Formative assessment measures are commonly used in schools to assess early literacy skills as indicators of reading acquisition and to design instruction accordingly. The purpose of this research was to investigate the incremental predictive validity of formative assessment measures of reading comprehension. It was hypothesized that formative measures of reading comprehension will contribute more to our understanding of students' overall reading abilities than simply Oral Reading Fluency (ORF). It was also hypothesized that these measures can be modeled in a meaningful way to explain student performance on criterion measures of academic competence. Four formative measures of reading comprehension---Maze (MZ), Retell Fluency (RTF), Written Retell (WRT), and Sentence Verification Technique (SVT)---were used to measure unique aspects of reading comprehension through production-type responses in an efficient and instructionally meaningful way. The Group Reading Assessment and Diagnostic Evaluation (GRADE) was used as a measure of overall reading proficiency while the Massachusetts Comprehensive Assessment System (MCAS) was used as a measure of academic competence. Data were collected from 111 fourth grade students from two Western Massachusetts elementary schools. Four multiple regression equations were computed to test the hypothesis that measures of reading comprehension will contribute more to our understanding of reading proficiency than ORF alone. Each measure significantly predicted performance on GRADE above and beyond that predicted by ORF. A larger multiple regression equation was used to evaluate which measure predicted a unique and significant proportion of the variance in reading proficiency. The MZ, SVT and WRT were significant predictors in the model. Using the measures found to be significant with ORF, a logistic regression analysis was computed to evaluate how reliably the newly constructed model predicted a pass or fail status on the fourth grade English Language Arts section of MCAS. None of the predictors were significant. An additional multiple regression analysis was computed to predict MCAS performance and the newly constructed model of reading proficiency. This model predicted approximately .66 of the variability in MCAS performance.
| Identifer | oai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:dissertations-4340 |
| Date | 01 January 2006 |
| Creators | Marcotte, Amanda M |
| Publisher | ScholarWorks@UMass Amherst |
| Source Sets | University of Massachusetts, Amherst |
| Language | English |
| Detected Language | English |
| Type | text |
| Source | Doctoral Dissertations Available from Proquest |
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