Curriculum-Based Measurement of Reading: An Evaluation of Frequentist and Bayesian Methods to Model Progress Monitoring Data

Theodore J. Christ, Christopher David Desjardins

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Curriculum-Based Measurement of Oral Reading (CBM-R) is often used to monitor student progress and guide educational decisions. Ordinary least squares regression (OLSR) is the most widely used method to estimate the slope, or rate of improvement (ROI), even though published research demonstrates OLSR’s lack of validity and reliability, and imprecision of ROI estimates, especially after brief duration of monitoring (6-10 weeks). This study illustrates and examines the use of Bayesian methods to estimate ROI. Conditions included four progress monitoring durations (6, 8, 10, and 30 weeks), two schedules of data collection (weekly, biweekly), and two ROI growth distributions that broadly corresponded with ROIs for general and special education populations. A Bayesian approach with alternate prior distributions for the ROIs is presented and explored. Results demonstrate that Bayesian estimates of ROI were more precise than OLSR with comparable reliabilities, and Bayesian estimates were consistently within the plausible range of ROIs in contrast to OLSR, which often provided unrealistic estimates. Results also showcase the influence the priors had estimated ROIs and the potential dangers of prior distribution misspecification.

Original languageEnglish (US)
Pages (from-to)55-73
Number of pages19
JournalJournal of Psychoeducational Assessment
Volume36
Issue number1
DOIs
StatePublished - Feb 1 2018

Bibliographical note

Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research reported here was supported by the Institute of Education Sciences, U.S. Department of Education, through Grant R324A130161 to the University of Minnesota.

Publisher Copyright:
© 2017, © The Author(s) 2017.

Keywords

  • assessment
  • assessment of interventions/outcomes
  • bayesian
  • curriculum-based assessment
  • curriculum-based measurement
  • diagnosis
  • education assessment
  • measurement
  • progress monitor
  • response to intervention (RtI), multitiered system of supports (MTSS)

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