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Chiang, Feng-Kuang; Zhu, Dan; Yu, Wenhao – Journal of Computer Assisted Learning, 2022
Background: During the COVID-19 pandemic, online learning has played an increasingly crucial role in the educational system. Academic dishonesty (AD) in online learning is a challenging problem that represents a complex psychological and social phenomenon for learners. However, there is a lack of comprehensive and systematic reviews of AD in…
Descriptors: Cheating, Research Reports, Intervention, COVID-19
Xuandong Zhao – ProQuest LLC, 2024
The rapid advancement of powerful Large Language Models (LLMs), such as ChatGPT and Llama, has revolutionized the world by bringing new creative possibilities and enhancing productivity. However, these advancements also pose significant challenges and risks, including the potential for misuse in the form of fake news, academic dishonesty,…
Descriptors: Computational Linguistics, Intellectual Property, Artificial Intelligence, Productivity
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Silvia Sierra-Martínez; María-Esther Martínez-Figueira; María Dolores Castro Pais; Teresa Pessoa – British Educational Research Journal, 2024
Academic integrity is part of the process that explains the communication of information in an ethical manner. Although the prevalence of dishonest acts at university has been noted, it is an aim of the educational system to analyse what motivates them from an age prior to their incorporation into university studies. The aim of this work is to…
Descriptors: Plagiarism, Photography, Participatory Research, High School Students
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Mulholland, Mary-Lee – Journal of College and Character, 2020
With the perceived increase in plagiarism in post-secondary institutions, there has been a simultaneous increase in research and analysis on the issue emerging from multiple fields including education, humanities, social science, business and management, sciences, and the media. The focus of this research ranges from the frequency of cases,…
Descriptors: Plagiarism, Ethics, Moral Issues, Educational Policy
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Ruiperez-Valiente, Jose A.; Munoz-Merino, Pedro J.; Alexandron, Giora; Pritchard, David E. – IEEE Transactions on Learning Technologies, 2019
One of the reported methods of cheating in online environments in the literature is CAMEO (Copying Answers using Multiple Existences Online), where harvesting accounts are used to obtain correct answers that are later submitted in the master account which gives the student credit to obtain a certificate. In previous research, we developed an…
Descriptors: Computer Assisted Testing, Tests, Online Courses, Identification
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Munoz, Albert; Mackay, Jonathon – Journal of University Teaching and Learning Practice, 2019
Online testing is a popular practice for tertiary educators, largely owing to efficiency in automation, scalability, and capability to add depth and breadth to subject offerings. As with all assessments, designs need to consider whether student cheating may be inadvertently made easier and more difficult to detect. Cheating can jeopardise the…
Descriptors: Cheating, Test Construction, Computer Assisted Testing, Classification
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Demir, Ergul – Eurasian Journal of Educational Research, 2018
Purpose: The answer-copying tendency has the potential to detect suspicious answer patterns for prior distributions of statistical detection techniques. The aim of this study is to develop a valid and reliable measurement tool as a scale in order to observe the tendency of university students' copying of answers. Also, it is aimed to provide…
Descriptors: College Students, Cheating, Test Construction, Student Behavior
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Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
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Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis