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Salvatore G. Garofalo; Stephen J. Farenga – Science & Education, 2025
The purpose of this study was to gauge the attitudes towards artificial intelligence (AI) use in the science classroom by science teachers at the start of generative AI chatbot popularity (March 2023). The lens of distributed cognition afforded an opportunity to gather thoughts, opinions, and perceptions from 24 secondary science educators as well…
Descriptors: Secondary School Teachers, Science Teachers, Teacher Attitudes, Artificial Intelligence
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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
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Jyoti Prakash Meher; Rajib Mall – IEEE Transactions on Education, 2025
Contribution: This article suggests a novel method for diagnosing a learner's cognitive proficiency using deep neural networks (DNNs) based on her answers to a series of questions. The outcome of the forecast can be used for adaptive assistance. Background: Often a learner spends considerable amounts of time in attempting questions on the concepts…
Descriptors: Cognitive Ability, Assistive Technology, Adaptive Testing, Computer Assisted Testing
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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
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Andreea Dutulescu; Stefan Ruseti; Denis Iorga; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2025
Automated multiple-choice question (MCQ) generation is valuable for scalable assessment and enhanced learning experiences. How-ever, existing MCQ generation methods face challenges in ensuring plausible distractors and maintaining answer consistency. This paper intro-duces a method for MCQ generation that integrates reasoning-based explanations…
Descriptors: Automation, Computer Assisted Testing, Multiple Choice Tests, Natural Language Processing
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Gurvinder Kaur; Stephanie Stroever; Megh Gore; Bridget Vories; Vaughan H. Lee; Keith N. Bishop; Brandt L. Schneider – Discover Education, 2025
Background: Formative assessments build a positive learning environment and provide feedback to enhance learning. This study examined the impact of online formative and low-stake summative assessments on medical students' learning outcomes in the Clinically Oriented Anatomy course from 2016 to 2020. We aimed to demonstrate that formative…
Descriptors: At Risk Students, Identification, Prediction, Anatomy
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Tiana P. Johnson-Clements; Guy J. Curtis; Joseph Clare – Journal of Academic Ethics, 2025
Concerns over students engaging in various forms of academic misconduct persist, especially with the post-COVID-19 rise in online learning and assessment. Research has demonstrated a clear role of the personality trait psychopathy in cheating, yet little is known about why this relationship exists. Building on the research by Curtis et al.…
Descriptors: Pandemics, COVID-19, Cheating, Electronic Learning
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Abigail M. A. Love; Ru Ying Cai; Jennifer Stephenson; Emma Gallagher; Michael D. Toland; Vicki Gibbs – Journal of Autism and Developmental Disorders, 2025
Autistic students are educated in Australia across a variety of contexts and almost all educators use individualized goal-setting as a way of ensuring appropriate accommodations and curriculum modifications. Educators experience similar challenges when developing individualized goals for students, including lack of a standardized process for goal…
Descriptors: Computer Assisted Testing, Adaptive Testing, Autism Spectrum Disorders, Foreign Countries
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Wesley Morris; Langdon Holmes; Joon Suh Choi; Scott Crossley – International Journal of Artificial Intelligence in Education, 2025
Recent developments in the field of artificial intelligence allow for improved performance in the automated assessment of extended response items in mathematics, potentially allowing for the scoring of these items cheaply and at scale. This study details the grand prize-winning approach to developing large language models (LLMs) to automatically…
Descriptors: Automation, Computer Assisted Testing, Mathematics Tests, Scoring
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Lena Frenken; Paul Libbrecht; Benjamin Becker; Gilbert Greefrath – International Journal of Mathematical Education in Science and Technology, 2024
The German national educational standards state explicitly that students should be enabled to successfully interact with dynamic geometry software. In a feasibility study on providing a standardized assessment instrument by digital means, in order to assess students' mathematical competencies, the implementation of a task with such a dynamic…
Descriptors: Geometry, Standardized Tests, Foreign Countries, Computer Software
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Arif Cem Topuz; Kinshuk – Educational Technology Research and Development, 2024
Online assessments of learning, or online exams, have become increasingly widespread with the rise of distance learning. Online exams are preferred by many students and are perceived as a quick and easy tool to measure knowledge. On the contrary, some students are concerned about the possibility of cheating and technological difficulties in online…
Descriptors: Computer Assisted Testing, Student Evaluation, Evaluation Methods, Student Attitudes
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Archana Praveen Kumar; Ashalatha Nayak; Manjula Shenoy K.; Chaitanya; Kaustav Ghosh – International Journal of Artificial Intelligence in Education, 2024
Multiple Choice Questions (MCQs) are a popular assessment method because they enable automated evaluation, flexible administration and use with huge groups. Despite these benefits, the manual construction of MCQs is challenging, time-consuming and error-prone. This is because each MCQ is comprised of a question called the "stem", a…
Descriptors: Multiple Choice Tests, Test Construction, Test Items, Semantics
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Ulrike Padó; Yunus Eryilmaz; Larissa Kirschner – International Journal of Artificial Intelligence in Education, 2024
Short-Answer Grading (SAG) is a time-consuming task for teachers that automated SAG models have long promised to make easier. However, there are three challenges for their broad-scale adoption: A technical challenge regarding the need for high-quality models, which is exacerbated for languages with fewer resources than English; a usability…
Descriptors: Grading, Automation, Test Format, Computer Assisted Testing
Chris Jellis – Research Matters, 2024
The Centre for Evaluation and Monitoring (CEM), based in the North of England, recently celebrated its 40th birthday. Arising from an evaluation project at Newcastle University, and a subsequent move to Durham University, it rapidly grew in scope and influence, developing a series of highly regarded school assessments. For a relatively small…
Descriptors: Educational Assessment, Foreign Countries, Computer Assisted Testing, Adaptive Testing
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Jing Miao; Yi Cao; Michael E. Walker – ETS Research Report Series, 2024
Studies of test score comparability have been conducted at different stages in the history of testing to ensure that test results carry the same meaning regardless of test conditions. The expansion of at-home testing via remote proctoring sparked another round of interest. This study uses data from three licensure tests to assess potential mode…
Descriptors: Testing, Test Format, Computer Assisted Testing, Home Study
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