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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
Mohamed Kara-Mohamed – Journal of Educational Technology Systems, 2025
(1) Context: The growing accessibility of Artificial Intelligence (AI) technology, such as ChatGPT, poses a challenge to the integrity of online assessments in higher education. As AI becomes more integrated into academic contexts, educators face the complex task of maintaining assessment standards particularly within modern Virtual Learning…
Descriptors: Artificial Intelligence, Virtual Classrooms, Computer Assisted Testing, Universities
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
Sundas Azeem; Muhammad Abbas – Education and Information Technologies, 2025
The study examined the association of big five personality traits (i.e., conscientiousness, openness to experience, and neuroticism) with use of Generative Artificial Intelligence (GenAI) among university students. It also examined the moderating role of perceived fairness in grading on the relationships of personality traits with GenAI usage.…
Descriptors: Personality Traits, Artificial Intelligence, Technology Uses in Education, Technology Integration
Sofie van den Berg; Pantelis M. Papadopoulos – Innovations in Education and Teaching International, 2025
This qualitative study explores the levels of technology acceptance of students and teachers in higher education regarding the use of artificial intelligence (AI) in summative assessment. Twelve students and eight teachers of a university expressed their views on a series of hypothetical scenarios. Stimulated recall interviews, using hypothetical…
Descriptors: Summative Evaluation, Artificial Intelligence, Qualitative Research, Technology Uses in Education
Jussi S. Jauhiainen; Agustín Garagorry Guerra – Innovations in Education and Teaching International, 2025
The study highlights ChatGPT-4's potential in educational settings for the evaluation of university students' open-ended written examination responses. ChatGPT-4 evaluated 54 written responses, ranging from 24 to 256 words in English. It assessed each response using five criteria and assigned a grade on a six-point scale from fail to excellent,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Student Evaluation, Writing Evaluation
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)
Lam Ky Nhan – Turkish Online Journal of Distance Education, 2025
This study investigates the impact of artificial intelligence (AI) on personalized learning, automated assessment and feedback, intelligent tutoring systems, and student engagement in online learning environments. The research focuses on fourth-year English major students at a university in the Mekong Delta region, utilizing a mixed-methods…
Descriptors: Artificial Intelligence, Individualized Instruction, Automation, Computer Assisted Testing
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
Zheng, Lanqin; Long, Miaolang; Chen, Bodong; Fan, Yunchao – International Journal of Educational Technology in Higher Education, 2023
Online collaborative learning is implemented extensively in higher education. Nevertheless, it remains challenging to help learners achieve high-level group performance, knowledge elaboration, and socially shared regulation in online collaborative learning. To cope with these challenges, this study proposes and evaluates a novel automated…
Descriptors: Learning Analytics, Computer Assisted Testing, Cooperative Learning, Graphs
Linda Amrane-Cooper; Stylianos Hatzipanagos; Liz Marr; Alan Tait – Open Praxis, 2024
The COVID-19 pandemic accelerated the shift to online assessment, prompting debates over validity, security, and increasingly the impact of Artificial Intelligence (AI) tools, especially generative AI, on traditional examination methods. This paper explores perceptions of the evolving landscape of online assessment and the role of AI within higher…
Descriptors: Computer Assisted Testing, Artificial Intelligence, Foreign Countries, Technology Uses in Education
Barno Sayfutdinovna Abdullaeva; Diyorjon Abdullaev; Feruza Abulkosimovna Rakhmatova; Laylo Djuraeva; Nigora Asqaraliyevna Sulaymonova; Zebo Fazliddinovna Shamsiddinova; Oynisa Khamraeva – Language Testing in Asia, 2024
Acquiring technological literacy and acceptance has a significant influence on academic emotion regulation (AER), academic resilience (AR), willingness to communicate (WTC), and academic enjoyment (AE), which are crucial for the success of university students. However, this area has not been adequately explored in research, particularly in the…
Descriptors: Technological Literacy, Emotional Response, Self Control, Resilience (Psychology)
Neha Biju; Nasser Said Gomaa Abdelrasheed; Khilola Bakiyeva; K. D. V. Prasad; Biruk Jember – Language Testing in Asia, 2024
In recent years, language practitioners have paid increasing attention to artificial intelligence (AI)'s role in language programs. This study investigated the impact of AI-assisted language assessment on L2 learners' foreign language anxiety (FLA), attitudes, motivation, and writing skills. The study adopted a sequential exploratory mixed-methods…
Descriptors: Artificial Intelligence, Computer Software, Computer Assisted Testing, Second Language Instruction
Gudiño Paredes, Sandra; Jasso Peña, Felipe de Jesús; de La Fuente Alcazar, Juana María – Distance Education, 2021
After almost a year of COVID-19, distance education mediated by digital tools prevails as an ideal way to study given the flexibility, ubiquity, and a variety of tools that make the process more acceptable. Remote proctored exams have become an important tool to ensure integrity and academic honesty in distance education. This mixed methods study…
Descriptors: Distance Education, Computer Assisted Testing, Integrity, Electronic Learning
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