Text comprehension is an essential skill in today's information-rich world, and self-explanation practice helps students improve their understanding of complex texts. This study was centered on leveraging open-source Large Language Models (LLMs), specifically FLAN-T5, to automatically assess the comprehension strategies employed by readers while…

The morphological structure of complex words impacts how they are processed during visual word recognition. This impact varies over the course of reading acquisition and for different languages and writing systems. Many theories of morphological processing rely on a decomposition mechanism, in which words are decomposed into explicit…

We conducted a broad-coverage investigation of the effects of syntactic distance and word order on language processing against a dependency-annotated reading time corpus of English. A combined method of quantitative syntax and psycholinguistic analyses was adopted to yield converging evidence. It was found that (i) head-initial structures allow…

Learning new words is fundamental in both first and second-language reading. There are, however, divided opinions on the best instructional approaches. Two widely used approaches across languages are whole-word focus and word-constituent focus. The appropriateness of each approach has varied historically, even within a single language (e.g., the…

Although text readability has traditionally been measured based on simple linguistic features, recent studies have employed natural language processing techniques to develop new readability formulas that better represent theoretical accounts of reading processes. This study evaluated the construct validity of different readability formulas,…

We present computational modeling results based on a self-paced reading study investigating number attraction effects in Eastern Armenian. We implement three novel computational models of agreement attraction in a Bayesian framework and compare their predictive fit to the data using k-fold cross-validation. We find that our data are better…

Ambridge reviews and augments an impressive body of research demonstrating both the advantages and the necessity of an exemplar-based model of knowledge of one's language. He cites three computational models that have been applied successfully to issues of phonology and morphology. Focusing on Ambridge's discussion of sentence-level constructions,…

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…

Classic accounts of lexical organization posit that humans are sensitive to environmental frequency, suggesting a mechanism for word learning based on repetition. However, a recent spate of evidence has revealed that it is not simply frequency but the diversity and distinctiveness of contexts in which a word occurs that drives lexical…

Research has identified a number of linguistic features that influence the reading comprehension of young readers; yet, less is known about whether and how these findings extend to adult readers. This study examines text comprehension, processing, and familiarity judgment provided by adult readers using a number of different approaches (i.e.,…

The processing difficulty of nested grammatical structure has been explained by different psycholinguistic theories. Here I provide corpus and behavioral evidence in favor of usage-based models, focusing on the case of object relative clauses in Spanish as a first language. A corpus analysis of spoken Spanish reveals that, as in English, the…

It is often assumed that graphemes are a crucial level of orthographic representation above letters. Current connectionist models of reading, however, do not address how the mapping from letters to graphemes is learned. One major challenge for computational modeling is therefore developing a model that learns this mapping and can assign the…

Learning to read in any language requires learning to map among print, sound and meaning. Writing systems differ in a number of factors that influence both the ease and the rate with which reading skill can be acquired, as well as the eventual division of labor between phonological and semantic processes. Further, developmental reading disability…

The Parallel Distributed Processing (PDP) framework has significant potential for producing models of cognitive tasks that approximate how the brain performs the same tasks. To date, however, there has been relatively little contact between PDP modeling and data from cognitive neuroscience. In an attempt to advance the relationship between…

Over the last decade, there has been increasing evidence for syllabic processing during visual word recognition. If syllabic effects prove to be independent from orthographic redundancy, this would seriously challenge the ability of current computational models to account for the processing of polysyllabic words. Three experiments are presented to…