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Caner Dilber; Ismail Yosumaz – Journal of Academic Ethics, 2026
The rapid advancement of language translation tools and generative artificial intelligence applications has significantly facilitated the production of academic research while simultaneously introducing new challenges to maintaining academic ethics and detecting plagiarism. This study examines how plagiarism rates vary when academic texts are…
Descriptors: Plagiarism, Translation, Computer Software, Identification
Nadi Suprapto; Nurhasan; Roy Martin Simamora; Ali Mursid; M. Arif Al Ardha – Journal of Academic Ethics, 2025
This study analyzes predominant themes and disciplinary and methodological trends in academic integrity and misconduct research. It utilizes bibliometric analysis to explore prevalent themes and interdisciplinary intersections within discussions based on Scopus metadata. R Studio, which uses "biblioshiny" software, is employed to…
Descriptors: Cheating, Plagiarism, Artificial Intelligence, Integrity
Karen Paullet; Jamie Pinchot; Evan Kinney; Tyler Stewart – Information Systems Education Journal, 2025
Generative AI tools such as ChatGPT are now in widespread use and are often utilized by students to help in creating writing assignments intended to be written entirely by the student. This has spurred the need for AI detection tools such as GPTZero. This study sought to determine the accuracy of GPTZero's AI detection in identifying whether…
Descriptors: Artificial Intelligence, Writing Assignments, Deception, Program Effectiveness
Dickson Okoree Mireku; Prosper Dzifa Dzamesi; Brandford Bervell – Research Ethics, 2024
The purpose of this study was to map the distribution of publications on plagiarism among higher educational institutions in sub-Saharan Africa (SSA). Studies reviewed were based on 171 plagiarism related publications within a decade (2012-2022). Findings revealed that most plagiarism related articles were published in 2016. Additionally, a…
Descriptors: Foreign Countries, Higher Education, Plagiarism, Literature Reviews
Cecilia Ka Yuk Chan – Education and Information Technologies, 2025
This novel study explores "AI-giarism," an emergent form of academic dishonesty involving AI and plagiarism, within the higher education context. The objective of this study is to investigate students' perception of adopting generative AI for research and study purposes, and their understanding of traditional plagiarism and their…
Descriptors: Higher Education, College Students, Artificial Intelligence, Plagiarism
Jon M. Wargo – Early Childhood Education Journal, 2025
Questioning the common practice of treating texts as property that can be stolen and instead exploring the social and rhetorical dimensions that define what is owned (and what is not), as well as what can be taken and appropriated, I drew on data from a yearlong qualitative investigation of young children writing with technology to interrogate how…
Descriptors: Emergent Literacy, Beginning Writing, Young Children, Writing Processes
Shushanta Pudasaini; Luis Miralles-Pechuán; David Lillis; Marisa Llorens Salvador – Journal of Academic Ethics, 2025
A survey conducted in 2023 surveyed 3,017 high school and college students. It found that almost one-third of them confessed to using ChatGPT for assistance with their homework. The rise of Large Language Models (LLMs) such as ChatGPT and Gemini has led to a surge in academic misconduct. Students can now complete their assignments and exams just…
Descriptors: High School Students, College Students, Artificial Intelligence, Cheating
Traci A. Giuliano – Teaching of Psychology, 2024
Background: Because plagiarism is such a common form of academic dishonesty, many instructors are seeking ways to effectively teach students to avoid plagiarism. Objective: The current study tested the effectiveness of a 3-pronged intervention to teach students in an upper-level psychology course to better understand plagiarism. Method: The…
Descriptors: Undergraduate Students, Plagiarism, Psychology, Intervention
Kelli Trei; Sara Benson; Siyao Cheng – portal: Libraries and the Academy, 2025
This study examines whether graduate students in STEM fields at an R1 institution understand copyright law. Thirty graduate students participated in semi-structured interviews related to copyright and ownership. This study revealed that these students often conflate issues around copyright and plagiarism and have little understanding of their own…
Descriptors: Graduate Students, Knowledge Level, Copyrights, Plagiarism
Nicholas R. Werse; Joshua Caleb Smith – Impacting Education: Journal on Transforming Professional Practice, 2025
In this article, the authors explore the concerns surrounding academic dishonesty related to generative artificial intelligence (GAI). The authors argue that while there are valid worries about students using GAI in ways the displace student work, these anxieties are not new and have been observed with previous disruptive technologies such as the…
Descriptors: Cheating, Artificial Intelligence, Anxiety, Teacher Role
Fawad Javed; Zain Uddin Ahmed – Journal of Academic Ethics, 2025
The objective of this study is to review the author/submission guidelines of dental journals and assess their plagiarism policies. A questionnaire based on seven variables was used to extract plagiarism-checking guidelines from the author/submission guidelines of the 50 dental journals subjected to scrutiny. Author/submission guidelines of two…
Descriptors: Plagiarism, Writing for Publication, Guidelines, Periodicals
Ramesh Chander Sharma; Suman Kalyan Panja – Open Praxis, 2025
Generative Artificial Intelligence (GAI) introduces new opportunities for society. While some universities have adopted GAI with a more hostile stance, others have done so with a more progressive perspective. In light of this contradiction, the main query is what is causing this controversy. The ethical issues surrounding GAI and academic…
Descriptors: Artificial Intelligence, Ethics, Plagiarism, Cheating
Amy Elizabeth Mendes – ProQuest LLC, 2023
Thousands of students and hundreds of institutions participate in intercollegiate forensics competitions each year. Previous research has discovered instances of plagiarism by competitors on multiple occasions, despite this being against the rules of competition and a violation of academic norms. The purpose of this pragmatic qualitative research…
Descriptors: Plagiarism, College Students, Competition, Intervention
Pasty Asamoah; John Serbe Marfo; Matilda Kokui Owusu-Bio; Daniel Zokpe – Education and Information Technologies, 2024
In this brief we shift the current academic integrity conversation from "detecting and preventing plagiarism" to "examining how plagiarized contents can be corrected with an objective knowledge of the number of words to modify and properly acknowledged". We proposed a simple, yet useful and powerful mathematical model that is…
Descriptors: Error Correction, Plagiarism, Integrity, Prevention
Mohammad Hosseini; David B. Resnik – Research Ethics, 2025
Journals and publishers are increasingly using artificial intelligence (AI) to screen submissions for potential misconduct, including plagiarism and data or image manipulation. While using AI can enhance the integrity of published manuscripts, it can also increase the risk of false/unsubstantiated allegations. Ambiguities related to journals' and…
Descriptors: Artificial Intelligence, Plagiarism, Writing for Publication, Periodicals

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