modeling (PLS-SEM)
Leguina, A. (2015) · International Journal of Research & Method in Education · doi:10.1080/1743727x.2015.1005806 · Cited by 18,921 · see citing works
Structural equation models with unobservable variables and measurement error: Algebra and statistics
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800313 · Cited by 13,287 · see citing works
I.—COMPUTING MACHINERY AND INTELLIGENCE
TURING, A. M. (1950) · Mind · doi:10.1093/mind/lix.236.433 · Cited by 10,290 · see citing works
On computable numbers, with an application to the entscheidungsproblem
Turing, A. M. (1937) · Proceedings of the London Mathematical Society · doi:10.1112/plms/s2-42.1.230 · Cited by 8,283 · see citing works
ChatGPT for good? On opportunities and challenges of large language models for education
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · Learning and Individual Differences · doi:10.1016/j.lindif.2023.102274 · Cited by 7,326 · see citing works
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021) · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3442188.3445922 · Cited by 6,988 · see citing works
Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepaño, C., Madriaga, M., Aggabao, R., Diaz-Candido, G., Maningo, J., et al. (2023) · PLOS Digital Health · doi:10.1371/journal.pdig.0000198 · Cited by 4,115 · see citing works
Baidoo-Anu, D., & Owusu Ansah, L. (2023) · doi:10.2139/ssrn.4337484 · Cited by 3,004 · see citing works
Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems
Mark, G., Fussell, S. R., Lampe, C., Schraefel, M., Hourcade, J., Appert, C., & Wigdor, D. J. (2017) · International Conference on Human Factors in Computing Systems · doi:10.1145/3025453 · Cited by 2,222 · see citing works
Exploring the impact of artificial intelligence on teaching and learning in higher education
Popenici, S. A. D., & Kerr, S. (2017) · Research and Practice in Technology Enhanced Learning · doi:10.1186/s41039-017-0062-8 · Cited by 2,019 · see citing works
What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023) · Smart Learning Environments · doi:10.1186/s40561-023-00237-x · Cited by 2,003 · see citing works
Lowry, P. B., & Gaskin, J. (2014) · IEEE Transactions on Professional Communication · doi:10.1109/tpc.2014.2312452 · Cited by 1,901 · see citing works
ChatGPT: five priorities for research
van Dis, E. A. M., Bollen, J., Zuidema, W., van Rooij, R., & Bockting, C. L. (2023) · Nature · doi:10.1038/d41586-023-00288-7 · Cited by 1,842 · see citing works
BAİDOO-ANU, D., & OWUSU ANSAH, L. (2023) · Journal of AI · doi:10.61969/jai.1337500 · Cited by 1,826 · see citing works
A SWOT analysis of ChatGPT: Implications for educational practice and research
Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2024) · Innovations in Education and Teaching International · doi:10.1080/14703297.2023.2195846 · Cited by 1,384 · see citing works
Chatting about ChatGPT: how may AI and GPT impact academia and libraries?
Lund, B. D., & Wang, T. (2023) · Library Hi Tech News · doi:10.1108/lhtn-01-2023-0009 · Cited by 1,355 · see citing works
Examining Science Education in ChatGPT: An Exploratory Study of Generative Artificial Intelligence
Cooper, G. (2023) · Journal of Science Education and Technology · doi:10.1007/s10956-023-10039-y · Cited by 1,263 · see citing works
Cascella, M., Montomoli, J., Bellini, V., & Bignami, E. (2023) · Journal of Medical Systems · doi:10.1007/s10916-023-01925-4 · Cited by 1,120 · see citing works
Gao, C. A., Howard, F. M., Markov, N. S., Dyer, E. C., Ramesh, S., Luo, Y., & Pearson, A. T. (2023) · npj Digital Medicine · doi:10.1038/s41746-023-00819-6 · Cited by 1,099 · see citing works
ChatGPT for Education and Research: Opportunities, Threats, and Strategies
Rahman, M. M., & Watanobe, Y. (2023) · Applied Sciences · doi:10.3390/app13095783 · Cited by 1,080 · see citing works
Self-citationChatbots and Conversational Agents in Mental Health: A Review of the Psychiatric Landscape
Vaidyam, A. N., Wisniewski, H., Halamka, J. D., Kashavan, M. S., & Torous, J. B. (2019) · The Canadian Journal of Psychiatry · doi:10.1177/0706743719828977 · Cited by 1,048 · see citing works
ChatGPT and other large language models are double-edged swords
Shen, Y., Heacock, L., Elias, J., Hentel, K. D., Reig, B., Shih, G., & Moy, L. (2023) · Radiology · doi:10.1148/radiol.230163 · Cited by 1,008 · see citing works
ChatGPT User Experience: Implications for Education
Zhai, X. (2023) · doi:10.2139/ssrn.4312418 · Cited by 935 · see citing works
Ouyang, F., Zheng, L., & Jiao, P. (2022) · Education and Information Technologies · doi:10.1007/s10639-022-10925-9 · Cited by 831 · see citing works
Strzelecki, A. (2024) · Interactive Learning Environments · doi:10.1080/10494820.2023.2209881 · Cited by 807 · see citing works
Chatbots for learning: A review of educational chatbots for the Facebook Messenger
Smutny, P., & Schreiberova, P. (2020) · Computers & Education · doi:10.1016/j.compedu.2020.103862 · Cited by 770 · see citing works
Chatbots in Education and Research: A Critical Examination of Ethical Implications and Solutions
Kooli, C. (2023) · Sustainability · doi:10.3390/su15075614 · Cited by 666 · see citing works
ChatGPT for (Finance) research: The Bananarama Conjecture
Dowling, M., & Lucey, B. M. (2023) · Finance research letters · doi:10.1016/j.frl.2023.103662 · Cited by 611 · see citing works
Tools such as ChatGPT threaten transparent science; here are our ground rules for their use
(2023) · Nature · doi:10.1038/d41586-023-00191-1 · Cited by 605 · see citing works
A Conversation on Artificial Intelligence, Chatbots, and Plagiarism in Higher Education
King, M. R., & chatGPT (2023) · Cellular and Molecular Bioengineering · doi:10.1007/s12195-022-00754-8 · Cited by 602 · see citing works
A New Chatbot for Customer Service on Social Media
Xu, A., Liu, Z., Guo, Y., Sinha, V. S., & Akkiraju, R. (2017) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3025453.3025496 · Cited by 589 · see citing works
Unleashing the Potential of Chatbots in Education: A State-Of-The-Art Analysis
Winkler, R., & Soellner, M. (2018) · Academy of Management Proceedings · doi:10.5465/ambpp.2018.15903abstract · Cited by 581 · see citing works
Are We There Yet? - A Systematic Literature Review on Chatbots in Education
Wollny, S., Schneider, J., Di Mitri, D., Weidlich, J., Rittberger, M., & Drachsler, H. (2021) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2021.654924 · Cited by 557 · see citing works
AI bot ChatGPT writes smart essays — should professors worry?
Stokel-Walker, C. (2022) · Nature · doi:10.1038/d41586-022-04397-7 · Cited by 543 · see citing works
ChatGPT and the rise of generative AI: Threat to academic integrity?
Eke, D. O. (2023) · Journal of Responsible Technology · doi:10.1016/j.jrt.2023.100060 · Cited by 532 · see citing works
Impact of the Implementation of ChatGPT in Education: A Systematic Review
Montenegro-Rueda, M., Fernández-Cerero, J., Fernández-Batanero, J. M., & López-Meneses, E. (2023) · Computers · doi:10.3390/computers12080153 · Cited by 509 · see citing works
Rediscovering the use of chatbots in education: A systematic literature review
Pérez, J. Q., Daradoumis, T., & Puig, J. M. M. (2020) · Computer Applications in Engineering Education · doi:10.1002/cae.22326 · Cited by 483 · see citing works
Transformative Effects of ChatGPT on Modern Education: Emerging Era of AI Chatbots
Gill, S. S., Xu, M.-X., Patros, P., Wu, H.-M., Kaur, R., Kaur, K., Fuller, S., Singh, M., Arora, P., Parlikad, A., et al. (2023) · Internet Things Cyber Phys. Syst. · doi:10.1016/j.iotcps.2023.06.002 · Cited by 466 · see citing works
The Robots Are Coming: Exploring the Implications of OpenAI Codex on Introductory Programming
Finnie-Ansley, J., Denny, P., Becker, B. A., Luxton-Reilly, A., & Prather, J. (2022) · Proceedings of the 24th Australasian Computing Education Conference · doi:10.1145/3511861.3511863 · Cited by 463 · see citing works
Yu, H. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1181712 · Cited by 409 · see citing works
Steenbergen-Hu, S., & Cooper, H. (2014) · Journal of Educational Psychology · doi:10.1037/a0034752 · Cited by 355 · see citing works
Lim, Z. W., Pushpanathan, K., Yew, S. M. E., Lai, Y., Sun, C., Lam, J. S. H., Chen, D. Z., Goh, J. H. L., Tan, M. C. J., Sheng, B., et al. (2023) · EBioMedicine · doi:10.1016/j.ebiom.2023.104770 · Cited by 316 · see citing works
ChatGPT: Fundamentals, Applications and Social Impacts
Abdullah, M., Madain, A., & Jararweh, Y. (2022) · 2022 Ninth International Conference on Social Networks Analysis, Management and Security (SNAMS) · doi:10.1109/snams58071.2022.10062688 · Cited by 310 · see citing works
Study and Analysis of Chat GPT and its Impact on Different Fields of Study
Kalla, D., Smith, N., Kuraku, S., & Samaah, F. (2023) · International Journal of Innovative Science and Research Technology (IJISRT) · doi:10.5281/zenodo.7767674 · Cited by 293 · see citing works
Newton, P. M. (2018) · Frontiers in Education · doi:10.3389/feduc.2018.00067 · Cited by 289 · see citing works
Feedback sources in essay writing: peer-generated or AI-generated feedback?
Banihashem, S. K., Kerman, N. T., Noroozi, O., Moon, J., & Drachsler, H. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00455-4 · Cited by 282 · see citing works
A novel measure of effect size for mediation analysis
Lachowicz, M. J., Preacher, K. J., & Kelley, K. (2018) · Psychological Methods · doi:10.1037/met0000165 · Cited by 271 · see citing works
Engineering Education in the Era of ChatGPT: Promise and Pitfalls of Generative AI for Education
Qadir, J. (2022) · doi:10.36227/techrxiv.21789434.v1 · Cited by 264 · see citing works
GPT-4 is here: what scientists think
Sanderson, K. (2023) · Nature · doi:10.1038/d41586-023-00816-5 · Cited by 262 · see citing works
Conversational AI: The Science Behind the Alexa PrizePreprint
Ram, A., Prasad, R., Khatri, C., Venkatesh, A., Gabriel, R., Liu, Q., Nunn, J., Hedayatnia, B., Cheng, M., Nagar, A., et al. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1801.03604 · Cited by 261 · see citing works
Strzelecki, A., & ElArabawy, S. (2024) · British Journal of Educational Technology · doi:10.1111/bjet.13425 · Cited by 260 · see citing works
Empowering learners for the age of artificial intelligence
Gašević, D., Siemens, G., & Sadiq, S. (2023) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2023.100130 · Cited by 234 · see citing works
Gravel, J., D’Amours-Gravel, M., & Osmanlliu, E. (2023) · Mayo Clinic Proceedings: Digital Health · doi:10.1016/j.mcpdig.2023.05.004 · Cited by 222 · see citing works
Wang, X., Pang, H., Wallace, M. P., Wang, Q., & Chen, W. (2022) · Computer Assisted Language Learning · doi:10.1080/09588221.2022.2056203 · Cited by 214 · see citing works
The Social life of AI in Education
Williamson, B. (2023) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-023-00342-5 · Cited by 213 · see citing works
Budhathoki, T., Zirar, A., Njoya, E. T., & Timsina, A. (2024) · Studies in Higher Education · doi:10.1080/03075079.2024.2333937 · Cited by 210 · see citing works
Homolak, J. (2023) · Croatian Medical Journal · doi:10.3325/cmj.2023.64.1 · Cited by 208 · see citing works
Fine-tuning ChatGPT for automatic scoring
Latif, E., & Zhaı, X. (2024) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2024.100210 · Cited by 186 · see citing works
HS Kumar, A. (2023) · Biology, Engineering, Medicine and Science Reports · doi:10.5530/bems.9.1.5 · Cited by 165 · see citing works
Generative AI in Education: Pedagogical, Theoretical, and Methodological Perspectives
Noroozi, O., Soleimani, S., Farrokhnia, M., & Banihashem, S. K. (2024) · International Journal of Technology in Education · doi:10.46328/ijte.845 · Cited by 165 · see citing works
Chan, A. (2023) · AI and Ethics · doi:10.1007/s43681-022-00148-6 · Cited by 155 · see citing works
Gökçearslan, Ş., Tosun, C., & Erdemir, Z. G. (2024) · International Journal of Technology in Education · doi:10.46328/ijte.600 · Cited by 144 · see citing works
ChatGPT: Future Directions and Open possibilities
Aljanabi, M. (2023) · Mesopotamian Journal of CyberSecurity · doi:10.58496/mjcs/2023/003 · Cited by 143 · see citing works
Is Chat Gpt biased against conservatives? An empirical study
McGee, R. W. (2023) · doi:10.2139/ssrn.4359405 · Cited by 141 · see citing works
Lai, C. Y., Cheung, K. Y., Chan, C. S., & Law, K. K. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100246 · Cited by 122 · see citing works
Mohamed, A. M., Shaaban, T. S., Bakry, S. H., Guillén-Gámez, F. D., & Strzelecki, A. (2025) · Innovative Higher Education · doi:10.1007/s10755-024-09747-z · Cited by 115 · see citing works
Plagiarism in the Context of Education and Evolving Detection Strategies
Gasparyan, A. Y., Nurmashev, B., Seksenbayev, B., Trukhachev, V. I., Kostyukova, E. I., & Kitas, G. D. (2017) · Journal of Korean Medical Science · doi:10.3346/jkms.2017.32.8.1220 · Cited by 114 · see citing works
Zemčík, T. (2019) · DEStech Transactions on Computer Science and Engineering · doi:10.12783/dtcse/aicae2019/31439 · Cited by 112 · see citing works
Social Constructivism—Jerome Bruner
Rannikmäe, M., Holbrook, J., & Soobard, R. (2020) · Springer Texts in Education · doi:10.1007/978-3-030-43620-9_18 · Cited by 105 · see citing works
Why do students use ChatGPT? Answering through a triangulation approach
Niloy, A. C., Bari, M. A., Sultana, J., Chowdhury, R., Raisa, F. M., Islam, A., Mahmud, S., Jahan, I., Sarkar, M., Akter, S., et al. (2024) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2024.100208 · Cited by 104 · see citing works
Self-citationPerceptions of Higher Education Students towards ChatGPT Usage
Das, S. R., & Madhusudan, J. V. (2024) · International Journal of Technology in Education · doi:10.46328/ijte.583 · Cited by 103 · see citing works
Gupta, A. (2020) · International Journal of Engineering Research and · doi:10.17577/ijertv9is070143 · Cited by 92 · see citing works
Role of AI in Blended Learning: A Systematic Literature Review
Park, Y., & Doo, M. Y. (2024) · The International Review of Research in Open and Distributed Learning · doi:10.19173/irrodl.v25i1.7566 · Cited by 81 · see citing works
The impact of AI in physics education: a comprehensive review from GCSE to university levels
Yeadon, W., & Hardy, T. (2024) · Physics Education · doi:10.1088/1361-6552/ad1fa2 · Cited by 80 · see citing works
ChatGPT has Mastered the Principles of Economics: Now What?Preprint
Geerling, W., Mateer, G. D., Wooten, J., & Damodaran, N. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4356034 · Cited by 75 · see citing works
Does perception mean learning? Insights from an online peer feedback setting
Noroozi, O., Alqassab, M., Kerman, N. T., Banihashem, S. K., & Panadero, E. (2024) · Assessment & Evaluation in Higher Education · doi:10.1080/02602938.2024.2345669 · Cited by 73 · see citing works
Institutionalizing ethics in AI through broader impact requirements
Prunkl, C., Ashurst, C., Anderljung, M., Webb, H., Leike, J., & Dafoe, A. (2021) · Nature Machine Intelligence · doi:10.1038/s42256-021-00298-y · Cited by 69 · see citing works
Jiang, Y., Hao, J., Fauss, M., & Li, C. (2024) · Computers & Education · doi:10.1016/j.compedu.2024.105070 · Cited by 68 · see citing works
Sevnarayan, K., & Potter, M.-A. (2024) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2024.7.1.41 · Cited by 64 · see citing works
Strengths, Weaknesses, Opportunities, and Threats of Using ChatGPT in Scientific Research
Giray, L., Jacob, J., & Gumalin, D. L. (2024) · International Journal of Technology in Education · doi:10.46328/ijte.618 · Cited by 58 · see citing works
Pérez-Marín, D. (2021) · Digital · doi:10.3390/digital1010002 · Cited by 57 · see citing works
Hobert, S., & von Wolff, R. M. (2019) · Journal of the Association for Information Systems · Cited by 56 · see citing works
Arthur, F., Salifu, I., & Nortey, S. A. (2024) · Interactive Learning Environments · doi:10.1080/10494820.2024.2362805 · Cited by 50 · see citing works
Proceedings of the 25th Australasian Computing Education Conference
(2023) · doi:10.1145/3576123 · Cited by 48 · see citing works
Garg, M., & Goel, A. (2021) · Computers & security · doi:10.1016/j.cose.2021.102544 · Cited by 47 · see citing works
A Bibliometric Analysis of Research on ChatGPT in Education
Polat, H., Topuz, A. C., Yıldız, M., Taşlıbeyaz, E., & Kurşun, E. (2024) · International Journal of Technology in Education · doi:10.46328/ijte.606 · Cited by 47 · see citing works
How Are You, Chatbot? Evaluating Chatbots in Educational Settings - Results of a Literature Review
Hobert, S. (2019) · Fachtagung "e-Learning" der Gesellschaft für Informatik · doi:10.18420/delfi2019_289 · Cited by 44 · see citing works
Mind meets machine: Unravelling GPT-4’s cognitive psychology
Dhingra, S., Singh, M., Vaisakh, S. B., Malviya, N., & Gill, S. S. (2023) · BenchCouncil Transactions on Benchmarks Standards and Evaluations · doi:10.1016/j.tbench.2023.100139 · Cited by 43 · see citing works
A Discussion about the Impact of ChatGPT in Education: Benefits and Concerns
Alves de Castro, C. (2023) · Journal of Business Theory and Practice · doi:10.22158/jbtp.v11n2p28 · Cited by 35 · see citing works
Farahat, A. M. (2022) · International Journal for Educational Integrity · doi:10.1007/s40979-021-00095-5 · Cited by 33 · see citing works
Cristianini, N. (2016) · The New Scientist · doi:10.1016/s0262-4079(16)31992-3 · Cited by 32 · see citing works
Why We Teach Science (and Why We Should)
Rudolph, J. L. (2023) · doi:10.1093/oso/9780192867193.001.0001 · Cited by 32 · see citing works
de Souza, B. C., Neto, A. S. D. A., & Roazzi, A. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4412505 · Cited by 27 · see citing works
Rane, N., Choudhary, S., & Rane, J. (2024) · Studies in Economics and Business Relations · doi:10.48185/sebr.v5i1.1051 · Cited by 25 · see citing works
Sobaih, A. E. (2024) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2024.7.1.21 · Cited by 23 · see citing works
Generative AI for Education (GAIED): Advances, Opportunities, and ChallengesPreprint
Denny, P. C., Gulwani, S., Heffernan, N. T., Käser, T., Moore, S., Rafferty, A. N., & Singla, A. K. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2402.01580 · Cited by 23 · see citing works
Mardiansyah, K., & Surya, W. (2024) · Research Square · doi:10.21203/rs.3.rs-4005702/v1 · Cited by 23 · see citing works
Do MOOCs Pose a Threat to Higher Education
Finkle, T. A., & Masters, E. (2014) · Research in higher education journal · Cited by 20 · see citing works
Jung, H., Lee, J.-J., & Park, C. (2020) · Journal of Digital Contents Society · doi:10.9728/dcs.2020.21.3.487 · Cited by 19 · see citing works
Rethinking Computer Science Through AI
Kersting, K. (2020) · Künstliche Intell. · doi:10.1007/s13218-020-00692-5 · Cited by 18 · see citing works
The Hermeneutics of Computer-Generated Texts
Henrickson, L., & Meroño-Peñuela, A. (2022) · Configurations · doi:10.1353/con.2022.0008 · Cited by 17 · see citing works
Use of Laptops and Other Technology in the Classroom
Spies, A. R., Kjos, A. L., Miesner, A. R., Chesnut, R. J., Fink, J. L., D'Antonio, N., & Russo‐Alvarez, G. (2010) · American Journal of Pharmaceutical Education · doi:10.5688/aj7408152 · Cited by 16 · see citing works
My AI students: Evaluating the proficiency of three AI chatbots in completeness and accuracy
Govender, R. G. (2024) · Contemporary Educational Technology · doi:10.30935/cedtech/14564 · Cited by 15 · see citing works
Thinking Responsibly About Responsible AI in Risk Management: The Darkside of AI in RM
Metwally, A. B. M., Ali, S. A. M., & Mohamed, A. T. I. (2024) · ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS) · doi:10.1109/icetsis61505.2024.10459684 · Cited by 14 · see citing works
Sun, D. (2023) · Food and Bioprocess Technology · doi:10.1007/s11947-023-03046-9 · Cited by 7 · see citing works
ChatGPT vsPreprint
Ahmed, I., Kajol, M. A., Hasan, U., & Datta, P. P. (2023) · doi:10.36227/techrxiv.23536290.v1 · Cited by 6 · see citing works
Vyas, S. D. (2018) · Library Herald · doi:10.5958/0976-2469.2018.00037.4 · Cited by 3 · see citing works
Flagged first, then by citations
2 of the 112 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Balaskas, S., Tsiantos, V., Chatzifotiou, S., & Rigou, M. (2025) · Information · doi:10.3390/info16020082 · Cited by 81 · see citing works
Khan, S. M. F. A., & Suhluli, S. A. (2025) · Technologies · doi:10.3390/technologies13110486 · Cited by 38 · see citing works
Jayasinghe, S., Gamage, K. A. A., Yang, D., Cheng, C., Disanayake, C., & Apeji, U. D. (2026) · Education Sciences · doi:10.3390/educsci16010137 · Cited by 23 · see citing works
Can generative AI Be an effective Co-Teacher? An experiment
Niloy, A. C., Akter, S., Sultana, J., Rahman, M. A., Sultana, N., Islam, T., Isha, N. J., Afroz, M., Zabeen, M., Tabassum, M., et al. (2025) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2025.100418 · Cited by 15 · see citing works
Self-citationHow University students in Bangladesh engage with ChatGPT: A qualitative study
Hasib, M., & Islam, M. S. (2025) · PLoS ONE · doi:10.1371/journal.pone.0333089 · Cited by 14 · see citing works
Tao, Y., & Shen, Q. (2025) · PLoS ONE · doi:10.1371/journal.pone.0334331 · Cited by 7 · see citing works
GPTs and the Choice Architecture of Pedagogies in Vocational Education
Scott, H., & Dwight, A. (2025) · Systems · doi:10.3390/systems13100872 · Cited by 4 · see citing works
Yin, J., Yuan, T., Zhang, Y., Yang, G., & Wang, X. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1735465 · Cited by 5 · see citing works
Nahiyan, S., & Rahman, A. G. (2026) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2026.102729 · Cited by 3 · see citing works
Uddın, M. M. (2025) · Discover Education · doi:10.1007/s44217-025-00805-y · Cited by 1 · see citing works
Integration of Artificial Intelligence in Blended Business Education
Berraies, S., & Rejeb, W. B. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-3815-6.ch008 · Cited by 1 · see citing works
Tan, J. W. D., Oh, H. X., Krishnan, V., Neo, A. W. M., Mohamed, I. N., Mohamed, R. M. P., Chowdhury, M. E. H., & Kumar, J. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1750324 · Cited by 1 · see citing works
Balamurugan, A. (2025) · International Journal for Research in Applied Science and Engineering Technology · doi:10.22214/ijraset.2025.72748
Senior High School Students’ Behavioral Intent, Usage, and Misuse of Generative AI in Learning
Tutor, B. O. D., Bernardo, L. M. A., Tadique, J. M. V., Pontanar, M. C. T., Pangilinan, J. B., & Butial, R. M. (2025) · International Conference on Distance Education and Learning (ICDEL) · doi:10.1109/icdel65868.2025.11193475
Use and Misuse of ChatGPT Among Tertiary-Level Students
Tutor, B. O. D., Jimenez, A. S., Villamin, A. A., Justiniani, M. V., Olarte, M. L., & Lirio, E. J. D. (2026) · Lecture notes in educational technology · doi:10.1007/978-981-95-2521-8_15
Augmented Instructors and Students
Berraies, S., Rejeb, W. B., & Abidine, S. Z. E. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-4377-8.ch006
Locally Hosted DeepSeek and Llama3.2 Code Generation and Computer Science Pedagogy
Wolfer, J. (2025) · Experiment@International Conference · doi:10.1109/exp.at2565440.2025.11348352
Artificial Intelligence in Economics Education: A Case Study from TürkiyePreprint
Garan, Ö., & Balın, B. E. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5343602
Redefining Academic Integrity in the Age of AI
Reginio, F. N., Marces, R. K. J. G., Lolong, H. M. G., & Niko, N. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-5601-3.ch016 · Cited by 1 · see citing works
ÜRETKEN YAPAY ZEKADA SİBER GÜVENLİK VE ETİK: CHATGPT ÖRNEĞİ
Gürsoy, S., & Yalçın, N. (2026) · Güvenlik Bilimleri Dergisi · doi:10.28956/gbd.1707204
Using chatbot in education – A systematic review and research agenda
Wut, T. M., Low, M. P., & Tam, K.-W. (2026) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2026.102956
Moral Dilemmas of Using AI in Academia: What Do Students Think?
Drushlyak, M. G., Будянський, Д. В., Шамоня, В. Г., Бобокало, А., Skoropad, H., & Семеніхіна, О. В. (2026) · International Convention on Information and Communication Technology, Electronics and Microelectronics · doi:10.1109/mipro70003.2026.11591977
A Structural Equation Modeling Approach to the Effect of AI Usage on Academic Performance
Yao, A. J., Palmiano, J. P., Flores, C. V., Regala, A., Mendoza, G., & BOLASOC, J. A. P. (2026) · International Conference on Information Technology and Education Technology (ITET) · doi:10.1109/itet70052.2026.11650939
Role of AI dependency in shaping 21st century skills in higher education with AI trust as a mediator
Akter, M. S., Sultana, F., Alam, S., Rupa, R. A., & Sultana, N. (2026) · Discover Artificial Intelligence · doi:10.1007/s44163-026-02056-8
Self-citationFrom innovation self-efficacy to innovative work behavior: a job crafting perspective
Campodonico, S., & Guevara, R. (2026) · Evidence-based HRM a Global Forum for Empirical Scholarship · doi:10.1108/ebhrm-02-2026-0077
Pizarro, L. I. M., & Chávez, A. A. (2026) · Erevna Research Reports · doi:10.70171/wrwxkz66
- Authors
- Niloy, A. C., Hafiz, R., Hossain, B. M., Gulmeher, F., Sultana, N., Islam, K. F., Bushra, F., Islam, S., Hoque, S. I., Rahman, M., & Kabir, S.
- Affiliations
- East West University (BD)
- Corresponding author
- Niloy, Ahnaf Chowdhury
- Venue
- International Journal of Educational Research Open
- Publisher
- Elsevier BV
- Published
- 2024-12
- Volume
- 7
- Pages
- 100396
- ISSN
- 2666-3740 (ISSN-L)
- OpenAlex
- W4403946826
- Cited by
- 26
- References
- 112
- Citations by year
- 2026: 14 · 2025: 12
- FWCI
- 10.82
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- International Journal of Educational Research Open (publishedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- AI chatbots, ChatGPT, academic integrity, student perceptions, university students, artificial intelligence in education, student behavior
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
