Adult literacy learners are characterized by their diversity, both in terms of educational histories and cognitive skill sets. Accounting for the specific strengths and weaknesses of each learner is vital to the assessment of literacy gains and optimization of educational systems. We examined pre- and post-difference scores on a component reading…

We propose that machine-learned computational models (MLCMs), in which the model parameters and perhaps even structure are learned from data, can complement extant approaches to the study of text and discourse. Such models are particularly useful when theoretical understanding is insufficient, when the data are rife with nonlinearities and…

Two studies attempt to determine the causes of poor metacomprehension accuracy and then, in turn, to identify interventions that circumvent these difficulties to support effective comprehension monitoring performance. The first study explored the cues that both at-risk and typical college readers use as a basis for their metacomprehension…