Exploring Students’ and Faculty’s Knowledge, Attitudes, and Perceptions Towards ChatGPT: A Cross-Sectional Empirical Study
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Aim/Purpose: This study explores the Knowledge, Attitude, and Perception (KAP) towards ChatGPT among university students and faculty. It also examines the faculty’s readiness to cope with the challenges and leverage the opportunities presented by AI-powered conversational models. Background: Launched on November 30, 2022, ChatGPT took the world by storm with its capability to generate high-quality written expressions in a conversational manner. The reactions to this innovation varied, from enthusiasm regarding its potential to enrich students’ learning to concerns about its threat to students’ cognitive development and academic integrity. A systematic exploration of students’ and faculty’s KAP towards ChatGPT can play an important role in addressing the multifaceted dimensions of AI-driven conversational models. Methodology: This study employs a cross-sectional survey research design based on questionnaires distributed to 145 faculty members, as well as 855 undergraduate and graduate students at the ESPRIT School of Engineering and School of Business. The student sample was based on stratified and convenience sampling, while the faculty sample was based on a consensus sampling approach. Contribution: To the best of our knowledge, this is the first reported study that contributes to understanding the KAP of students and faculty towards ChatGPT, as well as the readiness of faculty to effectively adopt AI-driven conversational models. Furthermore, our research contributes to the body of knowledge by taking Vygotsky’s (1978) principle of social interaction and its role in promoting cognitive development to a new level by hypothesizing that if students were to acquire the competencies to actively engage with AI-driven chatbots in meaningful discussions and collaborative conversations, they might be able to develop some higher-order thinking skills further. Findings: Our results indicated that faculty demonstrated a higher level of ChatGPT knowledge than students and that more than 40% of surveyed students and faculty expressed some trust in the reliability of ChatGPT’s responses, a perception that does not align with reality. Faculty attitude towards ChatGPT was comparatively more reserved compared to that of students and showcased varying opinions. Furthermore, the surveyed faculty showcased a more negative perception of ChatGPT than students, and they expressed a greater degree of skepticism. Our research revealed that 63.4% of surveyed faculty reported that they lack the requisite training and resources to integrate ChatGPT into their pedagogical practices. Recommendations for Practitioners: HEIs should take appropriate measures to enhance students’ and faculty’s knowledge, attitude, and perception regarding ChatGPT to stimulate ethical, meaningful, innovative, and engaging interactions and learning experiences. Recommendation for Researchers: Our study has shed light on some moderating factors that shape the acceptance of AI-driven conversational models and some adoption barriers. It delves into the perceptions, biases, and misconceptions held by both students and faculty, thereby providing a basis for future investigations on the effective integration of AI-driven conversational models in higher education. Impact on Society: This research provides new insights that can harness the potential merits of ChatGPT in enhancing students’ learning while mitigating potential pitfalls. It suggests facilitating open forums and dialogues among students, faculty, employers, and other key stakeholders to debate the impact of AI-driven conversational models on students’ learning and faculty’s teaching and assessment. Future Research: We invite researchers to conduct cross-cultural studies on this topic while also taking into consideration a qualitative research design approach. Future research can also test the hypothesis that AI-driven conversational models inhibit critical thinking by facilitating the passive consumption of information.
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Technology awareness and use of GenAI tools are negatively correlated with fear and skepticism, especially concerning academic integrity violations.
“and both were negatively correlated with fear and skepticism (Kamoun et al., 2024), especially concerning academic integrity violations (Rajabi et al., 2024; van Wyk, 2024).”
From Planets, cars, and personas: Toward an understanding of faculty perceptions of artificial intelligence through visual metaphors and projective techniques (2025) · cites this paper as Kamoun et al., 2024
Kamoun et al.’s Correlation Analysis (page unavailable) reports a positive association between knowledge and attitude, not the negative correlation attributed to it. It also reports a slight inverse association between faculty knowledge and perception; the Findings section says faculty were more knowledgeable than students yet more skeptical. The academic-integrity clause is attached to other citations, so it is not part of this verdict. (LLM, conf=0.82)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredKamoun et al. (2024) found that a significant portion of students exhibited a lack of understanding or dismissive attitudes toward using ChatGPT for plagiarism.
“Notably, Kamoun et al. (2024) found that a significant portion of students exhibited a lack of understanding or dismissive attitudes toward using ChatGPT for plagiarism.”
From Fostering AI Literacy in Undergraduates: A ChatGPT Workshop Case Study (2025) · cites this paper as Kamoun et al. (2024)
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Cites
DiMaggio, P. J., & Powell, W. W. (1983) · American Sociological Review · doi:10.2307/2095101 · Cited by 38,435 · see citing works
Technological Pedagogical Content Knowledge: A Framework for Teacher Knowledge
Mishra, P., & Koehler, M. J. (2006) · Teachers College Record: The Voice of Scholarship in Education · doi:10.1111/j.1467-9620.2006.00684.x · Cited by 12,604 · see citing works
Technology Acceptance Model 3 and a Research Agenda on Interventions
Venkatesh, V., & Bala, H. (2008) · Decision Sciences · doi:10.1111/j.1540-5915.2008.00192.x · Cited by 8,159 · see citing works
Expectancy-value theory of achievement motivation
Wigfield, A., & Eccles, J. S. (2000) · Contemporary Educational Psychology · doi:10.1006/ceps.1999.1015 · Cited by 7,383 · see citing works
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 · see citing works
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 · see citing works
Ray, P. P. (2023) · Internet of Things and Cyber-Physical Systems · doi:10.1016/j.iotcps.2023.04.003 · Cited by 2,463 · cited 1× · see citing works
“Yet, more than 40% of surveyed students and faculty expressed unwavering trust in the reliability of ChatGPT’s responses, a perception that does not align with reality given that most AI - driven conversational models are prone to errors and biases (e.g., Amaro et al., 2023; Ray, 2023).”
BackgroundPavlik, J. V. (2023) · Journalism & Mass Communication Educator · doi:10.1177/10776958221149577 · Cited by 972 · see citing works
Designing for Learning in an Open World
Conole, G. C. (2012) · Springer eBooks · doi:10.1007/978-1-4419-8517-0 · Cited by 537 · see citing works
Ashworth, P. D., Bannister, P., Thorne, P., & Researc, S. O. T. Q. (1997) · Studies in Higher Education · doi:10.1080/03075079712331381034 · Cited by 518 · see citing works
ChatGPT: The End of Online Exam Integrity?
Susnjak, T. (2022) · arXiv · doi:10.48550/arxiv.2212.09292 · Cited by 370 · cited 3× · see citing works
“Susnjak (2022) conducted several experiments to probe the potential misuse of ChatGPT as a tool for academic misconduct in online exams.”
BackgroundMethodExploring university students' perceptions of plagiarism: a focus group study
Gullifer, J., & Tyson, G. (2010) · Studies in Higher Education · doi:10.1080/03075070903096508 · Cited by 263 · see citing works
Marsden, H., Carroll, M., & Neill, J. T. (2005) · Australian Journal of Psychology · doi:10.1080/00049530412331283426 · Cited by 257 · see citing works
Multiple-Choice Exams: An Obstacle for Higher-Level Thinking in Introductory Science Classes
Stanger-Hall, K. F. (2012) · CBE—Life Sciences Education · doi:10.1187/cbe.11-11-0100 · Cited by 243 · see citing works
A 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 · see citing works
Haque, M. U., Dharmadasa, I., Sworna, Z. T., Rajapakse, R. N., & Ahmad, H. (2022) · arXiv · doi:10.48550/arxiv.2212.05856 · Cited by 203 · see citing works
Examining the Effect of Proctoring on Online Test Scores.
Alessio, H., Malay, N. J., Maurer, K., Bailer, A., & Rubin, B. (2017) · Online Learning · doi:10.24059/olj.v21i1.885 · Cited by 146 · see citing works
A Strategy to Reduce Plagiarism in an Undergraduate Course
Belter, R. W., & du Pré, A. (2009) · Teaching of Psychology · doi:10.1080/00986280903173165 · Cited by 107 · see citing works
Deterring Cheating in Online Environments
Corrigan-Gibbs, H., Gupta, N., Northcutt, C. G., Cutrell, E., & Thies, W. (2015) · TCHI · doi:10.1145/2810239 · Cited by 96 · see citing works
Khan, S. N., Kambris, M. E. K., & Alfalahi, H. (2021) · Education and Information Technologies · doi:10.1007/s10639-021-10784-w · Cited by 77 · see citing works
Copy Wrong: Plagiarism, Process, Property, and the Law
Stearns, L. (1992) · California Law Review · doi:10.2307/3480772 · Cited by 69 · see citing works
AI Unreliable Answers: A Case Study on ChatGPT
Amaro, I., Greca, A. D., Francese, R., Tortora, G., & Tucci, C. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-35894-4_2 · Cited by 53 · see citing works
Cheating behaviours, the Internet and Education undergraduate students
Trushell, J., Byrne, K., & Simpson, R. G. (2011) · Journal of Computer Assisted Learning · doi:10.1111/j.1365-2729.2011.00424.x · Cited by 51 · see citing works
Is Plagiarism a Forerunner of Other Deviance? Imagined Futures of Academically Dishonest Students
Lovett, G., Komarraju, M., Weston, R., & Dollinger, S. J. (2007) · Ethics & Behavior · doi:10.1080/10508420701519387 · Cited by 43 · see citing works
Critical Review of Quantitative and Qualitative Research
Xiong, X. (2022) · Advances in Social Science, Education and Humanities Research/Advances in social science, education and humanities research · doi:10.2991/assehr.k.220704.172 · Cited by 23 · see citing works
Whisenhunt, B., Cathey, C. L., Hudson, D. L., & Needy, L. (2022) · Scholarship of Teaching and Learning in Psychology · doi:10.1037/stl0000242 · Cited by 19 · see citing works
Fask, A., Englander, F., & Wang, Z.-B. (2014) · Journal of Academic Ethics · doi:10.1007/s10805-014-9207-1
Kamoun, F., Ayeb, W. E., Jabri, I., Sifi, S., & Iqbal, F. (2023) · ECE Official Conference Proceedings · doi:10.22492/issn.2188-1162.2023.20
Self-citation
Flagged first, then by citations
Research works printed but not linked: 4
- Burton, L. J. (2007). An interactive approach to writing essays and research reports in psychology (2nd ed.). John Wiley & Sons.
- Fishman, T. (2009, September). "We know it when we see it" is not good enough: Toward a standard defini- tion of plagiarism that transcends theft, fraud, and copyright. Proceedings of the 4th Asia-Pacific Conference on Educational Integrity, Wollongong, Australia, 45-53.
- Petress, K. (2003). Academic dishonesty: A plague on our profession. Education, 123(3), 624-627.
- Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
Cited by
Sorted by citations
Nazaretsky, T., Mejia‐Domenzain, P., Swamy, V., Frej, J., & Käser, T. (2025) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2025.100368 · Cited by 146 · see citing works
Bećirović, S., Polz, E., & Tinkel, I. (2025) · Smart Learning Environments · doi:10.1186/s40561-025-00384-3 · Cited by 133 · see citing works
“Furthermore, the fear of being insufficiently prepared to use AI output adequately (Kamoun et al., 2024) or the concern of limited creativity of AI output (Lepik, 2024; Pavlik, 2023) may explain the participants’ low scores in AI output.”
InfluentialAI Literacy in K-12 and Higher Education in the Wake of Generative AI: An Integrative Review
Gu, X., & Ericson, B. J. (2025) · ACM Conference on International Computing Education Research (ICER) · doi:10.1145/3702652.3744217 · Cited by 113 · see citing works
“Amid reflections on how generative AI tools could reshape computing education objectives [51, 64, 96], teaching AI literacy emerged as a potential path forward.”
AI Literacy in K-12 and Higher Education in the Wake of Generative AI: An Integrative Review
Gu, X., & Ericson, B. J. (2025) · arXiv · doi:10.48550/arxiv.2503.00079 · Cited by 73
“Amid reflections on how generative AI tools could reshape computing education objectives [51, 64, 96], teaching AI literacy emerged as a potential path forward.”
Abouammoh, N. A., Alhasan, K. A., Aljamaan, F., Raina, R., Malki, K. H., Altamimi, I., Muaygil, R. A., Wahabi, H., Jamal, A. A., Alhaboob, A. A. N., et al. (2025) · JMIR Medical Education · doi:10.2196/63400 · Cited by 101 · see citing works
“Previous literature has shown that in comparison with Google, the majority of the participants tend to doubtfully trust ChatGPT output for reasons related to the novelty of AI and users, lack of understanding of its algorithm, and information sources as studied previously [14,30].”
Medical students and ChatGPT: analyzing attitudes, practices, and academic perceptions
Abdelhafiz, A. S., Farghly, M. I., Sultan, E. A., Abouelmagd, M. E., Ashmawy, Y. M., & Elsebaie, E. H. (2025) · BMC Medical Education · doi:10.1186/s12909-025-06731-9 · Cited by 58 · see citing works
“…power, a 95% confidence level, a 5% significance level, and an estimated proportion of students expressing a positive attitude or trust in the reliability of ChatGPT at 40% [20], along with a design effect of 1, the minimum required sample size for this study was calculated to be 369 participants.”
Alshamy, A., Al-Harthi, A. S. A., & Abdullah, S. (2025) · Education Sciences · doi:10.3390/educsci15040501 · Cited by 46 · see citing works
“It is argued that GenAI is unable to foster genuine learning interactions, has data privacy issues, and lacks human interference in AI-mediated learning (Kamoun et al., 2024).”
Determinants of student adoption of artificial intelligence applications in higher education
Alshammari, S., Alrashidi, M. E., Alshammari, M. H., Alshammari, A. E. A., & Alkhwaldi, A. F. (2025) · Scientific Reports · doi:10.1038/s41598-025-19851-5 · Cited by 45 · see citing works
“Most studies have employed a TAM model that incorporates trust 48–50 .”
A Systematic Review of User Attitudes Toward GenAI: Influencing Factors and Industry Perspectives
Chen, J., Wei, X., Xie, Q., Hu, A., Qiao, Y., Wan, R., & Liu, Y. (2025) · Journal of Intelligence · doi:10.3390/jintelligence13070078 · Cited by 36 · see citing works
“Student educators were more independent in their attitudes and less swayed by external factors (Kamoun et al. 2024).”
Lelescu, A., Sava, S., Grosseck, G., & Maliţa, L. (2025) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-06253-1 · Cited by 37 · see citing works
“While policies provide a foundation, our analysis reveals that educators require professional support and training to effectively integrate GenAI into their teaching (Kamoun et al., 2024; Kurtz et al., 2024), with seventeen selected studies ( n = 17, 45”
InfluentialNovoa-Echaurren, Á., Pavez, I., & Anabalón, M. E. (2025) · Education Sciences · doi:10.3390/educsci15060643 · Cited by 40 · see citing works
“…studies have examined digital technology adoption in education through quantitative lenses that assess knowledge, attitudes, and perceptions (Kamoun et al., 2024), a notable gap remains in our understanding of the reflective processes through which teachers interpret, adapt, and redefine…”
Ngo, T. T. A., Vo, T. T. A., & Phan, M. T. (2025) · Acta Psychologica · doi:10.1016/j.actpsy.2025.105789 · Cited by 32 · see citing works
Generative AI Governance Model in Educational Research
de Pinho, I. G., Costa, A. P., & Pinho, C. S. B. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1594343 · Cited by 33 · see citing works
Xu, L., Ng, D. T. K., Lee, C. S. Y., Peng, P., & Chu, S. K. W. (2025) · Educational Technology Research and Development · doi:10.1007/s11423-025-10530-w · Cited by 28 · see citing works
“Additionally, the launch of OpenAI’s generative artificial intelligence (GenAI) chatbot ChatGPT in November 2022 has spurred interest on the effects of GenAI technologies on older adults, particularly DL development (Kamoun et al., 2024; Sriwisathiyakun & Dhamanitayakul, 2022).”
Subhani, F., Khan, S., Sandhu, M., & Shahzad, M. (2025) · TechTrends · doi:10.1007/s11528-025-01096-8 · Cited by 23 · see citing works
“Students who value academic integrity are more likely to adhere to institutional policies and guidelines regarding the use of AI tools (Kamoun, 2024).”
Shahzad, M. F., Xu, S., An, X., Asif, M., & Javed, I. (2025) · Interactive Learning Environments · doi:10.1080/10494820.2025.2524838 · Cited by 20 · see citing works
“A prior study suggested that factors such as technological culture, attitude towards technology adoption, and institution & government willingness and support affect GenAI technology adoption and implementation (Kamoun, 2024).”
Syed, W., Bashatah, A. S., Alharbi, K., Bakarman, S. S., Asiri, S., & Alqahtani, N. (2024) · Medical Science Monitor · doi:10.12659/msm.944993 · Cited by 20 · see citing works
“professionals in Riyadh, Saudi Arabia, and there is scant literature about awareness and perceptions towards ChatGPT among academicians and research professionals in Saudi Arabia and internationally [19,20].”
BackgroundÖzmat, D., & Akkoyunlu, B. (2024) · Participatory Educational Research · doi:10.17275/per.24.99.11.6 · Cited by 15 · see citing works
Nikoçeviq-Kurti, E., & Bërdynaj-Syla, L. (2024) · Educational Process: International Journal · doi:10.22521/edupij.2024.133.2 · Cited by 15
“…tend to have a more negative perception of ChatGPT compared to students and that they often display a higher degree of skepticism, with 63.4% of faculty reported as lacking the necessary training and resources to effectively integrate ChatGPT into their teaching practices (Kamoun et al., 2024).”
InfluentialSalido, A., Syarif, I., Suparjan, S., Wana, P. R., Sitepu, M. S., & Melisa, R. (2025) · Journal of Culture and Values in Education · doi:10.46303/jcve.2025.23 · Cited by 6 · see citing works
“…the integration of AI into collaborative and dialogic contexts — such as those described by Werdiningsih et al. (2024), Guo and Lee (2023), and Kamoun et al. (2024) — encourages intellectual empathy and fairness in evaluation, echoing Paul and Elder’s emphasis on dispositional attributes.”
InfluentialUnlocking AI Potential: Effort Expectancy, Satisfaction, and Usage in Research
Izhar, N. A., Teh, W. V. Y., & Adnan, A. (2025) · Journal of Information Technology Education Innovations in Practice · doi:10.28945/5450 · Cited by 12 · see citing works
“These programs should include mandatory workshops on ethical AI practices, covering topics such as plagiarism detection, critical evaluation of AI outputs, and strategies for mitigating biases (Kamoun et al., 2024).”
InfluentialJi, Y. (2026) · Journal of Academic Ethics · doi:10.1007/s10805-026-09752-1 · Cited by 15 · see citing works
“Since 2023, soon after ChatGPT’s release in November 2022, relevant research has emerged, including Barrett & Pack (2023) in the US and Črček & Patekar (2023) in Croatia, with eight studies in 2024.”
InfluentialTeachers’ perceptions of value-sensitive AI in education: A case study of AI tutor
Shen, Y., Le, H., Wang, Z., & Wang, Q. (2025) · Teaching and Teacher Education · doi:10.1016/j.tate.2025.105253 · Cited by 10 · see citing works
Karafil, B., & Uyar, A. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-13291-w · Cited by 14 · see citing works
“Kamoun et al. (2024) explored the “Knowledge, Attitude, and Perception (KAP)” towards ChatGPT among university students and academics.”
InfluentialEddine, R. J., Gide, E., & Sabbagh, A. A. (2026) · Discover Computing · doi:10.1007/s10791-026-10044-w · Cited by 16 · see citing works
Harrington, B., Zlotnikova, I., Nadarajan, G., & Ekundayo, S. (2025) · ACM Transactions on Computing Education · doi:10.1145/3776558 · Cited by 8 · see citing works
Al-Shamaileh, O., Mubin, O., & Nizamuddin, N. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2532712 · Cited by 7 · see citing works
CEALLAIGH, T. Ó., & Murphy, S. (2026) · Computers and Education Open · doi:10.1016/j.caeo.2026.100367 · Cited by 10 · see citing works
Bećirović, S., Augustín, M., Mattoš, B., & Dančo, J. (2026) · Discover Computing · doi:10.1007/s10791-026-10042-y · Cited by 7 · see citing works
Yin, X., Ye, J., Yu, S., Li, H., & Lu, G. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13831-y · Cited by 5 · see citing works
“…attitudes and acceptance towards GenAI’s applications, such as personalized learning, immediate feedback, and intelligent tutoring, serving as pivotal factors in motivating learning and shaping learning behaviors (Kamoun et al., 2024), embodying the role of GenAI-supported learning environments.”
How are faculty and college students embracing AI? — A multi-informant mixed method study
Xie, L., Jiang, Y., Chang, C., Zeng, X.-Y., Hong, J. S., & Mo, F. (2025) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2025.100506 · Cited by 7 · see citing works
Vinyard, M., & Roosa, M. S. (2025) · portal Libraries and the Academy · doi:10.1353/pla.2025.a971030 · Cited by 5 · see citing works
Fostering AI Literacy in Undergraduates: A ChatGPT Workshop Case Study
Archambault, S. G., Murph, N. L., & Ramachandran, S. (2025) · Library Trends · doi:10.1353/lib.2025.a968491 · Cited by 5 · see citing works
Mind Over Model? Students' Evaluation and Use of ChatGPT ‐Generated Versus Human‐Generated Texts
Latini, N., Bråten, I., & Strømsø, H. I. (2026) · Reading Research Quarterly · doi:10.1002/rrq.70087 · Cited by 5 · see citing works
“Several other quantitative survey studies with university-level participants also have found that students may report considerable mistrust in content generated by AI tools, in particular, by ChatGPT (e.g., Dietrich and Grassini 2025; Kamoun et al. 2024; Morrell-Mengual et al. 2025; Yu et al. 2024).”
Singh, P., & Anthonysamy, L. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13773-5 · Cited by 6 · see citing works
“…ambivalent feelings about AI simulations of conversation, calling for greater education and moral codes (Kamoun et al. These results underscore the need for extensive training and institutional backing to encourage the ethical use of AI in higher education (Kamoun et al., 2024; Zaragoza, 2023).”
Jogezai, N., Baloch, F. A., Jaffar, M., & Khilji, G. (2025) · Quality Assurance in Education · doi:10.1108/qae-12-2024-0255 · Cited by 5 · see citing works
Karakitsou, C., Karayianni, I., Leftheriotis, K., Logotheti, A., & Avgerinou, M. D. (2025) · Journal of Visual Literacy · doi:10.1080/1051144x.2025.2538256 · Cited by 3 · see citing works
“…they offer (van Wyk, 2024). studies agree that educators’ concerns can be countered through explicit formal guidelines (Barrett & Pack, 2023) and highlight the need for institutions to provide training on AI and the use of GenAI in educational contexts (Gaber et al., 2023; Kamoun et al., 2024).”
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Mariyadi, Al, A. D. F., Putra, P., Budi, M. G., & Grathyo, S. J. (2024) · Didaktika: Jurnal Kependidikan · doi:10.58230/27454312.1210 · Cited by 3
“Temuan tersebut sesuai dengan beberapa penelitian sebelumnya (Kamoun, 2024) yang mengungkap bahwa salah satu persepsi mahasiswa terhadap ChatGPT adalah aplikasi tersebut mudah untuk digunakan.”
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Bråten, I., Latini, N., & Strømsø, H. I. (2026) · Education and Information Technologies · doi:10.1007/s10639-026-13938-w · Cited by 2 · see citing works
“Recently, basic knowledge about ChatGPT also has been assessed with a small number of multiple-choice questions about what ChatGPT is, as well as about its key strength and main limitation (Kamoun et al., 2024).”
Laypersons’ perceptions and misconceptions of AI-chatbots: a systematic review
Schneller, M., Seier, J., & Albert, D. (2026) · Universal Access in the Information Society · doi:10.1007/s10209-026-01323-w · Cited by 1 · see citing works
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Rodafinos, A., Velli, K., & Barkoukis, V. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2630090 · Cited by 2 · see citing works
“Prior research has primarily focused on adoption correlates, often using cross-sectional designs (Fuller & Barnes, 2024; Kamoun et al., 2024).”
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Bui, N., & Dong, A.-J. (2026) · International Computer Science Conference · doi:10.1109/icsc67292.2026.00055 · Cited by 2 · see citing works
Jogezai, N. A., Jaffar, M., Baloch, F. A., & Khilji, G. K. (2025) · International Journal of Information and Learning Technology · doi:10.1108/ijilt-10-2024-0229 · Cited by 3 · see citing works
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Llerena-Izquierdo, J., Vargas, I. V. F., Gorozabel, J. A. P., & Arce, A. E. V. (2024) · IEEE URUCON · doi:10.1109/urucon63440.2024.10850207 · Cited by 1 · see citing works
“…of educational institutions, and especially teachers, to develop practices that not only provide students with new logical skills of thinking algorithmically, but also improve learning comprehension, foster autonomous individual learning, reduce academic risk, and optimize content plans [7]–[9].”
Achili, N., & Zerrouki, N. (2024) · ATRAS journal · doi:10.70091/atras/ai.34 · Cited by 2
“In another noteworthy research paper, Kamoun et al. (2024) investigated students’ and faculty members’ perceptions of AI.”
BackgroundResultInfluentialApata, O. E., Kwok, O., & Ajose, S. T. (2026) · Journal of Computer Assisted Learning · doi:10.1002/jcal.70309 · Cited by 3 · see citing works
The Use of ChatGPT Among High And Mid To Low Achiever Students in Writing Undergraduate
Hasyim, M., Zuhairi, A., Yunus, M., & Subarjo, S. (2025) · Ethical Lingua: Journal of Language Teaching and Literature · doi:10.30605/25409190.870 · Cited by 1 · see citing works
“These findings highlight the need for academic guidance and digital literacy development among lower-performing students to ensure that AI tools are used in a more ethical and constructive manner (Kamoun et al., 2024).”
Muchaku, S., Kabiti, H., & Nthambeleni, B. (2025) · International Journal of Research In Business and Social Science · doi:10.20525/ijrbs.v14i6.4080 · Cited by 1 · see citing works
Integridade acadêmica na era do ChatGPT
de Lima, J. C. R., & Felippe, M. L. (2025) · Revista Brasileira da Educação Profissional e Tecnológica · doi:10.15628/rbept.2025.17803 · Cited by 2 · see citing works
Núñez, E. V., & Zúñiga-Sánchez, O. (2025) · LATAM Revista Latinoamericana de Ciencias Sociales y Humanidades · doi:10.56712/latam.v6i3.4124 · Cited by 1 · see citing works
Engineering Students’ Perceptions of AI and Educational Innovations in the Academic Setting
Aguirre, H. C. C., Esparza, C., & Carrillo, L. G. (2025) · International Symposium on Electronic Commerce · doi:10.1109/isec64801.2025.11147296 · Cited by 1
“Students were found to have a moderately positive attitude towards AI like ChatGPT, with most perceiving it as an easy, reliable, and useful resource [7].”
InfluentialShahzad, M. F., Asif, M., Xu, S., Bilal, A., & Zahid, I. (2026) · The international journal of information and learning technology · doi:10.1108/ijilt-11-2025-0340
Gang, Y., Jiang, R., & Shen, Q. (2026) · System · doi:10.1016/j.system.2026.104143
Badillo-Marquez, G., Chafloque-Capuñay, J. E., Calcina, J. G. M., Rosales, L. L. R., Atahualpa, R. L. C., & Magallanes, M. (2026) · Prohominum · doi:10.47606/acven/ph0529
Jia, B., Mohamad, M., Kamsin, I. F., & Shim, J. (2026) · Arab World English Journal · doi:10.24093/awej/call12.17
“Kamoun et al. (2024) recommend introducing specialized training on formulating and refining prompts when interacting with GenAI tools while adhering to ethical and responsible use practices.”
Alvarado, J. E. G., Lagos, J. C. E., & Oyarvide, W. R. V. (2026) · Revista Tribunal · doi:10.59659/revistatribunal.v6i16.521
A Systematic Review of Generative AI for Educational Recommender Systems
Ilyasa, D. F., Ahmad, I., & Rahayu, N. W. (2026) · IEEE International Conference on Innovation, Ethics & Emerging Tech in Engineering and Computing Education (IE2C) · doi:10.1109/ie2c69620.2026.11663045
Supporting Mature-Aged Early Childhood Students’ Online Learning in Australian Higher Education
Liu, J., & Zheng, Z. (2026) · Education Sciences · doi:10.3390/educsci16060937
“The challenges associated with the critical and ethical use of GenAI tools further underline the need to enhance reflective teaching to cultivate pedagogical decision-making (Kamoun et al., 2024).”
Ngo, T., Vu, T., Nguyen, T., Nguyen, T., & Tieu, T. (2026) · Computer-Assisted Language Learning Electronic Journal · doi:10.54855/issue.12345.27
“Much of the existing literature focuses on the general benefits of ChatGPT in education (Lee et al., 2024; Torres-Cruz et al., 2023; Kamoun et al., 2024), while very few studies have focused on the improvements in academic writing of EFL learners, especially in non-native English contexts.”
Ahmed, A., Abbas, A., & Haider, I. (2026) · journal of social sciences review · doi:10.62843/jssr.v6i2.750
Inclusive AI-Enhanced Civic Engagement: Empowering Marginalized Voices
Schneller, M., Bedek, M., de Lera, E., Kocsis, O., Seier, J., & Albert, D. (2026) · Societies · doi:10.3390/soc16040115
Phan, B. H. V., Tong, H. A., Tran, D. Q., & Nguyen, T. V. (2026) · Education and Information Technologies · doi:10.1007/s10639-026-13955-9
Sánchez-Labella, J., González-Rojas, A., & Julián, I. P. (2025) · Community Notebook People Education and Welfare in the Society 5 0 · doi:10.61007/qdc.2025.2.376
Proença, J. J. C., & Vera, C. R. (2026) · Prometheus · doi:10.13169/prometheus.41.1.0004
Debs, L., Talley, K. G., & Souza, A. (2026) · ASEE Annual Conference & Exposition · doi:10.18260/1-2--59370
- Authors
- Kamoun, F., El Ayeb, W., Jabri, I., Sifi, S., & Iqbal, F.
- Affiliations
- École Supérieure Privée d'Ingénierie et de Technologies (TN)
- ESPRIT School of Business
- Zayed University (AE)
- Venue
- Journal of Information Technology Education: Research
- Publisher
- Informing Science Institute
- Published
- 2024
- Volume
- 23
- Pages
- 004
- ISSN
- 1539-3585 (ISSN-L)
- 1547-9714
- OpenAlex
- W4391759421
- Cited by
- 54
- References
- 32
- Citations by year
- 2026: 20 · 2025: 31 · 2024: 3
- FWCI
- 20.37
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Journal of Information Technology Education Research (publishedVersion, cc-by-nc)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Keywords
- ChatGPT, large language models, knowledge, attitudes and perceptions, university students, teacher perceptions, artificial intelligence in higher education, academic integrity, trust in AI, faculty readiness, higher-order thinking skills, AI ethics education
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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.
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