Weighing the Value of Complex Growth Estimation Methods to Evaluate Individual Student Response to Instruction

Abstract

Sophisticated analytic strategies have been proposed as viable methods to improve the quantification of student improvement and to assist educators in making treatment decisions. The performance of three categories of latent growth modeling techniques (linear, quadratic, and dual change) to capture growth in oral reading fluency in response to a 12-week structured supplemental reading intervention among 280 grade three students at-risk for learning disabilities were compared. Although the most complex approach (dual-change) yielded the best model fit indices, there were few practical differences between predicted values from simpler linear models. A discussion to carefully consider the relative benefits and appropriateness of increasingly complex growth modeling strategies to evaluate individual student responses to intervention is offered.