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Ye Ma; Deborah J. Harris – Educational Measurement: Issues and Practice, 2025
Item position effect (IPE) refers to situations where an item performs differently when it is administered in different positions on a test. The majority of previous research studies have focused on investigating IPE under linear testing. There is a lack of IPE research under adaptive testing. In addition, the existence of IPE might violate Item…
Descriptors: Computer Assisted Testing, Adaptive Testing, Item Response Theory, Test Items
Beyza Aksu Dunya; Stefanie Wind – International Journal of Testing, 2025
We explored the practicality of relatively small item pools in the context of low-stakes Computer-Adaptive Testing (CAT), such as CAT procedures that might be used for quick diagnostic or screening exams. We used a basic CAT algorithm without content balancing and exposure control restrictions to reflect low stakes testing scenarios. We examined…
Descriptors: Item Banks, Adaptive Testing, Computer Assisted Testing, Achievement
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
Liandi van den Berg – International Journal for Educational Integrity, 2025
Due to the coronavirus disease 2019 (COVID-2019) and the sudden shift to online learning, higher education institutions adopted various approaches to reduce cheating in online assessments, mainly involving online live proctoring (OLP). The international assessment integrity regulation trend also applied to a university in South Africa, where…
Descriptors: Foreign Countries, College Faculty, College Students, Computer Assisted Testing
Tyler M. Moore; Katherine C. Lopez; J. Cobb Scott; Jack C. Lennon; Akira Di Sandro; Eirini Zoupou; Alesandra Gorgone; Monica E. Calkins; Daniel H. Wolf; Joseph W. Kable; Kosha Ruparel; Raquel E. Gur; Ruben C. Gur – Journal of Psychoeducational Assessment, 2025
The Penn Computerized Neurocognitive Battery (CNB) is a collection of tests validated using neuroimaging, genetics, and other criteria. An updated version of the CNB was constructed in which all tests were converted to either computerized adaptive (CAT) or abbreviated forms. In a mixed community/clinical sample (N = 307; mean age = 25.9 years;…
Descriptors: Computer Assisted Testing, Cognitive Ability, Genetics, Adaptive Testing
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
Lae Lae Shwe; Sureena Matayong; Suntorn Witosurapot – Education and Information Technologies, 2024
Multiple Choice Questions (MCQs) are an important evaluation technique for both examinations and learning activities. However, the manual creation of questions is time-consuming and challenging for teachers. Hence, there is a notable demand for an Automatic Question Generation (AQG) system. Several systems have been created for this aim, but the…
Descriptors: Difficulty Level, Computer Assisted Testing, Adaptive Testing, Multiple Choice Tests
New York State Education Department, 2024
The instructions in this manual explain the responsibilities of school administrators for the New York State Testing Program (NYSTP) Grades 3-8 English Language Arts, Mathematics, and Grades 5 & 8 Science Tests. School administrators must be thoroughly familiar with the contents of the manual, and the policies and procedures must be followed…
Descriptors: Testing Programs, Language Arts, Mathematics Tests, Science Tests
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
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
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
Jonas Flodén – British Educational Research Journal, 2025
This study compares how the generative AI (GenAI) large language model (LLM) ChatGPT performs in grading university exams compared to human teachers. Aspects investigated include consistency, large discrepancies and length of answer. Implications for higher education, including the role of teachers and ethics, are also discussed. Three…
Descriptors: College Faculty, Artificial Intelligence, Comparative Testing, Scoring
Xuelan Qiu; Jimmy de la Torre; You-Gan Wang; Jinran Wu – Educational Measurement: Issues and Practice, 2024
Multidimensional forced-choice (MFC) items have been found to be useful to reduce response biases in personality assessments. However, conventional scoring methods for the MFC items result in ipsative data, hindering the wider applications of the MFC format. In the last decade, a number of item response theory (IRT) models have been developed,…
Descriptors: Item Response Theory, Personality Traits, Personality Measures, Personality Assessment
Mücahit Öztürk – Open Praxis, 2024
This study examined the problems that pre-service teachers face in the online assessment process and their suggestions for solutions to these problems. The participants were 136 pre-service teachers who have been experiencing online assessment for a long time and who took the Foundations of Open and Distance Learning course. This research is a…
Descriptors: Foreign Countries, Preservice Teacher Education, Preservice Teachers, Distance Education
Running out of Time: Leveraging Process Data to Identify Students Who May Benefit from Extended Time
Burhan Ogut; Ruhan Circi; Huade Huo; Juanita Hicks; Michelle Yin – International Electronic Journal of Elementary Education, 2025
This study explored the effectiveness of extended time (ET) accommodations in the 2017 NAEP Grade 8 Mathematics assessment to enhance educational equity. Analyzing NAEP process data through an XGBoost model, we examined if early interactions with assessment items could predict students' likelihood of requiring ET by identifying those who received…
Descriptors: Identification, Testing Accommodations, National Competency Tests, Equal Education