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Elkhatat, Ahmed M. – International Journal for Educational Integrity, 2023
Academic plagiarism is a pressing concern in educational institutions. With the emergence of artificial intelligence (AI) chatbots, like ChatGPT, potential risks related to cheating and plagiarism have increased. This study aims to investigate the authenticity capabilities of ChatGPT models 3.5 and 4 in generating novel, coherent, and accurate…
Descriptors: Artificial Intelligence, Plagiarism, Integrity, Models
Cheers, Hayden; Lin, Yuqing – Computer Science Education, 2023
Background and Context: 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, such tools do not identify plagiarism, nor suggest what assignment submissions are suspicious of plagiarism. Source code plagiarism…
Descriptors: Plagiarism, Programming, Computer Science Education, Identification
Luke Parker; Chris Carter; Alice L. Karakas; Jane A. Loper; Ahmad Sokkar – AERA Online Paper Repository, 2024
In 2023, ChatGPT emerged as a transformative force in education, igniting widespread interest across academia. This paper rigorously investigates ChatGPT's impact on higher education using a mixed-methods approach, comparing its (ChatGPT) performance with real students' work in undergraduate assignments. Key findings reveal ChatGPT consistently…
Descriptors: Artificial Intelligence, Technology Education, Higher Education, Influence of Technology
Elkhatat, Ahmed M.; Elsaid, Khaled; Almeer, Saeed – International Journal for Educational Integrity, 2021
One of the main goals of assignments in the academic environment is to assess the students' knowledge and mastery of a specific topic, and it is crucial to ensure that the work is original and has been solely made by the students to assess their competence acquisition. Therefore, Text-Matching Software Products (TMSPs) are used by academic…
Descriptors: Plagiarism, Identification, Assignments, Computer Software
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
Yovav Eshet – Education and Information Technologies, 2024
The COVID-19 pandemic has forced higher education institutions worldwide to shift from face-to-face (F2F) to emergency remote teaching (ERT), which has led to an increased concern about academic integrity. This study examines the relationship between learning environment and academic integrity via plagiarism detection software in different…
Descriptors: Plagiarism, Integrity, Ethics, Student Behavior
Martínez, Salvador; Wimmer, Manuel; Cabot, Jordi – Computer Science Education, 2020
Background and Context: Reports suggest plagiarism is a common occurrence in universities. While plagiarism detection mechanisms exist for textual artifacts, this is less so for non-code related ones such as software design artifacts like models, metamodels or model transformations. Objective: To provide an efficient mechanism for the detection of…
Descriptors: Plagiarism, Identification, Computer Software, Computer Uses in Education
Eaton, Sarah Elaine; Crossman, Katherine; Behjat, Laleh; Yates, Robin Michael; Fear, Elise; Trifkovic, Milana – Journal of Academic Ethics, 2020
This institutional self-study investigated the use of text-matching software (TMS) to prevent plagiarism by students in a Canadian university that did not have an institutional license for TMS at the time of the study. Assignments from a graduate-level engineering course were analyzed using iThenticate®. During the initial phase of the study,…
Descriptors: Computer Software, Plagiarism, College Students, Engineering Education
Schneider, Johannes; Bernstein, Abraham; Brocke, Jan vom; Damevski, Kostadin; Shepherd, David C. – IEEE Transactions on Learning Technologies, 2018
All methodologies for detecting plagiarism to date have focused on the final digital "outcome", such as a document or source code. Our novel approach takes the creation process into account using logged events collected by special software or by the macro recorders found in most office applications. We look at an author's interaction…
Descriptors: Plagiarism, Assignments, Programming, Computer Software
Meyer, Patricia – ProQuest LLC, 2018
This study explored the adoption level of a specific plagiarism detection software by college professors in a classroom environment. As universities and colleges struggle with the issue of plagiarism and maintaining high standards of integrity, technology tools have been created and provided to assist faculty in identifying if a student has…
Descriptors: Plagiarism, Computer Software, College Faculty, College Students
Adam Wong; Edmund Wut – International Association for Development of the Information Society, 2022
As lessons were forced to switch to online or hybrid mode during COVID-19, educators need to apply tools to foster engagement inside and outside the classroom. Screencasting software enables teachers to evaluate students' learning outcomes in compensation for the lack of face-to-face interactions. This study investigated the use of…
Descriptors: Information Science Education, Information Management, Management Systems, Educational Change
Ersan, Ceyhun; Uslu, Banu – International Journal of Technology in Education and Science, 2020
In this study, the effect of science and research ethics course on preschool teacher candidates' possible plagiarism behaviors was examined. Fifteen teacher candidates were asked to prepare a written assignment (pre-test) before the start of the course. Similarly, a second written assignment (post-test) was taken at the end of the course which…
Descriptors: Plagiarism, Prevention, Preservice Teachers, Homework
Edwards, John; Hart, Kaden; Shrestha, Raj – Journal of Educational Data Mining, 2023
Analysis of programming process data has become popular in computing education research and educational data mining in the last decade. This type of data is quantitative, often of high temporal resolution, and it can be collected non-intrusively while the student is in a natural setting. Many levels of granularity can be obtained, such as…
Descriptors: Data Analysis, Computer Science Education, Learning Analytics, Research Methodology
Norris, Mark – Research in Higher Education Journal, 2019
The delivery of online university courses has continued to grow for more than a decade. New advances in technology have made the efficient delivery of courses possible, as well as increasing the collections of tools for students to cheat. Cheating results in the atrophy of the student's academic integrity, it has the potential to damage a…
Descriptors: Cheating, Online Courses, Integrity, College Students
Orlando, Joanne; Hanham, Jose; Ullman, Jacqueline – Australasian Journal of Educational Technology, 2018
Current pedagogical practices have seen the rapid spread of technological tools that carry out tasks on behalf of the learner; we use the term "technological proxy" to refer to these tools. A popular technological proxy used by students worldwide is a text-matching software called Turnitin. Turnitin alerts users to sections of an…
Descriptors: Academic Discourse, Self Efficacy, Goal Orientation, Feedback (Response)
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