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Hon Keung Yau; Choi Ho Man – Turkish Online Journal of Educational Technology - TOJET, 2025
This study explores Hong Kong higher education students' perceptions of E-assessment systems, focusing on factors shaping acceptance of E-examinations over traditional formats. Quantitative analysis of 107 respondents reveals significant positive correlations between diverse pre-exam guidance (e.g., tutorials) and key system features (e.g.,…
Descriptors: Foreign Countries, College Students, Student Attitudes, Computer Assisted Testing
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Danielle Lottridge; Davis Dimalen; Gerald Weber – ACM Transactions on Computing Education, 2025
Automated assessment is well-established within computer science courses but largely absent from human--computer interaction courses. Automating the assessment of human--computer interaction (HCI) is challenging because the coursework tends not to be computational but rather highly creative, such as designing and implementing interactive…
Descriptors: Computer Science Education, Computer Assisted Testing, Automation, Man Machine Systems
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Ilhama Mammadova; Fatime Ismayilli; Elnaz Aliyeva; Narmin Mammadova – Educational Process: International Journal, 2025
Background/purpose: Artificial Intelligence (AI) is increasingly shaping assessment practices in higher education, promising faster feedback and reduced instructor workload while also raising concerns about fairness and transparency. This study examines how AI technologies are transforming assessment processes and the experiences of stakeholders.…
Descriptors: Artificial Intelligence, Student Evaluation, Technology Uses in Education, Undergraduate Students
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E. Marano; P. M. Newton; Z. Birch; M. Croombs; C. Gilbert; M. J. Draper – Higher Education Quarterly, 2024
Remote or online proctoring (invigilating) is a technology primarily used to improve the integrity of online examinations. The use of remote proctoring increased significantly as the world switched to online assessment during the COVID-19 pandemic. Remote proctoring received negative media attention, including concerns about user privacy,…
Descriptors: Student Experience, Supervision, Distance Education, Technology Uses in Education
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Colette Melissa Kell; Yasmeen Thandar; Adelle Kemlall Bhundoo; Firoza Haffejee; Bongiwe Mbhele; Jennifer Ducray – Journal of Applied Research in Higher Education, 2025
Purpose: Academic integrity is vital to the success and sustainability of the academic project and particularly critical in the training of ethical and informed health professionals. Yet studies have found that cheating in online exams was commonplace during the COVID-19 pandemic. With the increased use of online and blended learning…
Descriptors: Foreign Countries, Universities, Integrity, Cheating
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Pearson, Christopher; Penna, Nigel – Assessment & Evaluation in Higher Education, 2023
E-assessments are becoming increasingly common and progressively more complex. Consequently, how these longer, more complex questions are designed and marked is imperative. This article uses the NUMBAS e-assessment tool to investigate the best practice for creating longer questions and their mark schemes on surveying modules taken by engineering…
Descriptors: Automation, Scoring, Engineering Education, Foreign Countries
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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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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
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Timos Almpanis; Dom Conroy; Paul Joseph-Richard – Electronic Journal of e-Learning, 2025
The advent of Generative AI (GAI) tools such as ChatGPT, Google Gemini, and Microsoft Copilot has significantly impacted higher education. This exploratory study investigates the current perspectives of lecturers in Human Resource Management (HRM) and Psychology on adapting assessment strategies in response to GAI developments. Through an online…
Descriptors: Artificial Intelligence, Technology Uses in Education, Higher Education, College Faculty
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Amr Selim Wannas; Marwa M. AbdelMohsen – Knowledge Management & E-Learning, 2025
The global pandemic caused by COVID-19 has acted as a significant driver for the adoption of online educational practices, including instruction and assessment. Given the urgent need for an alternative to traditional assessment methods during the pandemic, various studies have explored this topic across different contexts to evaluate the impact,…
Descriptors: English (Second Language), Computer Assisted Testing, Second Language Learning, Second Language Instruction
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Christian Grévisse; Françoise Kayser – Anatomical Sciences Education, 2025
Radioanatomy, short for radiographic anatomy, is the study of anatomy through medical imaging. Its early-stage introduction into medical curricula has been recommended in the literature. As with many other medical courses, it has seen a shift toward blended learning, including assessment on learning management systems such as Moodle, one advantage…
Descriptors: Science Education, Radiology, Anatomy, Learning Management Systems
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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Griffiths, Barry J. – Research on Education and Media, 2022
This pilot study looks at how the author proactively sought to mitigate the issue of cheating when giving online tests during the Spring 2021 semester, at a time when the COVID-19 pandemic forced many teachers around the world to use modalities that involved distance learning. The genesis, implementation and results of the strategy used during the…
Descriptors: Computer Assisted Testing, Supervision, Cheating, Educational Technology
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Seyma Yildirim-Erbasli; Okan Bulut; Carrie Demmans Epp; Ying Cui – Educational Technology Research and Development, 2025
Conversational agents have been designed to improve instruction quality and support student learning. In addition to their instructional use, they can be incorporated into assessment--conversation-based assessment (CBA). This study primarily introduces a CBA with selected-response and constructed-response tests as a formative assessment tool for…
Descriptors: Higher Education, Artificial Intelligence, Computer Mediated Communication, Technology Uses in Education
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Bolat, Yusuf Islam; Tas, Nurullah – Education and Information Technologies, 2023
The purpose of this meta-analysis was to examine the effects of Gamified-Assessment Tools (GAT) used in formal educational settings on student academic achievement. We used PRISMA systematic procedures to screen the articles across Web of Science, ERIC, Scopus, Pubmed, and PsycArticles databases. We identified 23 independent results from 17…
Descriptors: Gamification, Student Evaluation, Academic Achievement, Computer Assisted Testing
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