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Research papers on Generative AI in education

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

    Rosario Michel-Villarreal, E. Vilalta-perdomo, D. Salinas-Navarro, et al. · 2023 · Education Sciences · 778 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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  3. The impact of generative AI on academic integrity of authentic assessments within a higher education context

    Alexander K. Kofinas, C. Tsay, D. Pike · 2025 · Br. J. Educ. Technol. · 223 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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  4. Generative artificial intelligence (Gen-AI) in pharmacy education: Utilization and implications for academic integrity: A scoping review

    R. Mortlock, C. Lucas · 2024 · Exploratory Research in Clinical and Social Pharmacy · 79 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, identify

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  5. Academic Integrity In The Age Of Generative AI: Perceptions And Responses Of Vietnamese EFL Teachers

    C. Ngo, T. Tran, T. Nguyen · 2024 · Teaching English With Technology · 66 citations

    This study examines the perceptions and responses of Vietnamese teachers of English as a Foreign Language (EFL) to academic integrity concerns that arise from the use of AI, specifically chatbots like ChatGPT, in foreign language education. The study employed an open-ended survey to collect data from 31 Vietnamese EFL teachers who were asked to share their views on AI-based academic dishonesty, identify perceived causes, outline consequences for students engaging in AI-based plagiarism, and articulate their pedagogical responses to the issue. The study found that teachers primarily attributed students’ AI-driven plagiarism to a deficiency in original ideas, poor learning attitudes and motiva

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  6. 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 · 56 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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  8. Generative AI in Higher Education: Educators' Perspectives on Academic Learning and Integrity

    Naghmeh M. Aghaee, John Vrågård, Freddie Brorsson · 2024 · European Conference on e-Learning · 17 citations

    Generative Artificial Intelligence (Gen AI), exemplified by models such as ChatGPT, has rapidly advanced, becoming a significant force in various sectors, including higher education. ChatGPT, a leading application of Gen AI, utilizes large language models (LLMs) to generate human-like text, providing capabilities that range from answering complex questions to facilitating software development. As these tools become increasingly integrated into academic environments, their impact on teaching and learning processes has become more under focus. However, there are not many studies focusing on the impact of such systems on students’ performance and the use of such systems. This study therefore ex

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  9. Generative AI in Science Education: A Learning Revolution or a Threat to Academic Integrity? A Bibliometric Analysis

    M. D. H. Wirzal, N. A. H. Md Nordin, N. S. Abd Halim, et al. · 2024 · Jurnal Penelitian dan Pengkajian Ilmu Pendidikan: e-Saintika · 14 citations

    The integration of generative artificial intelligence (AI) in Science, Technology, Engineering, and Mathematics (STEM) education presents transformative opportunities alongside significant challenges. This study investigates the dual impact of generative AI on STEM learning outcomes and academic integrity through a comprehensive bibliometric analysis employing co-citation, keyword analysis, and trend mapping. The results reveal that AI tools such as ChatGPT have revolutionized personalized learning by offering tailored feedback, enhancing critical thinking, and improving student engagement. However, these advancements are tempered by concerns over academic misconduct, particularly plagiarism

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  10. Modeling the Influence of Generative AI Writing Tools on Academic Integrity and Writing Proficiency in Higher Education: A Structural Equation Modeling Approach

    O. Alkhatib, Sadaf Raja, Asadullah · 2025 · Research Journal for Social Affairs · 7 citations

    The integration of Generative AI writing tools in higher education has transformed the landscape of academic writing, presenting both opportunities and challenges for teachers and students. This study examines the effect of the GenAI writing tools on the academic integrity and the writing proficiency of students using a quantitative cross-sectional survey design. The study targeted undergraduate students in Punjab, Pakistan, utilizing a stratified purposive sampling strategy to select 400 participants from six representative universities (three public and three private). All participants were active users of GenAI tools such as ChatGPT, Grammarly, QuillBot and Google Gemini. Data were analyz

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  11. Redesigning Assessments in Business Education: Addressing Generative AI's Impact on Academic Integrity

    Robin Ghosh · 2024 · International Journal of Science and Research (IJSR) · 4 citations

    Generative AI technologies, including ChatGPT, DALL·E, and others, are increasingly prevalent in tertiary business education. While these tools offer enhanced learning opportunities and aid creativity, they also introduce new challenges for assessment design, raising concerns about academic integrity, skill development, and learning outcomes. This paper examines the implications of generative AI on traditional assessment methods in tertiary business education and advocates for a reconsideration of assessment frameworks to ensure academic integrity and authenticity in student learning. Drawing from secondary data, studies, and educational reports, the paper offers a set of recommendations for

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  12. Generative AI and Academic Integrity in Higher Education

    Sathy Akter · 2026 · British Journal of Arts and Humanities · 4 citations

    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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  13. Adoption of Generative AI and Learning Analytics for Personalized Learning in Nigerian Higher Education: Effects on Student Engagement, Learning Outcomes, and Academic Integrity

    Ayonote Elenode · 2026 · Engineering and Applied Sciences · 2 citations

    This study examines the integration of generative artificial intelligence (GenAI) and learning analytics (LA) in fostering personalized learning within Nigerian higher education institutions. Specifically, it explores how these emerging technologies influence student engagement, academic performance, and perceptions of academic integrity in digitally mediated learning environments. A mixed-method research design was adopted, involving 420 undergraduate students and 60 academic staff drawn from three Nigerian universities. Quantitative data were collected through structured questionnaires assessing GenAI usage patterns, learning analytics engagement, levels of digital literacy, and integrity

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  14. 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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  15. ANALISIS DAMPAK PENGGUNAAN GENERATIVE AI (CHATGPT) TERHADAP INTEGRITAS AKADEMIK MAHASISWA DI PENDIDIKAN TINGGI

    Jadiaman Parhusip, Olga Noviola Agustin, Bryan Desmonda Ferdinand, et al. · 2025 · TRANSFORMASI · 1 citations

    The rapid adoption of Generative AI, such as ChatGPT, in higher education has sparked significant debate regarding its impact on academic integrity. This research aims to analyze the ethical and social impacts of using Generative AI on student academic integrity. This study uses the Systematic Literature Review (SLR) method. Literature was searched from databases like Google Scholar and Scopus published between 2022 and 2025. After applying inclusion and exclusion criteria, 10 relevant articles were selected for synthesis. The results identify several key themes: (1) Increased risk of novel forms of plagiarism and academic dishonesty, (2) a potential decline in critical thinking and original

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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. Impact of Generative Artificial Intelligence (ChatGPT) on Students’ Critical Thinking Skills and Academic Integrity in Higher Education

    Seemeen Umar Khan Yousufzai, Zunaira Faraz, Mohamed Abbad, et al. · 2026 · Social Science Review Archives

    Generative Artificial Intelligence (AI) tools, such as ChatGPT, are increasingly integrated into higher education. While these tools offer convenience and learning support, concerns exist regarding their impact on students’ critical thinking skills and academic integrity. This study investigates the influence of ChatGPT usage on university students’ cognitive and ethical outcomes, focusing on critical thinking and adherence to academic integrity. A quantitative research design was employed, surveying 250 undergraduate and postgraduate students. Data were collected using a structured Likert-scale questionnaire covering ChatGPT usage, critical thinking, and academic integrity. Reliability was

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

    Han-Nee Chong, E. 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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  19. Cheating, Chatbots, and Change: A Bibliometric Mapping of Academic Integrity and Generative AI in Higher Education

    Hanifah Daluma, Joel T. Aclao · 2026 · Journal of Education and Learning Reviews

    Background and Aim: Generative artificial intelligence (GenAI) tools such as ChatGPT have rapidly entered higher education, reshaping how students write, learn, and are assessed, while intensifying concerns about plagiarism, contract cheating, and academic misconduct. Despite fast-growing commentary and empirical work, bibliometric evidence remains limited on how research at the intersection of academic integrity, GenAI, and higher education has organized itself in the post-ChatGPT period. This study maps publication volume, thematic structure, collaboration patterns, and early visibility indicators in this integrity-focused GenAI literature from 2023 to 2025. Materials and Methods: A biblio

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  20. Generative AI and Academic Integrity in Higher Education: Challenges and Future Directions

    Dr. G. Purushothaman, Dr. S. Ganapathy, Mr. Saurabh Jaiswal, Mr. Thanga Kumaran M · 2026 · International Journal of Advanced Research in Science Communication and Technology

    The public release of ChatGPT in late 2022, and the wave of generative artificial intelligence (GenAI) tools that followed it, has unsettled long-standing assumptions about how learning is demonstrated and assessed in higher education. Essays, reports, code, and even reflective writing can now be produced in seconds by systems whose output is fluent, personalised, and largely indistinguishable from student work. This paper examines the resulting collision between GenAI and academic integrity from a governance and assurance perspective. Drawing on the rapidly growing literature published since 2022, it maps the principal challenges facing institutions: the unreliability and demonstrated bias

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  21. Generative AI in mathematics education: Considerations for academic integrity and assessment strategies

    Kunti Robi'atul Mahmudah, N. Peni, Faida Musa'ad, et al. · 2026 · Jurnal Elemen

    The rapid advancement of generative artificial intelligence (GenAI), particularly tools like ChatGPT, has introduced both opportunities and challenges for academic assessment in higher education. This systematic review explores how GenAI has influenced academic integrity concerns and highlights the assessment redesign strategies proposed or implemented in response. Drawing from 18 peer-reviewed articles published between 2022 and 2025, the review identifies seven key thematic areas: integration of GenAI in educational settings, pedagogical opportunities, integrity-related challenges, impacts on critical thinking and originality, educator and student perspectives, practical implementation out

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  22. Generative AI Adoption in Indonesian Higher Education: A Sociotechnical Analysis of Student Engagement, Digital and AI Literacy, and Academic Integrity

    S. Sudrajat, Bagaskara Nur Rochmansyah, Leonita Leonita, et al. · 2026 · Daengku: Journal of Humanities and Social Sciences Innovation

    Generative artificial intelligence (GenAI) has rapidly entered higher education and changed how students access information, complete academic tasks, and engage with learning. However, GenAI adoption cannot be understood only as individual technology use because it is also shaped by literacy, academic integrity, institutional rules, and pedagogical context. This study analyzes GenAI adoption in Indonesian higher education through a sociotechnical perspective. The study used a descriptive-analytical design based on an Indonesian higher education subset extracted from a public global survey dataset on students’ early perceptions of ChatGPT. After institutional-location filtering, the final ana

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  23. Artificial Intelligence Governance in Indonesian Education: Regulatory Analysis and the Strengthening of Academic Integrity in the Era of Generative AI

    Rizki Auliadi, Mikraj Mikraj · 2026 · Jurnal Ilmiah Guru Madrasah

    The development of Generative Artificial Intelligence (Generative AI) technologies, such as ChatGPT, Gemini, Claude, and Copilot, has brought significant transformation to the Indonesian education sector. These technologies offer numerous benefits, including supporting personalized learning, enhancing the efficiency of educational administration, and facilitating the retrieval and processing of academic information. However, the increasing use of AI has also raised concerns regarding academic integrity, including AI-assisted plagiarism, information fabrication, excessive dependence on technology, and the decline of students’ critical thinking skills. These challenges highlight the necessity

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  24. 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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