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Showing 1 to 15 of 17 results Save | Export
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Jinshui Wang; Shuguang Chen; Zhengyi Tang; Pengchen Lin; Yupeng Wang – Education and Information Technologies, 2025
Mastering SQL programming skills is fundamental in computer science education, and Online Judging Systems (OJS) play a critical role in automatically assessing SQL codes, improving the accuracy and efficiency of evaluations. However, these systems are vulnerable to manipulation by students who can submit "cheating codes" that pass the…
Descriptors: Programming, Computer Science Education, Cheating, Computer Assisted Testing
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Yang Zhen; Xiaoyan Zhu – Educational and Psychological Measurement, 2024
The pervasive issue of cheating in educational tests has emerged as a paramount concern within the realm of education, prompting scholars to explore diverse methodologies for identifying potential transgressors. While machine learning models have been extensively investigated for this purpose, the untapped potential of TabNet, an intricate deep…
Descriptors: Artificial Intelligence, Models, Cheating, Identification
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Langenfeld, Thomas – Journal of Applied Testing Technology, 2022
The turn to online learning and training programs as a response to challenging times (i.e., the COVID-19 crisis) necessitated the need for internet-based testing solutions. Researchers generally have found that Unproctored Internet Testing (UIT) for high-stakes cognitive ability assessments results in higher scores than proctored assessments. Live…
Descriptors: Internet, Computer Assisted Testing, COVID-19, Pandemics
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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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Yang Jiang; Mo Zhang; Jiangang Hao; Paul Deane; Chen Li – Journal of Educational Measurement, 2024
The emergence of sophisticated AI tools such as ChatGPT, coupled with the transition to remote delivery of educational assessments in the COVID-19 era, has led to increasing concerns about academic integrity and test security. Using AI tools, test takers can produce high-quality texts effortlessly and use them to game assessments. It is thus…
Descriptors: Integrity, Artificial Intelligence, Technology Uses in Education, Ethics
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Kaiwen Man – Educational and Psychological Measurement, 2024
In various fields, including college admission, medical board certifications, and military recruitment, high-stakes decisions are frequently made based on scores obtained from large-scale assessments. These decisions necessitate precise and reliable scores that enable valid inferences to be drawn about test-takers. However, the ability of such…
Descriptors: Prior Learning, Testing, Behavior, Artificial Intelligence
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Surahman, Ence; Wang, Tzu-Hua – Journal of Computer Assisted Learning, 2022
Background: Academic dishonesty (AD) and trustworthy assessment (TA) are fundamental issues in the context of an online assessment. However, little systematic work currently exists on how researchers have explored AD and TA issues in online assessment practice. Objectives: Hence, this research aimed at investigating the latest findings regarding…
Descriptors: Ethics, Trust (Psychology), Computer Assisted Testing, Educational Technology
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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
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LaFlair, Geoffrey T.; Langenfeld, Thomas; Baig, Basim; Horie, André Kenji; Attali, Yigal; von Davier, Alina A. – Journal of Computer Assisted Learning, 2022
Background: Digital-first assessments leverage the affordances of technology in all elements of the assessment process--from design and development to score reporting and evaluation to create test taker-centric assessments. Objectives: The goal of this paper is to describe the engineering, machine learning, and psychometric processes and…
Descriptors: Computer Assisted Testing, Affordances, Scoring, Engineering
Hong Jiao, Editor; Robert W. Lissitz, Editor – IAP - Information Age Publishing, Inc., 2024
With the exponential increase of digital assessment, different types of data in addition to item responses become available in the measurement process. One of the salient features in digital assessment is that process data can be easily collected. This non-conventional structured or unstructured data source may bring new perspectives to better…
Descriptors: Artificial Intelligence, Natural Language Processing, Psychometrics, Computer Assisted Testing
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Alexander Stanoyevitch – Discover Education, 2024
Online education, while not a new phenomenon, underwent a monumental shift during the COVID-19 pandemic, pushing educators and students alike into the uncharted waters of full-time digital learning. With this shift came renewed concerns about the integrity of online assessments. Amidst a landscape rapidly being reshaped by online exam/homework…
Descriptors: Computer Assisted Testing, Student Evaluation, Artificial Intelligence, Electronic Learning
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Nejdet Karadag – Journal of Educational Technology and Online Learning, 2023
The purpose of this study is to examine the impact of artificial intelligence (AI) on online assessment in the context of opportunities and threats based on the literature. To this end, 19 articles related to the AI tool ChatGPT and online assessment were analysed through rapid literature review. In the content analysis, the themes of "AI's…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Natural Language Processing, Grading
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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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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
Josh Freeman – Higher Education Policy Institute, 2025
Building on our 2024 AI Survey, we surveyed 1,041 full-time undergraduate students through Savanta about their use of generative artificial intelligence (GenAI) tools. In 2025, we find that the student use of AI has surged in the last year, with almost all students (92%) now using AI in some form, up from 66% in 2024, and some 88% having used…
Descriptors: Student Surveys, Student Attitudes, Cheating, Artificial Intelligence
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