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Selcuk Acar; Peter Organisciak; Denis Dumas – Journal of Creative Behavior, 2025
In this three-study investigation, we applied various approaches to score drawings created in response to both Form A and Form B of the Torrance Tests of Creative Thinking-Figural (broadly TTCT-F) as well as the Multi-Trial Creative Ideation task (MTCI). We focused on TTCT-F in Study 1, and utilizing a random forest classifier, we achieved 79% and…
Descriptors: Scoring, Computer Assisted Testing, Models, Correlation
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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
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Peter Baldwin; Victoria Yaneva; Kai North; Le An Ha; Yiyun Zhou; Alex J. Mechaber; Brian E. Clauser – Journal of Educational Measurement, 2025
Recent developments in the use of large-language models have led to substantial improvements in the accuracy of content-based automated scoring of free-text responses. The reported accuracy levels suggest that automated systems could have widespread applicability in assessment. However, before they are used in operational testing, other aspects of…
Descriptors: Artificial Intelligence, Scoring, Computational Linguistics, Accuracy
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Ebru Balta; Arzu Uçar – International Journal of Assessment Tools in Education, 2025
Unproctored Computerized Adaptive Testing (CAT) is gaining traction due to its convenience, flexibility, and scalability, particularly in high-stakes assessments. However, the lack of proctor can give rise to aberrant testing behavior. These behaviors can impair the validity of test scores. This paper explores the use of a verification test to…
Descriptors: Adaptive Testing, Computer Assisted Testing, Paper and Pencil Tests, Test Validity
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Mounia Machkour; Latifa Lamalif; Sophia Faris; Khalifa Mansouri – Educational Process: International Journal, 2025
Background/purpose: This study addresses the problem of demotivation generated by traditional assessment methods, which are often standardized, unengaging, and ill-suited to individual differences. In an increasingly digitized educational context, the primary objective is to assess the ability of an adaptive assessment system, developed on the…
Descriptors: Foreign Countries, High School Seniors, Student Evaluation, Student Motivation
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Chioma Udeozor; Fernando Russo Abegão; Jarka Glassey – British Journal of Educational Technology, 2024
Digital games (DGs) have the potential to immerse learners in simulated real-world environments that foster contextualised and active learning experiences. These also offer opportunities for performance assessments by providing an environment for students to carry out tasks requiring the application of knowledge and skills learned in the…
Descriptors: Educational Technology, Computer Assisted Testing, Game Based Learning, Test Construction
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Karyssa A. Courey; Frederick L. Oswald; Steven A. Culpepper – Practical Assessment, Research & Evaluation, 2024
Historically, organizational researchers have fully embraced frequentist statistics and null hypothesis significance testing (NHST). Bayesian statistics is an underused alternative paradigm offering numerous benefits for organizational researchers and practitioners: e.g., accumulating direct evidence for the null hypothesis (vs. 'fail to reject…
Descriptors: Bayesian Statistics, Statistical Distributions, Researchers, Institutional Research
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Pauline Frizelle; Ana Buckley; Tricia Biancone; Anna Ceroni; Darren Dahly; Paul Fletcher; Dorothy V. M. Bishop; Cristina McKean – Journal of Child Language, 2024
This study reports on the feasibility of using the Test of Complex Syntax- Electronic (TECS-E), as a self-directed app, to measure sentence comprehension in children aged 4 to 5 ½ years old; how testing apps might be adapted for effective independent use; and agreement levels between face-to-face supported computerized and independent computerized…
Descriptors: Language Processing, Computer Software, Language Tests, Syntax
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Chen, Fu; Lu, Chang; Cui, Ying; Gao, Yizhu – IEEE Transactions on Learning Technologies, 2023
Learning outcome modeling is a technical underpinning for the successful evaluation of learners' learning outcomes through computer-based assessments. In recent years, collaborative filtering approaches have gained popularity as a technique to model learners' item responses. However, how to model the temporal dependencies between item responses…
Descriptors: Outcomes of Education, Models, Computer Assisted Testing, Cooperation
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Henderson, Michael; Chung, Jennifer; Awdry, Rebecca; Ashford, Cliff; Bryant, Mike; Mundy, Matthew; Ryan, Kris – International Journal for Educational Integrity, 2023
Discussions around assessment integrity often focus on the exam conditions and the motivations and values of those who cheated in comparison with those who did not. We argue that discourse needs to move away from a binary representation of cheating. Instead, we propose that the conversation may be more productive and more impactful by focusing on…
Descriptors: College Students, Computer Assisted Testing, Cheating, Ambiguity (Semantics)
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Okan Bulut; Doyoung Kim – Journal of Applied Testing Technology, 2023
The development of a Computerized Adaptive Test (CAT) for operational use begins with several important steps, such as creating a large-size item bank, piloting the items on a sizable and representative sample of examinees, dimensionality assessment of the item bank, and estimation of item parameters. Among these steps, testing the dimensionality…
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Banks, Statistical Analysis
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George Kinnear; Paola Iannone; Ben Davies – Educational Studies in Mathematics, 2025
Example-generation tasks have been suggested as an effective way to both promote students' learning of mathematics and assess students' understanding of concepts. E-assessment offers the potential to use example-generation tasks with large groups of students, but there has been little research on this approach so far. Across two studies, we…
Descriptors: Mathematics Skills, Learning Strategies, Skill Development, Student Evaluation
Victoria Crisp; Sylvia Vitello; Abdullah Ali Khan; Heather Mahy; Sarah Hughes – Research Matters, 2025
This research set out to enhance our understanding of the exam techniques and types of written annotations or markings that learners may wish to use to support their thinking when taking digital multiple-choice exams. Additionally, we aimed to further explore issues around the factors that contribute to learners writing less rough work and…
Descriptors: Computer Assisted Testing, Test Format, Multiple Choice Tests, Notetaking
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Angela Chamberlain; Emily D'Arcy; Andrew J. O. Whitehouse; Kerry Wallace; Maya Hayden-Evans; Sonya Girdler; Benjamin Milbourn; Sven Bölte; Kiah Evans – Journal of Autism and Developmental Disorders, 2025
Purpose: The PEDI-CAT (ASD) is used to assess functioning of children and youth on the autism spectrum; however, current psychometric evidence is limited. This study aimed to explore the reliability, validity and acceptability of the PEDI-CAT (ASD) using a large Australian sample. Methods: Caregivers of 134 children and youth on the spectrum…
Descriptors: Autism Spectrum Disorders, Children, Youth, Test Reliability
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Kylie Gorney; Mark D. Reckase – Journal of Educational Measurement, 2025
In computerized adaptive testing, item exposure control methods are often used to provide a more balanced usage of the item pool. Many of the most popular methods, including the restricted method (Revuelta and Ponsoda), use a single maximum exposure rate to limit the proportion of times that each item is administered. However, Barrada et al.…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Item Banks
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