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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
Urrutia, Felipe; Araya, Roberto – Journal of Educational Computing Research, 2024
Written answers to open-ended questions can have a higher long-term effect on learning than multiple-choice questions. However, it is critical that teachers immediately review the answers, and ask to redo those that are incoherent. This can be a difficult task and can be time-consuming for teachers. A possible solution is to automate the detection…
Descriptors: Elementary School Students, Grade 4, Elementary School Mathematics, Mathematics Tests
L. Hannah; E. E. Jang; M. Shah; V. Gupta – Language Assessment Quarterly, 2023
Machines have a long-demonstrated ability to find statistical relationships between qualities of texts and surface-level linguistic indicators of writing. More recently, unlocked by artificial intelligence, the potential of using machines to identify content-related writing trait criteria has been uncovered. This development is significant,…
Descriptors: Validity, Automation, Scoring, Writing Assignments