Predictive coding theories suggest that core symptoms in autism spectrum disorders (ASD) may stem from atypical mechanisms of perceptual inference (i.e., inferring the hidden causes of sensations). Specifically, there would be an imbalance in the precision or weight ascribed to sensory inputs relative to prior expectations. Using three tactile…

Reading comprehension is key to knowledge acquisition and to reinforcing memory for previous information. While reading, a mental representation is constructed in the reader's mind. The mental model comprises the words in the text, the relations between the words, and inferences linking to concepts in prior knowledge. The automated model of…

Research with school-age readers suggests that the contributions of reading and language skills vary across reading comprehension assessments and proficiency levels. With a sample of 168 struggling adult readers, we estimated the explanatory effects of decoding, oral vocabulary, listening comprehension, fluency, background knowledge, and…

Research with school-age readers suggests that the contributions of reading and language skills vary across reading comprehension assessments and proficiency levels. With a sample of 168 struggling adult readers, we estimated the explanatory effects of decoding, oral vocabulary, listening comprehension, fluency, background knowledge, and…

A large body of work has demonstrated that reader resources influence inference processes and comprehension, but few models of comprehension have accounted for such resources. The Direct and Mediational Inference model of comprehension (DIME) assumes that general inference processes mediate the effects of reader resources on general comprehension…

A large body of work has demonstrated that reader resources influence inference processes and comprehension, but few models of comprehension have accounted for such resources. The Direct and Mediational Inference model of comprehension (DIME) assumes that general inference processes mediate the effects of reader resources on general comprehension…

How does the visual system recognize images of a novel object after a single observation despite possible variations in the viewpoint of that object relative to the observer? One possibility is comparing the image with a prototype for invariance over a relevant transformation set (e.g., translations and dilations). However, invariance over…

It is unclear how children learn labels for multiple overlapping categories such as "Labrador," "dog," and "animal." Xu and Tenenbaum (2007a) suggested that learners infer correct meanings with the help of Bayesian inference. They instantiated these claims in a Bayesian model, which they tested with preschoolers and…

In this thesis, we study the importance of background knowledge in relation extraction systems. We not only demonstrate the benefits of leveraging background knowledge to improve the systems' performance but also propose a principled framework that allows one to effectively incorporate knowledge into statistical machine learning models for…

A dual-source model of probabilistic conditional inference is proposed. According to the model, inferences are based on 2 sources of evidence: logical form and prior knowledge. Logical form is a decontextualized source of evidence, whereas prior knowledge is activated by the contents of the conditional rule. In Experiments 1 to 3, manipulations of…

Failure to "activate" relevant, existing background knowledge may be a cause of poor reading comprehension. This failure may cause particular problems with inferences that depend heavily on prior knowledge. Conversely, teaching how to use background knowledge in the context of gap-filling inferences could improve reading comprehension in…

Everyday inductive inferences are often guided by rich background knowledge. Formal models of induction should aim to incorporate this knowledge and should explain how different kinds of knowledge lead to the distinctive patterns of reasoning found in different inductive contexts. This article presents a Bayesian framework that attempts to meet…

This paper reports on findings based on analyses of a unique dataset collected by ACT that includes information on student achievement in a variety of subjects at the high school level, which allow us to examine the relationship between teacher effect estimates derived from VAM specifications employing different student learning assumptions.…

Inferences are important because not everything in the text is explicit. Therefore, the reader must generate inferences that fill in "missing" information. Various factors can influence inference processes, including those that are related to the text and reader. Moreover, these two factors are likely to interact in highly complex ways,…

In this study, we are interested to see the impact of self-discipline on students' knowledge and learning. Self-discipline can influence both learning rate as well as knowledge accumulation over time. We used a Knowledge Tracing (KT) model to make inferences about students' knowledge and learning. Based on a widely used questionnaire, we measured…