Measuring Inferential Integrative Reasoning Using Modern Objective Measurement
Alexander Mario Blum · Proceedings of the 2019 AERA Annual Meeting · 2019
We constructed a new taxonomy for inferential thinking, a construct called integrative inferential reasoning (IIR).IIR extends Pearson and Johnson's (1978) framework of text-implicit and script-implicit inferences, and integrates several other prominent literacy theories to form a unified inferential reasoning construct.We validated our construct using a researcher-made IIR instrument which was administered to 72 participants.Participants answered open-ended inference questions about various aspects of visual narratives presented in comic-strip format.We categorized participants' responses as exemplifying one of the levels of IIR: text-implicit, script-implicit, or a combination of both.We used item response models to validate the ordinal nature of IIR, and its structure.Specifically, we fit Masters' (1982) Partial Credit Model and obtained a Wright map, mean location data, fit statistics, and reliability estimates.Results confirmed that the IIR construct behaves ordinally.Additionally, age was found to be a reliable predictor of IIR, and item types (each modeled as a separate dimension) were found to have reasonable latent correlations between the dimensions.This research provides important insights for teaching and assessing narrative comprehension, and demonstrates a good example of using modern objective measurement methods.