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Jill Oeding; Theresa Gunn; Jamie Seitz – Open Praxis, 2024
This quantitative study is designed to help educational institutions and instructors make informed decisions regarding the use of online proctoring software. The researchers studied the impact of proctoring software in online courses by comparing the final grades of two groups of online, undergraduate students who took the same online course with…
Descriptors: Supervision, Computer Software, Online Courses, Grades (Scholastic)
Jonathan M. Golding; Anne Lippert; Jeffrey S. Neuschatz; Ilyssa Salomon; Kelly Burke – Teaching of Psychology, 2025
Background: The advent of generative-artificial intelligence (AI) applications introduces new challenges for colleges. Importantly, the growth of these applications requires faculty to adjust their pedagogy to account for the changing technological landscape. Objective: As colleges wrestle with the implications of these applications, it is…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Software, Humanities
Daniel Holcombe – Hispania, 2025
Accompanying the recent rise in cautious popularity surrounding Generative Artificial Intelligence (Gen-AI), some language educators are exploring innovative linguistic interactions with Gen-AI. Seeking to add a literature approximation to such criticism, this article explores two activities that feature Gen-AI in undergraduate literature courses.…
Descriptors: Undergraduate Students, Artificial Intelligence, Computer Software, Cheating
Chad C. Tossell; Nathan L. Tenhundfeld; Ali Momen; Katrina Cooley; Ewart J. de Visser – IEEE Transactions on Learning Technologies, 2024
This article examined student experiences before and after an essay writing assignment that required the use of ChatGPT within an undergraduate engineering course. Utilizing a pre-post study design, we gathered data from 24 participants to evaluate ChatGPT's support for both completing and grading an essay assignment, exploring its educational…
Descriptors: Student Attitudes, Computer Software, Artificial Intelligence, Grading
Dawson, Phillip; Sutherland-Smith, Wendy; Ricksen, Mark – Assessment & Evaluation in Higher Education, 2020
Contract cheating happens when students outsource their assessed work to a third party. One approach that has been suggested for improving contract cheating detection is comparing students' assignment submissions with their previous work, the rationale being that changes in style may indicate a piece of work has been written by somebody else. This…
Descriptors: Cheating, Identification, Accuracy, Computer Software
Hoseana, Jonathan; Stepanus, Oriza; Octora, Elvina – International Journal of Mathematical Education in Science and Technology, 2023
As educational systems move from onsite to online due to the COVID-19 pandemic, teachers face the difficulty of designing online examination formats which minimize opportunities for dishonesty. In this paper, we expose our design of such a format: a protected Microsoft Excel spreadsheet containing short-answer questions, which was implemented in a…
Descriptors: Plagiarism, Calculus, Algebra, Computer Software
Gregory J. Crowther; Usha Sankar; Leena S. Knight; Deborah L. Myers; Kevin T. Patton; Lekelia D. Jenkins; Thomas A. Knight – Journal of Microbiology & Biology Education, 2023
The biology education literature includes compelling assertions that unfamiliar problems are especially useful for revealing students' true understanding of biology. However, there is only limited evidence that such novel problems have different cognitive requirements than more familiar problems. Here, we sought additional evidence by using…
Descriptors: Science Instruction, Artificial Intelligence, Scoring, Molecular Structure
Jia, Jiyou; He, Yunfan – Interactive Technology and Smart Education, 2022
Purpose: The purpose of this study is to design and implement an intelligent online proctoring system (IOPS) by using the advantage of artificial intelligence technology in order to monitor the online exam, which is urgently needed in online learning settings worldwide. As a pilot application, the authors used this system in an authentic…
Descriptors: Artificial Intelligence, Supervision, Computer Assisted Testing, Electronic Learning
Melnychenko, Anatolii; Zheliaskova, Tetiana – Advanced Education, 2021
The rapid spread of the SARS-CoV-2 coronavirus has led to the global COVID-19 pandemic and a lockdown was introduced in Ukraine in March 2020. This forced universities to urgently transform the traditional system of organisation of the educational process and transfer to distance learning. This study aims to evaluate the distance learning system…
Descriptors: COVID-19, Pandemics, Foreign Countries, Educational Change
Josh Freeman – Higher Education Policy Institute, 2025
Building on our 2024 AI Survey, we surveyed 1,041 full-time undergraduate students through Savanta about their use of generative artificial intelligence (GenAI) tools. In 2025, we find that the student use of AI has surged in the last year, with almost all students (92%) now using AI in some form, up from 66% in 2024, and some 88% having used…
Descriptors: Student Surveys, Student Attitudes, Cheating, Artificial Intelligence
Haus, Goffredo; Pasquinelli, Yuri Benvenuto; Scaccia, Daniela; Scarabottolo, Nello – International Association for Development of the Information Society, 2020
The paper deals with the problem of carrying on online written exams in the University of Milan, suddenly closed due to the Covid-19 emergency. Main goal of the paper is to present and compare the different scenarios envisioned, depending on the number of students to be monitored in parallel to avoid cheating. For limited numbers, direct…
Descriptors: COVID-19, Pandemics, Computer Assisted Testing, Cheating
Balbay, Seher; Kilis, Selcan – Contemporary Educational Technology, 2019
This cross-sectional survey study investigates students' perceptions of the effectiveness of Turnitin in detecting plagiarism in academic presentation slides. The data was collected online from 311 students studying at a prominent English-medium instruction university in Turkey. The findings indicated that more than half of them believed in the…
Descriptors: Program Effectiveness, Foreign Countries, Computer Software, Plagiarism
Alessio, Helaine M.; Malay, Nancy; Maurer, Karsten; Bailer, A. John; Rubin, Beth – Online Learning, 2017
Online education continues to grow, bringing opportunities and challenges for students and instructors. One challenge is the perception that academic integrity associated with online tests is compromised due to undetected cheating that yields artificially higher grades. To address these concerns, proctoring software has been developed to address…
Descriptors: Supervision, Scores, Computer Assisted Testing, Undergraduate Students
Linantud, John; Kaftan, Joanna – Journal of Political Science Education, 2019
This article uses a multimethod research design to compare Statecraft to non-Statecraft assignments and courses along three dimensions: student engagement, political attitudes, and academic honesty. The results indicate that Statecraft increased student engagement and academic honesty. In terms of political attitudes, students generally remained…
Descriptors: Political Science, Teaching Methods, Comparative Analysis, International Relations
Kashian, Nicole; Cruz, Shannon M.; Jang, Jeong-woo; Silk, Kami J. – Journal of Academic Ethics, 2015
Plagiarism is a prevalent form of academic dishonesty in the undergraduate instructional context. Although students engage in plagiarism with some frequency, instructors often do little to help students understand the significance of plagiarism or to create assignments that reduce its likelihood. This study reports survey, coding, and TurnItIn…
Descriptors: Plagiarism, Cheating, Learning Activities, Ethics
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