CORE + Prosody

CORE + Prosody is a comprehensive measure of reading fluency that unites accuracy, rate, and prosody of students’ oral reading.

Oral reading fluency is an essential part of reading proficiency1, and is perhaps the most prevalent reading assessment used in classrooms across the U.S.; however, these traditional assessments measure only accuracy and rate, and entirely neglect prosody. Prosody is reading with appropriate expression and phrasing, and is one way a reader demonstrates they understand the meaning of the text. Research has shown prosody to be an important indicator of comprehension, beyond accuracy and rate alone, particularly among developing readers2.

The purpose of CORE + Prosody is to develop and validate an automated scoring system to measure, unite, and scale the accuracy, rate, and prosody in oral reading fluency to be used as a screening and progress monitoring measure for students in Grades 2 through 4.

CORE + Prosody is a four-year project funded by the Institute of Education Sciences (IES), the statistics, research, and evaluation arm of the U.S. Department of Education.

CORE + Prosody has the potential to increase the reliability and validity of decisions made from oral reading fluency assessment scores, resulting in better identification of students in need of reading interventions, and better evaluation of those interventions.

The CORE + Prosody assessment:

Computerized Oral Reading Evaluation - CORE

CORE + Prosody builds upon Computerized Oral Reading Evaluation (CORE), a project that uses (a) shorter passages, (b) automatic speech recognition to score oral reading fluency accuracy and rate, and (c) a latent variable psychometric model to scale, equate, and link scores across Grades 2 through 4 to improve reading outcomes for students across reading proficiency levels. Please visit the CORE project blog for information about the project procedures and results.

Developing Computational Tools for Model-Based Oral Reading Fluency Assessments

Developing Computational Tools for Model-Based Oral Reading Fluency Assessments, led by Principal Investigator Akihito Kamata.

This project expands upon the existing estimation model developed as part of the CORE project to include the development of (a) a sentence-level model that takes into account between-sentence dependency, and (b) incomplete reading. The model parameter estimation algorithms for these extensions will be developed by the method of moments, the Monte Carlo EM algorithm approach, and the Bayesian HMC approach used in the software package Stan.

This project will produce a Shiny app for rendering user-friendly R code needed to estimate model parameters, providing better oral reading fluency score comparability both within- and between-students for better longitudinal and cross-sectional studies, as well as better estimates of measurement errors for oral reading fluency scores. The research team will demonstrate the use of the new software on data collected by the CORE project, and develop web-based tutorials for supporting applied researchers who want to use the Shiny app.

  1. National Reading Panel↩︎

  2. Benjamin & Schwanenflugel (2010); Miller & Schwanenflugel (2006); Valencia et al., (2010); Benjamin et al., (2013)↩︎

  3. Nese & Kamata (2020)↩︎

  4. Kara, Kamata, Potgieter, & Nese (2020)↩︎

  5. Nese & Kamata (2020)↩︎