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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
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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
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Becker, Benjamin; van Rijn, Peter; Molenaar, Dylan; Debeer, Dries – Assessment & Evaluation in Higher Education, 2022
A common approach to increase test security in higher educational high-stakes testing is the use of different test forms with identical items but different item orders. The effects of such varied item orders are relatively well studied, but findings have generally been mixed. When multiple test forms with different item orders are used, we argue…
Descriptors: Information Security, High Stakes Tests, Computer Security, Test Items
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Troy, Jesse D.; Neely, Megan L.; Pomann, Gina-Maria; Grambow, Steven C.; Samsa, Gregory P. – Journal of Curriculum and Teaching, 2022
Student evaluation is a key consideration for educational program administrators because program success depends on students' ability to demonstrate successful development of core competencies. Student evaluations must therefore be aligned with learning objectives and overall program goals. Graduate level educational programs typically incorporate…
Descriptors: Student Evaluation, Evaluation Methods, Statistics Education, Alignment (Education)
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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
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Cosma, Georgina; Joy, Mike; Sinclair, Jane; Andreou, Margarita; Zhang, Dongyong; Cook, Beverley; Boyatt, Russell – ACM Transactions on Computing Education, 2017
Perspectives of students on what constitutes source-code plagiarism may differ based on their educational background. Surveys have been conducted with home students undertaking computing and joint computing subject degrees at higher education institutions throughout the UK, China, and South Cyprus, and a total of 984 responses have been…
Descriptors: Foreign Countries, College Students, Plagiarism, Student Attitudes
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Haas, Timothy C. – International Journal of Distance Education Technologies, 2016
Before massive numbers of students can take online courses for college credit, the challenges of providing tutoring support, answers to student-posed questions, and the control of cheating will need to be addressed. These challenges are taken up here by developing an online course delivery system that runs in a cluster computing environment and is…
Descriptors: Online Courses, Educational Technology, Technology Uses in Education, Electronic Learning