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Jila Niknejad; Margaret Bayer – International Journal of Mathematical Education in Science and Technology, 2025
In Spring 2020, the need for redesigning online assessments to preserve integrity became a priority to many educators. Many of us found methods to proctor examinations using Zoom and proctoring software. Such examinations pose their own issues. To reduce the technical difficulties and cost, many Zoom proctored examination sessions were shortened;…
Descriptors: Mathematics Instruction, Mathematics Tests, Computer Assisted Testing, Computer Software
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Angelone, Anna Maria; Galassi, Alessandra; Vittorini, Pierpaolo – International Journal of Learning Technology, 2022
The adoption of computerised adaptive testing (CAT) instead of classical testing (FIT) raises questions from both teachers' and students' perspectives. The scientific literature shows that teachers using CAT instead of FIT should experience shorter times to complete the assessment and obtain more precise evaluations. As for the students, adaptive…
Descriptors: Adaptive Testing, Computer Assisted Testing, College Freshmen, Student Attitudes
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Shengnan Han; Shahrokh Nikou; Workneh Yilma Ayele – International Journal of Educational Management, 2024
Purpose: To improve the academic integrity of online examinations, digital proctoring systems have recently been implemented in higher education institutions (HEIs). The paper aims to understand how digital proctoring has been practised in higher education (HE) and proposes future research directions for studying digital proctoring in HE.…
Descriptors: Computer Assisted Testing, Supervision, Higher Education, Cheating
Andrea E. Green – ProQuest LLC, 2024
No solution can ultimately eliminate cheating in online courses. However, universities reserve funding for authentication systems to minimize the threat of cheating in online courses. Most higher education institutions use a combination of authentication methods to secure systems against impersonation attacks during online examinations.…
Descriptors: College Students, Cheating, Online Courses, Intervention
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Rebecka Weegar; Peter Idestam-Almquist – International Journal of Artificial Intelligence in Education, 2024
Machine learning methods can be used to reduce the manual workload in exam grading, making it possible for teachers to spend more time on other tasks. However, when it comes to grading exams, fully eliminating manual work is not yet possible even with very accurate automated grading, as any grading mistakes could have significant consequences for…
Descriptors: Grading, Computer Assisted Testing, Introductory Courses, Computer Science Education
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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
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Rodríguez-Villalobos, Martha; Fernandez-Garza, Jessica; Heredia-Escorza, Yolanda – International Journal of Information and Learning Technology, 2023
Purpose: The objective of this study was to compare three distinct methods of test monitoring in the context of distance education--non-proctored remote or online tests, traditional face-to-face proctored tests and remotely proctored tests using software--to analyze if the method in which tests are monitored influences the obtained grades.…
Descriptors: Computer Assisted Testing, Academic Achievement, Distance Education, Computer Software
Samuel S. Davidson – ProQuest LLC, 2024
Automated corrective feedback (ACF), in which a computer system helps language learners identify and correct errors in their writing or speech, is considered an important tool for language instruction by many researchers. Such systems allow learners to correct their own mistakes, thereby reducing teacher workload and potentially preventing issues…
Descriptors: Computer Assisted Testing, Automation, Student Evaluation, Feedback (Response)
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E. A. J. Terblanche; Annelien Adriana van Rooyen; P. C. Enwereji – Discover Education, 2024
The COVID-19 pandemic accelerated the implementation of online assessments at an unprecedented pace. The pandemic required most higher education institutions worldwide to implement online assessments almost overnight. The study aimed to gain an understanding of auditing students' perceptions of online assessments and e-proctoring systems during…
Descriptors: Computer Assisted Testing, Supervision, Student Attitudes, Electronic Learning
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Sahin, Muhittin; Aydin, Furkan; Sulak, Sema; Müftüoglu, Cennet Terzi; Tepgeç, Mustafa; Yilmaz, Gizem Karaoglan; Yilmaz, Ramazan; Yurdugül, Halil – International Association for Development of the Information Society, 2021
The use of technology for teaching and learning has created a paradigm shifting in learning environments and learning process, and also the paradigm shifting has also affected the assessment processes. In addition to these, online environments provide more opportunities to assess of the learners. In this study, the Adaptive Mastery Testing (AMT)…
Descriptors: Teaching Methods, Learning Processes, Adaptive Testing, Computer Assisted Testing
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Purpura, James E.; Davoodifard, Mashad; Voss, Erik – Language Assessment Quarterly, 2021
The online placement test for the Community English Language Program (CLP) at Teachers College, Columbia University has been administered in a computer lab since 2015. While most of the components of this placement exam system are online, including registration, exam delivery, scoring, and score reporting, the COVID-19 pandemic elevated the need…
Descriptors: Student Placement, Language Tests, Second Language Instruction, Second Language Learning
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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
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Hanna, Gila; Yan, Xiaoheng – For the Learning of Mathematics, 2021
The paper argues that there is a need for new approaches to teaching proof with newly-available technology. It contributes to filling this need by opening a discussion on digital proof assistants, programs that allow one to do mathematics with the aid of a computer, construct proofs, and check their correctness. The paper starts by exploring such…
Descriptors: Mathematics Instruction, Validity, Mathematical Logic, Teaching Methods
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Duncan, Alex; Joyner, David – Journal of Computer Assisted Learning, 2022
Background: It is important for institutions of higher education to maintain academic integrity, both for students and the institutions themselves. Proctoring is one way of accomplishing this, and with the increasing popularity of online courses--along with the sudden shift to online education sparked by the COVID-19 pandemic--digital proctoring…
Descriptors: Computer Assisted Testing, Supervision, Integrity, COVID-19
Dewar, Cynthia – ProQuest LLC, 2023
This study examined California Community Colleges' administrator decisions about online proctoring software during the COVID-19 global pandemic between March 2020 and June 2022. Understanding how decisions were made, by whom, what information was considered, and how information was evaluated can support more informed decision making regarding…
Descriptors: Community Colleges, Computer Software, Computer Assisted Testing, COVID-19
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