Folio Search · free preview

Papers on “generative AI ChatGPT education academic integrity”

Live results from Semantic Scholar, CrossRef and OpenAlex. No account needed to look.

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

   Damian Okaibedi Eke · 2023 · Journal of Responsible Technology · 461 cites

   Save to my library →

2. 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 cites

   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

   Save to my library →

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

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

   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

   Save to my library →

4. 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

   Save to my library →

5. 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

   Save to my library →

6. 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

   Save to my library →

7. 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

   Save to my library →

8. 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

   Save to my library →