Joseph Nese

The purpose of this study is to expand the existing estimation model available in a computer-based oral reading fluency (ORF) assessment which was developed as part of a previous IES grant (R305A140203). The extensions of the previous model will include the development of a sentence-level model that takes into account between-sentence dependency and incomplete reading.

The research team will develop and validate an automated scoring system to measure, unite, and scale the rate, accuracy, and prosody of oral reading fluency (ORF) for students in grades 2 to 4. Research has shown that prosody explains variance in reading comprehension beyond rate and accuracy; however, current ORF assessments neglect the measurement of prosody. This project can increase the reliability and validity of decisions made from ORF scores, resulting in better identification of stud...

  The University of Oregon sought to develop and validate a new computerized assessment system of oral reading fluency (ORF) for use with students in Grades 2 through 4, called Computerized Oral Reading Evaluation (CORE). CORE contains an automated scoring algorithm based on a speech recognition engine, shorter passages, and a latent variable psychometric model, collecting word-level data that are used in a model-based approach to scale ORF scores with increased reliability compared to trad...

This postdoctoral fellowship program trained five fellows to conduct research on in measurement tools used to document progress with learning to read and solve mathematics problems in U.S. elementary and middle schools.