The Integration of Generative AI Tools in Academic Writing: Implications for Student Research
Open accessAbstract
This article explores the integration of generative Artificial Intelligence (AI) tools in academia, focusing on their impact on student research and writing at advanced levels. It explores how AI can assist with key tasks such as literature reviews, research question formulation, argument construction, data analysis, and thesis organization. The paper argues that the responsible integration of AI is essential, emphasizing the ongoing need for critical thinking to maintain academic integrity. A qualitative case study illustrates student experiences with AI-assisted academic writing, revealing perceived benefits including increased efficiency and enhanced quality, while emphasizing the necessity of verifying AI outputs and preserving human critical oversight. The discussion further addresses the need for universities to adapt by embedding AI literacy into curricula and establishing clear ethical use policies. The central position asserts that, by embracing AI as a valuable ally rather than prohibiting its use, universities can empower students to enrich their learning experiences and better prepare for success in an AI-driven workforce.
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Rodafinos illustrates the creative and productive affordances of tools like ChatGPT, while also warning of their potential to undermine academic integrity when used uncritically.
“Rodafinos [38] illustrates the creative and productive affordances of tools like ChatGPT, while also warning of their potential to undermine academic integrity when used uncritically.”
From Artificial Intelligence in Higher Education: A State-of-the-Art Overview of Pedagogical Integrity, Artificial Intelligence Literacy, and Policy Integration (2025) · cites this paper as [38]
Rodafinos and Cheng et al. also note the risk of depersonalized thinking and formulaic academic expression.
“However, they also note the risk of depersonalized thinking and formulaic academic expression.”
From Artificial Intelligence in Higher Education: A State-of-the-Art Overview of Pedagogical Integrity, Artificial Intelligence Literacy, and Policy Integration (2025) · cites this paper as [38]
Rodafinos and Cheng et al. examine the positive contributions of AI to assignment writing, particularly in structuring, language precision, and statistical support.
“Rodafinos [38] and Cheng et al. [3] examine the positive contributions of AI to assignment writing, particularly in structuring, language precision, and statistical support.”
From Artificial Intelligence in Higher Education: A State-of-the-Art Overview of Pedagogical Integrity, Artificial Intelligence Literacy, and Policy Integration (2025) · cites this paper as [38]
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Cites
Southworth, J., Migliaccio, K., Glover, J., Glover, J., Reed, D., McCarty, C., Brendemuhl, J., & Thomas, A. (2023) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2023.100127 · Cited by 647 · cited 1× · see citing works
“Following the lead of universities like the University of Florida with their “AI Across the Curriculum” initiative (Southworth et al., 2023), institutions are increasingly integrating AI Literacy into their programs, equipping students with the necessary skills to navigate the evolving world of AI.”
Fabrication and errors in the bibliographic citations generated by ChatGPT
Walters, W. H., & Wilder, E. I. (2023) · Scientific Reports · doi:10.1038/s41598-023-41032-5 · Cited by 499 · cited 1× · see citing works
“5 have produced fabricated citations in approximately 30% to 57% of cases, depending on the discipline, while even improved versions like ChatGPT-4 still generate fabricated references at a lower but non-negligible rate (Walters & Wilder, 2023).”
Will ChatGPT get you caught? Rethinking of Plagiarism DetectionPreprint
Khalil, M., & Er, E. (2023) · Interacción · doi:10.48550/arxiv.2302.04335 · Cited by 369 · cited 1× · see citing works
“The rate of plagiarism using AI-generated content has risen sharply (Song, 2024; Khalil & Er, 2023), prompting universities to scramble for solutions.”
Assigning AI: Seven Approaches for Students, with Prompts
Mollick, E. R., & Mollick, L. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4475995 · Cited by 319 · see citing works
Alshater, M. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4312358 · Cited by 304 · see citing works
Higher education crisis: Academic misconduct with generative AI
Song, N. (2024) · Journal of Contingencies and Crisis Management · doi:10.1111/1468-5973.12532 · Cited by 107 · cited 1× · see citing works
“The rate of plagiarism using AI-generated content has risen sharply (Song, 2024; Khalil & Er, 2023), prompting universities to scramble for solutions.”
ChatGPT in academic writing: Maximizing its benefits and minimizing the risks
Mondal, H., & Mondal, S. (2023) · Indian Journal of Ophthalmology · doi:10.4103/ijo.ijo_718_23 · Cited by 80 · see citing works
Cerdà-Navarro, A., Garma, C. T., Morey-López, M., & Curiel, E. (2022) · Heliyon · doi:10.1016/j.heliyon.2022.e09170 · Cited by 45 · see citing works
Novos desafios para a educação na Era da Inteligência Artificial
Azambuja, C. C., & da Silva, G. F. (2024) · Filosofia Unisinos · doi:10.4013/fsu.2024.251.07 · Cited by 41 · cited 1× · see citing works
“Universities need to proactively adapt (Azambuja & Silva, 2024; Romo-Pérez, 2023).”
Perkins, M., & Roe, J. (2025) · Edward Elgar Publishing eBooks · doi:10.4337/9781035338764.00012 · Cited by 25 · see citing works
Spennemann, D. H. R. (2025) · Publications · doi:10.3390/publications13010012 · Cited by 23 · cited 1× · see citing works
“Recent studies (e.g., Spennemann, 2025) have shown that generative AI models, including those commonly used by graduate students, can fabricate references and content with notable frequency.”
Wörner, J. H. R., Turtova, A. P., & Lang, A. S. I. D. (2024) · IEEE SoutheastCon · doi:10.1109/southeastcon52093.2024.10500042 · Cited by 19 · see citing works
Tarisayi, K. S. (2023) · AI and Ethics · doi:10.1007/s43681-023-00333-1 · Cited by 17 · cited 1× · see citing works
“Most universities have clear plagiarism policies (Cerdà-Navarro et al., 2022), although in the era of AI adjustments are urgently required (Tarisayi, 2023)-ensure you understand and follow them when using AI.”
Nešić, A. (2023) · Social informatics journal · doi:10.58898/sij.v2i1.01-06 · Cited by 16 · cited 1× · see citing works
“Emerging estimates suggest that a significant portion-potentially up to 90%-of future jobs will necessitate strong digital literacy skills (Tomašević, 2023; Riddle, 2015).”
Assigning AI: Seven Approaches for Students, with PromptsPreprint
Mollick, E., & Mollick, L. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2306.10052 · Cited by 15 · cited 1× · see citing works
“Mollick and Mollick (2023) proposed seven approaches for utilizing AI in classrooms: AI tutor, AI coach, AI mentor, AI teammate, AI tool, AI simulator, and AI students.”
Impact of AI on Education and the Need for Academia to Adopt: A Review
N, N. K. H., Mahadevaswamy, Praveena, K. S., & Shivashankar, R. (2024) · Journal of Engineering Education/Journal of engineering education transformations/Journal of engineering education transformation · doi:10.16920/jeet/2024/v37is2/24133 · Cited by 14 · cited 1× · see citing works
“The time for universities to adapt to the rise of AI is now (Kumar et al., 2024).”
ChatGPT ha llegado ¿Y ahora qué hacemos? La creatividad, nuestro último refugio
Romo-Pérez, V., Soidán, J. L. G., Özdemir, A. S., & Leirós‐Rodríguez, R. (2023) · Revista de Investigación en Educación · doi:10.35869/reined.v21i3.4973 · Cited by 13 · see citing works
My new favorite research partner is an AI: What roles can librarians play in the future?
Lo, L. S. (2023) · College & Research Libraries News · doi:10.5860/crln.84.6.209 · Cited by 11 · cited 1× · see citing works
“Let it conduct in-depth literature reviews, finding relevant sources and summarizing key findings (Lo, 2023).”
Perkins, M., & Roe, J. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2408.06872 · Cited by 11 · cited 1× · see citing works
“Gen AI can be your research assistant extraordinaire (Perkins & Roe, 2024; Shamsabadi & D’Souza, 2024).”
The robots are coming for your job! Why digital literacy is so important for the jobs of the future
Riddle, S. (2015) · doi:10.64628/aa.jv9aumw7m · Cited by 10 · see citing works
An Analysis of Integration of Artificial Intelligence in Higher Studies
Mishra, K., & Srivastava, A. K. (2024) · Revista Review Index Journal of Multidisciplinary · doi:10.31305/rrijm2024.v04.n01.006 · Cited by 8 · cited 1× · see citing works
“These powerful tools, capable of generating human-quality text, code, and data, are rapidly infiltrating schools and universities, transforming the way students approach their studies (Mishra & Srivastava, 2024; Woerner et al., 2024).”
A FAIR and Free Prompt-based Research AssistantPreprint
Shamsabadi, M., & D'Souza, J. (2024) · International Conference on Applications of Natural Language to Data Bases · doi:10.48550/arxiv.2405.14601 · Cited by 6 · cited 1× · see citing works
“Gen AI can be your research assistant extraordinaire (Perkins & Roe, 2024; Shamsabadi & D’Souza, 2024).”
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Adamakis, M., & Rachiotis, T. (2025) · Encyclopedia · doi:10.3390/encyclopedia5040180 · Cited by 76 · see citing works
“Rodafinos [38] illustrates the creative and productive affordances of tools like ChatGPT, while also warning of their potential to undermine academic integrity when used uncritically.”
InfluentialHorban, O., Stadnyk, M., Vintoniv-Bakharieva, S., Панасюк, Л. В., & Yatyshchuk, O. (2025) · Journal of Educational Technology and Learning Creativity · doi:10.37251/jetlc.v3i2.2333 · Cited by 5 · see citing works
“Rodafinos [50] posited GenAI as a cognitive accelerator in research writing, accentuating the enhancement of argument formation, thesis structuring, and critical verification of results.”
Gabay, R. A. E., Funa, A. A., & Ricafort, J. D. (2025) · Research Square · doi:10.21203/rs.3.rs-7440784/v1 · Cited by 5 · see citing works
Pérez, C. S. P. (2025) · Revista Española de Educación Médica · doi:10.6018/edumed.679941 · Cited by 1 · see citing works
Mokgwathi, M. S. (2026) · Discover Education · doi:10.1007/s44217-026-01797-z · Cited by 3 · see citing works
“Studies examining AI in academic writing emphasise the necessity of human oversight, verification of outputs, and transparent disclosure practices to maintain scholarly standards [19, 31].”
Χρυσανθοπούλου, Κ. (2026) · Ετήσιο Ελληνόφωνο Επιστημονικό Συνέδριο Εργαστηρίων Επικοινωνίας · doi:10.12681/cclabs.9684
Qureshi, S. (2026) · VFAST Transactions on Education and Social Sciences · doi:10.21015/vtess.v14i1.2396 · Cited by 2 · see citing works
“Interventions that teach students about how AI works, its limitations (hallucinations, biases, outdated information), appropriate citation practices, and strategies for reflective AI use reduce misconduct and support skill retention (Akiba and Garte, 2024; Rodafinos, 2025; Selim, 2024).”
InfluentialVorontsova, T. O., MUDRYK, U., Mykolenko, A. Z., Tvorko, V. M., Stakhurska, I. O., & Dzhyvak, V. G. (2026) · Academic Visions · doi:10.66556/2786-586x.55.vorontsova-t
Noor, M. L. A.-H. M., Isa, M. A., Sahrir, M. S., & Ghalib, M. F. (2026) · International Journal of Learning Teaching and Educational Research · doi:10.26803/ijlter.25.9.20
Alkashgari, R. H., Alhayani, A. A., Nasser, A. A., Sheikh, K. H., Sultan, I. E., & Badawy, Y. A. (2026) · MedEdPublish · doi:10.12688/mep.21859.1
Typologies and Competencies of Prompt Literacy in Generative Artificial Intelligence
Plaatjies, B. O., & van Wyk, M. M. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-8332-3.ch002
- Authors
- Rodafinos, A.
- Affiliations
- Aristotle University of Thessaloniki (GR)
- Corresponding author
- Rodafinos, Angelos
- ORCID
- Rodafinos, Angelos
- Venue
- Social Education Research
- Publisher
- Universal Wiser Publisher Pte. Ltd
- Published
- 2025-05-23
- Pages
- 250-258
- ISSN
- 2717-5723 (ISSN-L)
- 2717-5731
- OpenAlex
- W4410636079
- Cited by
- 11
- References
- 17
- Citations by year
- 2026: 7 · 2025: 4
- FWCI
- 11.53
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Social Education Research (publishedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- generative AI, academic writing, student research, AI-assisted writing, research question formulation, argument construction, data analysis, thesis organization, academic integrity, critical thinking, AI literacy, AI ethics policy, higher education, student experience
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