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Cornelis Potgieter; Xin Qiao; Akihito Kamata; Yusuf Kara – Grantee Submission, 2024
As part of the effort to develop an improved oral reading fluency (ORF) assessment system, Kara et al. (2020) estimated the ORF scores based on a latent variable psychometric model of accuracy and speed for ORF data via a fully Bayesian approach. This study further investigates likelihood-based estimators for the model-derived ORF scores,…
Descriptors: Oral Reading, Reading Fluency, Scores, Psychometrics
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Ethan R. Van Norman; David A. Klingbeil; Kristen Truman; Peter M. Nelson; David C. Parker – Grantee Submission, 2024
The transition from sounding out unfamiliar words to effortlessly reading connected text does not occur all at once nor at the same rate for students. The purpose of this study was to explore the accuracy of three decision rules (data point, median, and trend line) applied to progress monitoring outcomes of alphabetic principle (nonsense word…
Descriptors: Progress Monitoring, Outcomes of Education, Reading Rate, Word Recognition
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Nese, Joseph F. T.; Alonzo, Julie; Kamata, Akihito – Grantee Submission, 2016
The purpose of this study was to compare traditional oral reading fluency (ORF) measures to a computerized oral reading evaluation (CORE) system that uses speech recognition software. We applied a mixed model approach with two within-subject variables to test the mean WCPM score differences and the error rates between: passage length (25, 50, 85,…
Descriptors: Text Structure, Oral Reading, Reading Fluency, Reading Tests
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Nese, Joseph F. T.; Kamata, Akihito; Alonzo, Julie – Grantee Submission, 2015
Assessing reading fluency is critical because it functions as an indicator of comprehension and overall reading achievement. Although theory and research demonstrate the importance of ORF proficiency, traditional ORF assessment practices are lacking as sensitive measures of progress for educators to make instructional decisions. The purpose of…
Descriptors: Oral Reading, Reading Fluency, Accuracy, Reading Rate