Monster, P.I. provides valid and reliable written language scores for teachers and administrators (and researchers) as well as detailed scores on the components that make up written language (morphology, vocabulary, and syntax). This helps educators better understand the relationship between written language and literacy— and better understand how a student’s language skills support or hinder his or her literacy skills.
Measuring the things that make up language in a detailed way matters. The Monster, P.I. authors found morphology and vocabulary are best fit by bifactor models that identify performance overall and on specific skills within the constructs. Skills include identification of units of meaning, use of suffixes, wordsolving, and reading/spelling morphologically complex words for morphology and definition, synonym/antonym, analogy, and polysemy for vocabulary. Syntax, though, is best fit unidimensionally.
Monster, P.I. scores link in a meaningful way to reading performance. Specifically, performance on Monster, PI explained more than 50% of variance in standardized reading, suggesting operationalizing written language via Monster, PI can provide meaningful understandings of the relationship between written language and reading comprehension. Specifically, considering just a subset of a construct, like identification of units of meaning, explained significantly less variance in reading comprehension highlighting the importance of considering these broader constructs. Implications indicate a model of written language where component areas are considered broadly and contributions to reading comprehension are explored via general performance on components as well as skill level performance is important for future work.