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Tay McEdwards; Greta R. Underhill – Online Journal of Distance Learning Administration, 2025
Online learning has steadily increased since well before the COVID-19 pandemic (Seaman et al., 2018), but research has yet to explore online students' perceptions of online exam proctoring methods. The purpose of this exploratory study was to understand the perceptions of fully online students regarding types of proctoring at a large state…
Descriptors: Supervision, Computer Assisted Testing, Electronic Learning, Student Attitudes
Jonas Flodén – British Educational Research Journal, 2025
This study compares how the generative AI (GenAI) large language model (LLM) ChatGPT performs in grading university exams compared to human teachers. Aspects investigated include consistency, large discrepancies and length of answer. Implications for higher education, including the role of teachers and ethics, are also discussed. Three…
Descriptors: College Faculty, Artificial Intelligence, Comparative Testing, Scoring
Yusuf Oc; Hela Hassen – Marketing Education Review, 2025
Driven by technological innovations, continuous digital expansion has transformed fundamentally the landscape of modern higher education, leading to discussions about evaluation techniques. The emergence of generative artificial intelligence raises questions about reliability and academic honesty regarding multiple-choice assessments in online…
Descriptors: Higher Education, Multiple Choice Tests, Computer Assisted Testing, Electronic Learning
Gulnur Tyulepberdinova; Madina Mansurova; Talshyn Sarsembayeva; Sulu Issabayeva; Darazha Issabayeva – Journal of Computer Assisted Learning, 2024
Background: This study aims to assess how well several machine learning (ML) algorithms predict the physical, social, and mental health condition of university students. Objectives: The physical health measurements used in the study include BMI (Body Mass Index), %BF (percentage of Body Fat), BSC (Blood Serum Cholesterol), SBP (Systolic Blood…
Descriptors: Artificial Intelligence, Algorithms, Predictor Variables, Physical Health
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
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)
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
Andrea Fernández-Sánchez; Juan José Lorenzo-Castiñeiras; Ana Sánchez-Bello – European Journal of Education, 2025
The advent of artificial intelligence (AI) technologies heralds a transformative era in education. This study investigates the integration of AI tools in developing educational assessment rubrics within the 'Curriculum Design Development and Evaluation' course at the University of A Coruña during the 2023-2024 academic year. Employing an…
Descriptors: Foreign Countries, Higher Education, Artificial Intelligence, Technology Integration
On-Soon Lee – Journal of Pan-Pacific Association of Applied Linguistics, 2024
Despite the increasing interest in using AI tools as assistant agents in instructional settings, the effectiveness of ChatGPT, the generative pretrained AI, for evaluating the accuracy of second language (L2) writing has been largely unexplored in formative assessment. Therefore, the current study aims to examine how ChatGPT, as an evaluator,…
Descriptors: Foreign Countries, Undergraduate Students, English (Second Language), Second Language Learning
Dan Song; Alexander F. Tang – Language Learning & Technology, 2025
While many studies have addressed the benefits of technology-assisted L2 writing, limited research has delved into how generative artificial intelligence (GAI) supports students in completing their writing tasks in Mandarin Chinese. In this study, 26 university-level Mandarin Chinese foreign language students completed two writing tasks on two…
Descriptors: Artificial Intelligence, Second Language Learning, Standardized Tests, Writing Tests
Kenneth W. O'Connor – ProQuest LLC, 2023
Higher education is examining artificial intelligence (AI) as a key to increasing productivity and efficiency as colleges race to remain relevant and competitive in a rapidly evolving industry. With the increase of students taking online classes, professors are looking for solutions to help maintain integrity with their testing remotely. AI has…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Assisted Testing, Electronic Learning
Leonid Chernovaty – Advanced Education, 2024
This first attempt aims to determine the extent of students' covert use of machine translation (MT) in the online assessment of their sight translation, the strategies of such use, and its signs. The study is based on the analysis of target texts (TT) of specialised online sight translation from Ukrainian into English by 13 BA and 10 MA students.…
Descriptors: Computer Assisted Testing, Translation, Ukrainian, English (Second Language)
Mimi Ismail; Ahmed Al - Badri; Said Al - Senaidi – Journal of Education and e-Learning Research, 2025
This study aimed to reveal the differences in individuals' abilities, their standard errors, and the psychometric properties of the test according to the two methods of applying the test (electronic and paper). The descriptive approach was used to achieve the study's objectives. The study sample consisted of 74 male and female students at the…
Descriptors: Achievement Tests, Computer Assisted Testing, Psychometrics, Item Response Theory
Sefcik, Lesley; Veeran-Colton, Terisha; Baird, Michael; Price, Connie; Steyn, Steve – Australasian Journal of Educational Technology, 2022
This study aimed to understand the effects of a custom-developed, artificial intelligence-based, asynchronous remote invigilation system on the student user experience. The study was conducted over 3 years at a large Australian university, and findings demonstrate that familiarity with the system over time improved student attitudes towards remote…
Descriptors: Usability, Users (Information), Student Attitudes, Supervision
Sylla, Khalifa; Babou, Birahim; Ouya, Samuel – International Association for Development of the Information Society, 2022
This paper deals with a solution allowing digital universities to extend the functionalities of their distance learning platform to offer a secure solution for the dematerialization of assessments. Currently we are witnessing the rise of digital universities, this is the case in Africa, particularly in Senegal. We are witnessing strong growth in…
Descriptors: Foreign Countries, Virtual Universities, Computer Assisted Testing, Educational Technology