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Siraprapa Kotmungkun; Wichuta Chompurach; Piriya Thaksanan – English Language Teaching Educational Journal, 2024
This study explores the writing quality of two AI chatbots, OpenAI ChatGPT and Google Gemini. The research assesses the quality of the generated texts based on five essay models using the T.E.R.A. software, focusing on ease of understanding, readability, and reading levels using the Flesch-Kincaid formula. Thirty essays were generated, 15 from…
Descriptors: Plagiarism, Artificial Intelligence, Computer Software, Essays
Cheers, Hayden; Lin, Yuqing; Yan, Weigen – Informatics in Education, 2023
Source code plagiarism is a common occurrence in undergraduate computer science education. Many source code plagiarism detection tools have been proposed to address this problem. However, most of these tools only measure the similarity between assignment submissions, and do not actually identify which are suspicious of plagiarism. This work…
Descriptors: Plagiarism, Assignments, Computer Software, Computer Science Education
Christophe O. Soulage; Fabien Van Coppenolle; Fitsum Guebre-Egziabher – Advances in Physiology Education, 2024
Artificial intelligence (AI) has gained massive interest with the public release of the conversational AI "ChatGPT," but it also has become a matter of concern for academia as it can easily be misused. We performed a quantitative evaluation of the performance of ChatGPT on a medical physiology university examination. Forty-one answers…
Descriptors: Medical Students, Medical Education, Artificial Intelligence, Computer Software
Davoodifard, Mahshad – Studies in Applied Linguistics & TESOL, 2022
While investigating plagiarism is relevant in different fields, verification of original authorship has also attracted attention in academia and L2 learning and assessment contexts. Generally associated with academic misconduct and dishonesty, plagiarism in writing can take many shapes and be hard to detect. In addition to being a very…
Descriptors: Plagiarism, Second Language Learning, Second Language Instruction, Authors
Maertens, Rien; Van Petegem, Charlotte; Strijbol, Niko; Baeyens, Toon; Jacobs, Arne Carla; Dawyndt, Peter; Mesuere, Bart – Journal of Computer Assisted Learning, 2022
Background: Learning to code is increasingly embedded in secondary and higher education curricula, where solving programming exercises plays an important role in the learning process and in formative and summative assessment. Unfortunately, students admit that copying code from each other is a common practice and teachers indicate they rarely use…
Descriptors: Plagiarism, Benchmarking, Coding, Computer Science Education
Ji Eun Lee; Unkyoung Maeng – Journal of Pan-Pacific Association of Applied Linguistics, 2023
This study explored high school students' perceptions of using AI chatbots in English learning. Specifically, it aimed to gauge the breadth of chatbot utilization and discern perceptions surrounding potential challenges linked to their use. Thirty students from a high school took part in the survey. Data analysis involved frequency, mean and an…
Descriptors: Ethics, Student Attitudes, High School Students, Artificial Intelligence
Tim Vandenhoek – International Journal of Education and Development using Information and Communication Technology, 2023
Plagiarism in academic writing is known to be an issue of concern for educators, administrators, and students alike. Using self-reporting studies and plagiarism detection software, previous research has established that plagiarism in university-level academic writing is relatively common amongst the work of L1 and particularly L2 writers and that…
Descriptors: Plagiarism, Writing (Composition), College Students, Virtual Classrooms
Source Code Plagiarism Detection in Academia with Information Retrieval: Dataset and the Observation
Karnalim, Oscar; Budi, Setia; Toba, Hapnes; Joy, Mike – Informatics in Education, 2019
Source code plagiarism is an emerging issue in computer science education. As a result, a number of techniques have been proposed to handle this issue. However, comparing these techniques may be challenging, since they are evaluated with their own private dataset(s). This paper contributes in providing a public dataset for comparing these…
Descriptors: Plagiarism, Computer Science Education, Comparative Analysis, Problem Solving
Rogerson, Ann M.; McCarthy, Grace – International Journal for Educational Integrity, 2017
A casual comment by a student alerted the authors to the existence and prevalence of Internet-based paraphrasing tools. A subsequent quick Google search highlighted the broad range and availability of online paraphrasing tools which offer free 'services' to paraphrase large sections of text ranging from sentences, paragraphs, whole articles, book…
Descriptors: Plagiarism, Computer Software, Incidence, Cheating
El Rassi, Mary Ann Barbour – International Association for Development of the Information Society, 2019
It has long been debated whether the Open-Book-Open-Web exam was useful and efficient as the traditional closed book exams. Some scholars and practitioners have doubted the efficiency and the possibility of cheating in the OBOW as it is not directly monitored. This paper tends to investigate the effectiveness of OBOW exams by comparing them with…
Descriptors: Developing Nations, Test Format, Tests, Cheating
Wrigley, Stuart – Active Learning in Higher Education, 2019
This article discusses and challenges the increasing use of plagiarism detection services such as Turnitin and Grammarly by students, arguing that the increasingly online nature of composition is having a profound effect on student composition processes. This dependence on the Internet is leading to a strategy I term 'de-plagiarism', in which…
Descriptors: Plagiarism, Essays, Writing Processes, Computer Software
Mayes, Robin James – ProQuest LLC, 2017
This empirical exploratory study quantitatively analyzed content similarity indices (potential plagiarism) from a corpus consisting of 360 dissertations and 360 published articles. The population was defined using the filtering search criteria human resource development, training and development, organizational development, career development, or…
Descriptors: Plagiarism, Computer Software, Doctoral Dissertations, Regression (Statistics)
Zhang, Dongyang; Joy, Mike; Cosma, Georgina; Boyatt, Russell; Sinclair, Jane; Yau, Jane – Assessment & Evaluation in Higher Education, 2014
There has been much research and discussion relating to variations in plagiaristic activity observed in students from different demographic backgrounds. Differences in behaviour have been noted in many studies, although the underlying reasons are still a matter of debate. Existing work focuses mainly on textual plagiarism, and most often derives…
Descriptors: Foreign Countries, Plagiarism, Computer Software, College Students
Tennyson, Matthew F. – ProQuest LLC, 2013
Authorship attribution of source code is the task of deciding who wrote a program, given its source code. Applications include software forensics, plagiarism detection, and determining software ownership. A number of methods for the authorship attribution of source code have been presented in the past. A review of those existing methods is…
Descriptors: Authors, Programming, Computer Software, Plagiarism
Fawcett, Hannah; Oldfield, Jeremy – Teaching in Higher Education, 2016
Previous research suggests that audio feedback may be an important mechanism for facilitating effective and timely assignment feedback. The present study examined expectations and experiences of audio and written feedback provided through "turnitin for iPad®" from students within the same cohort and assignment. The results showed that…
Descriptors: Audio Equipment, Feedback (Response), Computer Software, Written Language
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