Computer Science · Literature

Research papers on Generative AI in education

Recent and highly-cited academic work on generative ai in education, gathered from Semantic Scholar, CrossRef and OpenAlex.

1. Challenges and Opportunities of Generative AI for Higher Education as Explained by ChatGPT

   Rosario Michel‐Villarreal, Eliseo Luis Vilalta-perdomo, David Ernesto Salinas-Navarro, et al. · 2023 · Education Sciences · 871 citations

   ChatGPT is revolutionizing the field of higher education by leveraging deep learning models to generate human-like content. However, its integration into academic settings raises concerns regarding academic integrity, plagiarism detection, and the potential impact on critical thinking skills. This article presents a study that adopts a thing ethnography approach to understand ChatGPT’s perspective on the challenges and opportunities it represents for higher education. The research explores the potential benefits and limitations of ChatGPT, as well as mitigation strategies for addressing the identified challenges. Findings emphasize the urgent need for clear policies, guidelines, and framewor

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2. ChatGPT in higher education: Considerations for academic integrity and student learning

   Miriam Sullivan, Andrew Kelly, Paul McLaughlan · 2023 · Journal of Applied Learning & Teaching · 847 citations

   The release of ChatGPT has sparked significant academic integrity concerns in higher education. However, some commentators have pointed out that generative artificial intelligence (AI) tools such as ChatGPT can enhance student learning. Consequently, academics should adapt their teaching and assessment practices to embrace the new reality of living, working, and studying in a world where AI is freely available. Despite this important debate, very little academic literature has been published on ChatGPT and other generative AI tools. This article uses content analysis to examine news articles (N=100) about how ChatGPT is disrupting higher education, concentrating specifically on Australia, Ne

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3. ChatGPT and the rise of generative AI: Threat to academic integrity?

   Damian Eke · 2023 · Journal of Responsible Technology · 528 citations

   The emergence of OpenAI's ChatGPT has put intense spotlight on Generative AI (Gen-AI) systems and their possible impacts on Academic integrity. This paper provides an overview of the current arguments around ChatGPT and Academic integrity and concludes that although these technologies are capable of revolutionising academia, the way ChatGPT and other generative AI systems are used could surely undermine academic integrity. However, to ensure that the risks to academic integrity are mitigated for greater maximisation, institutional and multi-stakeholder efforts are required.

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4. Generative AI and Academic Integrity in Higher Education: A Systematic Review and Research Agenda

   Kyle Bittle, Omar El-Gayar · 2025 · Information · 297 citations

   This systematic literature review rigorously evaluates the impact of Generative AI (GenAI) on academic integrity within higher education settings. The primary objective is to synthesize how GenAI technologies influence student behavior and academic honesty, assessing the benefits and risks associated with their integration. We defined clear inclusion and exclusion criteria, focusing on studies explicitly discussing GenAI’s role in higher education from January 2021 to December 2024. Databases included ABI/INFORM, ACM Digital Library, IEEE Xplore, and JSTOR, with the last search conducted in May 2024. A total of 41 studies met our precise inclusion criteria. Our synthesis methods involved qua

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5. Engineering Education in the Era of ChatGPT: Promise and Pitfalls of Generative AI for Education

   Junaid Qadir · 2022 · 264 citations

   Engineering education is constantly evolving to keep up with the latest technological developments and meet the changing needs of the engineering industry. One promising development in this field is the use of generative artificial intelligence technology, such as the ChatGPT conversational agent. ChatGPT has the potential to offer personalized and effective learning experiences by providing students with customized feedback and explanations, as well as creating realistic virtual simulations for hands-on learning. However, it is important to also consider the limitations of this technology. ChatGPT and other generative AI systems are only as good as their training data and may perpetuate bia

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6. The impact of generative AI on academic integrity of authentic assessments within a higher education context

   Alexander Kofinas, Crystal Han‐Huei Tsay, David Pike · 2025 · British Journal of Educational Technology · 197 citations

   Generative AI (hereinafter GenAI) technology, such as ChatGPT, is already influencing the higher education sector. In this work, we focused on the impact of GenAI on the academic integrity of assessments within higher education institutions, as GenAI can be used to circumvent assessment approaches within the sector, compromising their quality. The purpose of our research was threefold: first, to determine the extent to which the use of GenAI can be detected via the marking and moderation process; second, to understand whether the presence of GenAI affects the marking process; and finally, to establish whether authentic assessments can safeguard academic integrity. We used a series of experim

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7. The rapid rise of generative AI and its implications for academic integrity: Students’ perceptions and use of chatbots for assistance with assessments

   Jan Henrik Gruenhagen, Peter M. Sinclair, Julie‐Anne Carroll, et al. · 2024 · Computers and Education Artificial Intelligence · 189 citations

   The rapid adoption of generative AI tools such as ChatGPT by students has the potential to disrupt the higher education sector, with concerns being raised by academics about potential threats to academic integrity. This paper contributes to the pressing discussion about responses to AI tools by examining students' perceptions and the use of generative AI to assist them with assessments. Based on a survey among 337 Australian university students, this study found that more than a third of students have used a chatbot for assistance with an assessment, and do not necessarily perceive this as a breach of academic integrity. The study further investigated to what extent different psychosocial fa

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8. Understanding the diffusion of AI-generative (ChatGPT) in higher education: Does students' integrity matter?

   Mohamed Bouteraa, Saeed Awadh Bin‐Nashwan, Meshari Al-Daihani, et al. · 2024 · Computers in Human Behavior Reports · 163 citations

   ChatGPT, an AI-powered language model, is revolutionising the academic world. Scholars, researchers, and students use its advanced capabilities to achieve their educational objectives, including generating innovative ideas, delivering assignments, and conducting extensive research projects. Nevertheless, the use of ChatGPT among students is contentious, giving rise to significant apprehensions regarding integrity and AI-facilitated deceit. At the same time, scholarly communities currently need more well-defined standards for adopting such academia-oriented technology. This study aims to determine students' use of ChatGPT using the Unified Theory of Acceptance and Use of Technology (UTAUT) an

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9. The ChatGPT Effect: Nursing Education and Generative Artificial Intelligence

   Maxim Topaz, Laura‐Maria Peltonen, Martin Michalowski, et al. · 2024 · Journal of Nursing Education · 99 citations

   This article examines the potential of generative artificial intelligence (AI), such as ChatGPT (Chat Generative Pre-trained Transformer), in nursing education and the associated challenges and recommendations for their use. Generative AI offers potential benefits such as aiding students with assignments, providing realistic patient scenarios for practice, and enabling personalized, interactive learning experiences. However, integrating generative AI in nursing education also presents challenges, including academic integrity issues, the potential for plagiarism and copyright infringements, ethical implications, and the risk of producing misinformation. Clear institutional guidelines, compreh

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10. Navigating Generative AI (ChatGPT) in Higher Education: Opportunities and Challenges

    Tianchong Wang · 2023 · Lecture notes in educational technology · 56 citations

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11. Student Perceptions of AI-Assisted Writing and Academic Integrity: Ethical Concerns, Academic Misconduct, and Use of Generative AI in Higher Education

    Brady Lund, Nishith Reddy Mannuru, Zoë Abbie Teel, et al. · 2025 · AI in Education · 55 citations

    The rise of generative AI in higher education has disrupted our traditional understandings of academic integrity, moving our focus from clear-cut infractions to evolving ethical judgment. In this study, a survey of 401 students from major U.S. universities provides insight into how beliefs, behaviors, and policy awareness intersect in shaping how students interact with AI-assisted writing. The findings indicate that students’ ethical beliefs—not institutional policies—are the strongest predictors of perceived misconduct and actual AI use in writing. Policy awareness was found to have no significant effect on ethical judgments or behavior. Instead, students who believe AI writing is cheating

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12. Generative artificial intelligence (Gen-AI) in pharmacy education: Utilization and implications for academic integrity: A scoping review

    R. Mortlock, Cherie Lucas · 2024 · Exploratory Research in Clinical and Social Pharmacy · 49 citations

    Introduction: Generative artificial intelligence (Gen-AI), exemplified by the widely adopted ChatGPT, has garnered significant attention in recent years. Its application spans various health education domains, including pharmacy, where its potential benefits and drawbacks have become increasingly apparent. Despite the growing adoption of Gen-AIsuch as ChatGPT in pharmacy education, there remains a critical need to assess and mitigate associated risks. This review exploresthe literature and potential strategies for mitigating risks associated with the integration of Gen-AI in pharmacy education. Aim: To conduct a scoping review to identify implications of Gen-AI in pharmacy education, identif

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13. Purpose before policy: academic integrity, generative AI, and rhetorical stance

    Tristan B. Taylor, Travis LaCroix · 2026 · Higher Education · 2 citations

    The release of ChatGPT in 2022 sparked polarised responses in higher education, from rapid curricular adoption to warnings about academic misconduct and threats to academic integrity. This article argues that whether generative AI (GenAI) use constitutes misconduct depends on a prior question: what is the university’s purpose? We contend that (apparent) rising GenAI-related misconduct cases reflect structural incoherence in the neo-liberal university, where technological enthusiasm, corporate influence, and policy enforcement often conflict. Such misalignment produces moral and institutional ambiguity, leaving students accountable for behaviours implicitly shaped by the institution itself. D

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14. ACADEMIC INTEGRITY IN THE AGE OF CHATGPT AND GENERATIVE ARTIFICIAL INTELLIGENCE

    Dr. S. G. Baviskar · 2026 · Zenodo (CERN European Organization for Nuclear Research)

    Abstract: The rapid advancement of generative artificial intelligence (AI), particularly tools such as ChatGPT, has significantly transformed teaching, learning, and academic research. While these technologies offer unprecedented opportunities for personalized learning, efficiency, and creativity, they also raise serious concerns about academic integrity. Traditional notions of authorship, originality, plagiarism, and assessment are being challenged as students increasingly rely on AI-generated content for assignments, examinations, and research work. This paper examines the concept of academic integrity in the age of generative AI, focusing on the ethical, pedagogical, and institutional imp

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15. Generative AI and Academic Integrity in Higher Education

    Sathy Akter* · 2026 · British Journal of Arts and Humanities

    This research report examines the impact of Generative Artificial Intelligence (GenAI) on academic integrity in higher e­ducation on a global scale while specifically analyzing professional education in the USA. In this era marked by the widespread presence of Large Language Models like ChatGPT, DeepSeek and Gemini, the traditional ways of assessment are challenged as never before. This study refers to the literature published in the last five years (2021-2026) to assess the pedagogical, ethical, and technical aspects of the use of AI. The analysis finds that there seems to be an important change in the "honor code" approach of the traditional system for a more complex system that has been r

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16. Generative AI ChatGPT in Islamic Economics Education Critical Literacy and Academic Ethics

    Laelaturramadani Laelaturramadani · 2026 · Journal of Knowledge and Collaboration

    This study explores the utilization of Generative AI, specifically ChatGPT, in Islamic Economics Education, focusing on its impact on students' critical literacy and academic ethics. Employing a qualitative research design through a literature review, this study systematically analyzes relevant academic sources published in the past five years to investigate how AI tools, such as ChatGPT, are being integrated into the learning process in higher education, particularly in Islamic economics programs. The findings reveal that ChatGPT enhances learning efficiency by providing students with immediate access to complex economic concepts and supporting autonomous learning. However, concerns about a

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17. Faculty and Student Perceptions of Generative AI Use, ChatGPT and Academic Integrity: Connecting Findings to Assessment Redesign

    Han Nee Chong, Eugene Guillian · 2026 · Intersection: A Journal at the Intersection of Assessment and Learning

    This study examines faculty and student perceptions of generative artificial intelligence (GenAI), particularly ChatGPT, and its implications for academic integrity and assessment design in higher education. Using a cross-sectional survey design, quantitative and qualitative data were collected from 82 faculty and 190 students to explore attitudes, experiences, and practices related to AI use. Findings indicate broad recognition of GenAI’s potential to enhance learning efficiency and feedback, alongside concerns about academic dishonesty and the erosion of critical thinking and writing skills. From an assessment perspective, these concerns highlight the importance of designing tasks that mak

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18. Communicating academic integrity policy in the age of generative AI

    Natalia Vasilendiuc, Emilia Sercan · 2026 · Quality Assurance in Education

    Purpose: This study aims to examine how students and teaching staff perceive and enact academic-integrity policies in Romanian universities under the normative uncertainty created by generative artificial intelligence (AI). Design/methodology/approach: Parallel online questionnaires were completed by 786 students and 472 teaching-staff members at four public universities; closed-item analyses were complemented by thematic content analysis of open responses. Findings: Teaching staff evaluated integrity infrastructure more positively, while students perceived more examination and AI-assisted cheating. Student reporting was rare; teaching staff reporting intentions followed hierarchical interna

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19. Generative AI in Academic Chinese Writing for Native speakers: A Case Study of ChatGPT and Ernie Bot

    Su Yuan, Qiyao Ma, Ka Ching Chau, et al. · 2026 · STiLE - Scholarship of Teaching in Language Education

    With the rise of Generative Artificial Intelligence (GenAI), academic writing has undergone significant changes, prompting educators to adapt their teaching methods. This qualitative case study explores the integration of GenAI in academic Chinese writing education for native Chinese speakers within the context of Hong Kong universities. Through systematic evaluation of ChatGPT 3.5 and Ernie Bot 3.5 across academic writing tasks from a Chinese communication skills course, this study examines how GenAI tools can help students enhance their academic writing skills. GenAI performance is evaluated across content, structure, and language use in academic Chinese writing. Findings indicate that whi

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20. Navigating the AI-Education Nexus: Mitigating Academic Integrity Challenges in the Era of Generative AI

    Patrick Buckland, Marian Carcary · 2026 · Irish Journal of Technology Enhanced Learning

    Generative AI is reshaping teaching and assessment in higher education, but its capacity for misuse raises new concerns about academic integrity. This study examines approaches that higher education educators can take to safeguard honesty in students’ academic work while also harnessing AI to enrich learning and evaluation. Based on a systematic literature review (SLR) method, this study identified five interconnected strategic themes: (1) Policy and Guidelines for AI in Education; (2) AI Education and Training; (3) Attitudes towards GenAI in Education; (4) Transparency, Communication, and Engagement; and (5) Assessment Design and Format. These elements are integrated into a holistic concept

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21. Generative AI in Islamic Education: A Maqāṣid-Based Framework for Curriculum, Assessment and Academic Integrity

    Kamel Hayoune · 2026 · Islamic Reports

    Generative artificial intelligence (AI) has entered Islamic schools, seminaries and universities faster than the institutions can govern it. Students use chatbots to explain verses, draft essays and prepare for examinations, while teachers lack shared rules on what is permitted, how to disclose it and how to assess learning fairly. This paper proposes a practical framework that grounds those decisions in the objectives of the Sharia (maqāṣid al-sharīʿa) rather than in generic ethics alone. Using an analytical synthesis of recent evidence on generative AI in education, research on assessment and academic integrity, international governance guidance, and the maqāṣid literature, the paper maps

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22. From Academic Integrity to Institutional Stewardship: A Reflexive and Responsible Innovation Paradigm for Generative AI in Higher Education

    Navid Nazhand · 2026 · Education Sciences

    Generative artificial intelligence (GenAI) has diffused through higher education faster than institutions have been able to govern it, reshaping the conditions under which universities produce knowledge, judgement, credentials, and public trust. Current responses (prohibition, detection, and accommodation) fall short of a settled governance posture, and existing frameworks, from AI ethics principles to standard Responsible Research and Innovation (RRI) models, are not calibrated to higher education’s distinctive epistemic, formative, and public-good missions. This article addresses that gap through a disciplined conceptual synthesis drawing on RRI, reflexive governance, and higher education

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