NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Laws, Policies, & Programs
Assessments and Surveys
Law School Admission Test1
What Works Clearinghouse Rating
Showing 1 to 15 of 16 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Grochowalski, Joseph H.; Hendrickson, Amy – Journal of Educational Measurement, 2023
Test takers wishing to gain an unfair advantage often share answers with other test takers, either sharing all answers (a full key) or some (a partial key). Detecting key sharing during a tight testing window requires an efficient, easily interpretable, and rich form of analysis that is descriptive and inferential. We introduce a detection method…
Descriptors: Identification, Cooperative Learning, Cheating, Statistical Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Yang Zhen; Xiaoyan Zhu – Educational and Psychological Measurement, 2024
The pervasive issue of cheating in educational tests has emerged as a paramount concern within the realm of education, prompting scholars to explore diverse methodologies for identifying potential transgressors. While machine learning models have been extensively investigated for this purpose, the untapped potential of TabNet, an intricate deep…
Descriptors: Artificial Intelligence, Models, Cheating, Identification
Peer reviewed Peer reviewed
Direct linkDirect link
Cleophas, Catherine; Hönnige, Christoph; Meisel, Frank; Meyer, Philipp – INFORMS Transactions on Education, 2023
As the COVID-19 pandemic motivated a shift to virtual teaching, exams have increasingly moved online too. Detecting cheating through collusion is not easy when tech-savvy students take online exams at home and on their own devices. Such online at-home exams may tempt students to collude and share materials and answers. However, online exams'…
Descriptors: Computer Assisted Testing, Cheating, Identification, Essay Tests
Peer reviewed Peer reviewed
Direct linkDirect link
Becker, Kirk; Meng, Huijuan – Journal of Applied Testing Technology, 2022
The rise of online proctoring potentially provides more opportunities for item harvesting and consequent brain dumping and shared "study guides" based on stolen content. This has increased the need for rapid approaches for evaluating and acting on suspicious test responses in every delivery modality. Both hiring proxy test takers and…
Descriptors: Identification, Cheating, Computer Assisted Testing, Observation
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Marilyn U. Balagtas; Aurora B. Fulgencio; Joyce L. Bautista; Alvin B. Barcelona; Shiela Marie P. Jandusay; Ma. Danielle Renee Lim – Journal of Educators Online, 2025
The convenience and flexibility of online assessments can be beneficial in a variety of ways, but they can also pose risks and challenges, such as potential academic dishonesty by students. This study included 73 master's and doctoral students and investigated the relationship among their attitudes, experiences, and performance in an online…
Descriptors: Graduate Students, Student Attitudes, Student Experience, Academic Achievement
Peer reviewed Peer reviewed
Direct linkDirect link
Oeding, Jill M. – Quarterly Review of Distance Education, 2022
One of the primary findings from this study is the importance of watching the exam proctoring videos for online, remotely proctored exams. Proctors do not need to be experts in academic dishonesty to detect the misconduct. The key to detecting academic dishonesty is to closely monitor the examinee's eyes, know the eyes' position when the examinee…
Descriptors: Prevention, Identification, Cheating, Ethics
Peer reviewed Peer reviewed
Direct linkDirect link
Lim, Kieran Fergus – Physics Education, 2022
Undergraduate first-year courses are often mandatory for students in a variety of majors and degrees. Many students view these core courses as of little interest and relevance, which is associated with lack of motivation for study and can lead to cheating. Contract cheating in text-based is difficult to detect and prove. Contract cheating in…
Descriptors: College Freshmen, Contracts, Cheating, Assignments
Peer reviewed Peer reviewed
Direct linkDirect link
Emery-Wetherell, Meaghan; Wang, Ruoyao – Assessment & Evaluation in Higher Education, 2023
Over four semesters of a large introductory statistics course the authors found students were engaging in contract cheating on Chegg.com during multiple choice examinations. In this paper we describe our methodology for identifying, addressing and eventually eliminating cheating. We successfully identified 23 out of 25 students using a combination…
Descriptors: Computer Assisted Testing, Multiple Choice Tests, Cheating, Identification
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Jeske, Heimo J.; Lall, Manoj; Kogeda, Okuthe P. – Journal of Information Technology Education: Innovations in Practice, 2018
Aim/Purpose: The aim of this article is to develop a tool to detect plagiarism in real time amongst students being evaluated for learning in a computer-based assessment setting. Background: Cheating or copying all or part of source code of a program is a serious concern to academic institutions. Many academic institutions apply a combination of…
Descriptors: Plagiarism, Identification, Computer Software, Computer Assisted Testing
Peer reviewed Peer reviewed
Direct linkDirect link
D'Souza, Kelwyn A.; Siegfeldt, Denise V. – Decision Sciences Journal of Innovative Education, 2017
Selecting the right methodology to use for detecting cheating in online exams requires considerable time and effort due to a wide variety of scholarly publications on academic dishonesty in online education. This article offers a cheating detection framework that can serve as a guideline for conducting cheating studies. The necessary theories and…
Descriptors: Identification, Cheating, Computer Assisted Testing, Testing Problems
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Bao, Yingying; Chen, Guanliang; Hauff, Claudia – International Educational Data Mining Society, 2017
Massive Open Online Courses (MOOCs) are a promising form of online education. However, the occurrence of academic dishonesty has been threatening MOOC certificates' effectiveness as a serious tool for recruiters and employers. Recently, a large-scale study on the log traces from more than one hundred MOOCs created by Harvard and MIT has identified…
Descriptors: Large Group Instruction, Online Courses, Cheating, Incidence
Peer reviewed Peer reviewed
Direct linkDirect link
Belov, Dmitry I. – Journal of Educational Measurement, 2013
The development of statistical methods for detecting test collusion is a new research direction in the area of test security. Test collusion may be described as large-scale sharing of test materials, including answers to test items. Current methods of detecting test collusion are based on statistics also used in answer-copying detection.…
Descriptors: Cheating, Computer Assisted Testing, Adaptive Testing, Statistical Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Liu, I-Fan; Chen, Ruey-Shin; Lu, Hao-Chun – Educational Technology & Society, 2015
With the rapid development of the Internet and information technology, the issues related to online exams have become the concern of an increasing number of researchers. At present, the biggest challenges for the integration of web communication technology into online exams are the ability to detect cheating behaviors during the exam, and the…
Descriptors: Foreign Countries, Computer Assisted Testing, Cheating, Identification
Previous Page | Next Page »
Pages: 1  |  2