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Peter Rowlett; Chris Graham; Christian Lawson-Perfect – International Journal of Mathematical Education in Science and Technology, 2025
Partially automated assessment is implemented via the 'Printable worksheet' mode in the Numbas e-assessment system to create a mathematical modelling worksheet which is individualised with random parameters but completed and marked as if it were a non-automated piece of coursework, preserving validity while reducing the risk of academic misconduct…
Descriptors: Automation, Worksheets, Mathematical Models, Computer Assisted Testing
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Chen, Jennifer J.; Perez, ChareMone' – Childhood Education, 2023
Assessment holds the key to unlocking for the teacher a child's past (what he already knows), present (what he is learning), and future (what he still needs to learn) to inform teaching. Despite the benefits of assessment for informing teaching practice and enhancing student learning, it remains one of the most challenging and time-consuming tasks…
Descriptors: Evaluation Methods, Individualized Instruction, Artificial Intelligence, Computer Assisted Testing
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Harold Doran; Testsuhiro Yamada; Ted Diaz; Emre Gonulates; Vanessa Culver – Journal of Educational Measurement, 2025
Computer adaptive testing (CAT) is an increasingly common mode of test administration offering improved test security, better measurement precision, and the potential for shorter testing experiences. This article presents a new item selection algorithm based on a generalized objective function to support multiple types of testing conditions and…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Algorithms
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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Cleophas, Catherine; Hönnige, Christoph; Meisel, Frank; Meyer, Philipp – INFORMS Transactions on Education, 2023
As the COVID-19 pandemic motivated a shift to virtual teaching, exams have increasingly moved online too. Detecting cheating through collusion is not easy when tech-savvy students take online exams at home and on their own devices. Such online at-home exams may tempt students to collude and share materials and answers. However, online exams'…
Descriptors: Computer Assisted Testing, Cheating, Identification, Essay Tests
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Becker, Kirk; Meng, Huijuan – Journal of Applied Testing Technology, 2022
The rise of online proctoring potentially provides more opportunities for item harvesting and consequent brain dumping and shared "study guides" based on stolen content. This has increased the need for rapid approaches for evaluating and acting on suspicious test responses in every delivery modality. Both hiring proxy test takers and…
Descriptors: Identification, Cheating, Computer Assisted Testing, Observation
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Petrilli, Michael J. – Education Next, 2022
In the late 1960s, when federal officials and eminent psychologists were first designing the National Assessment of Educational Progress (NAEP), they probably never contemplated testing students younger than nine. The technology for mass testing at the time--bubble sheets and No. 2 pencils--only worked if students could read the instructions and…
Descriptors: Kindergarten, Student Evaluation, National Competency Tests, Computer Assisted Testing
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Sandra Camargo Salamanca; Maria Elena Oliveri; April L. Zenisky – International Journal of Testing, 2025
This article describes the 2022 "ITC/ATP Guidelines for Technology-Based Assessment" (TBA), a collaborative effort by the International Test Commission (ITC) and the Association of Test Publishers (ATP) to address digital assessment challenges. Developed by over 100 global experts, these "Guidelines" emphasize fairness,…
Descriptors: Guidelines, Standards, Technology Uses in Education, Computer Assisted Testing
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Stephanie Smith Budhai – Distance Learning, 2024
Online learning has provided pathways for access to flexible educational experiences, but can also feel isolating and impersonal, lacking authentic relationships with instructors and peers. Centering the discussion of humanizing distance education through the lens of three core pedagogical components of teaching and learning (i.e., instruction,…
Descriptors: Humanization, Electronic Learning, Culturally Relevant Education, Teaching Methods
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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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Veale, Clinton G. L. – Journal of Chemical Education, 2022
The shift to online education has dealt several important pedagogical lessons in a very short time frame, none more so than approaches to assessments. This experience, coupled to improved access to education, will likely see online assessments remain as a major component of modern mainstream education. The powerful technologies that facilitate the…
Descriptors: Visual Aids, Search Engines, Computer Assisted Testing, Chemistry
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McCaffrey, Daniel F.; Casabianca, Jodi M.; Ricker-Pedley, Kathryn L.; Lawless, René R.; Wendler, Cathy – ETS Research Report Series, 2022
This document describes a set of best practices for developing, implementing, and maintaining the critical process of scoring constructed-response tasks. These practices address both the use of human raters and automated scoring systems as part of the scoring process and cover the scoring of written, spoken, performance, or multimodal responses.…
Descriptors: Best Practices, Scoring, Test Format, Computer Assisted Testing
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Yan Jin; Jason Fan – Language Assessment Quarterly, 2023
In language assessment, AI technology has been incorporated in task design, assessment delivery, automated scoring of performance-based tasks, score reporting, and provision of feedback. AI technology is also used for collecting and analyzing performance data in language assessment validation. Research has been conducted to investigate the…
Descriptors: Language Tests, Artificial Intelligence, Computer Assisted Testing, Test Format
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Jiang, Zhuhan; Huang, Jiansheng – IEEE Transactions on Learning Technologies, 2022
Advanced digital technologies and social media have greatly improved both the learning experience and the assessment convenience, while inadvertently facilitated potential plagiarism and collaborative cheating at the same time. In this article, we will focus on the strategies and their technological implementations to run exams, or in-class tests…
Descriptors: Plagiarism, Educational Technology, Computer Assisted Testing, Cheating
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El Asame, Maryam; Wakrim, Mohamed; Battou, Amal – Education and Information Technologies, 2022
E-Assessment, which is a key element in the instructional design process, plays a major role in supporting and enhancing learning. However, the current e-assessment design does not achieve the desired pedagogical objectives in the e-learning environments. In this paper, we propose a hybrid pedagogical framework for e-learning environments, that…
Descriptors: Computer Assisted Testing, Student Evaluation, Teaching Methods, Instructional Design
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