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Mustafa Yildiz; Hasan Kagan Keskin; Saadin Oyucu; Douglas K. Hartman; Murat Temur; Mücahit Aydogmus – Reading & Writing Quarterly, 2025
This study examined whether an artificial intelligence-based automatic speech recognition system can accurately assess students' reading fluency and reading level. Participants were 120 fourth-grade students attending public schools in Türkiye. Students read a grade-level text out loud while their voice was recorded. Two experts and the artificial…
Descriptors: Artificial Intelligence, Reading Fluency, Human Factors Engineering, Grade 4
Qian, Hong; Staniewska, Dorota; Reckase, Mark; Woo, Ada – Educational Measurement: Issues and Practice, 2016
This article addresses the issue of how to detect item preknowledge using item response time data in two computer-based large-scale licensure examinations. Item preknowledge is indicated by an unexpected short response time and a correct response. Two samples were used for detecting item preknowledge for each examination. The first sample was from…
Descriptors: Reaction Time, Licensing Examinations (Professions), Computer Assisted Testing, Prior Learning
Colwell, Nicole Makas – Journal of Education and Training Studies, 2013
This paper highlights the current findings and issues regarding the role of computer-adaptive testing in test anxiety. The computer-adaptive test (CAT) proposed by one of the Common Core consortia brings these issues to the forefront. Research has long indicated that test anxiety impairs student performance. More recent research indicates that…
Descriptors: Test Anxiety, Computer Assisted Testing, Evaluation Methods, Standardized Tests

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