Kathleen Rastle

Bio: Kathleen Rastle is an academic researcher from Royal Holloway, University of London. The author has contributed to research in topics: Reading (process) & Priming (psychology). The author has an hindex of 38, co-authored 100 publications receiving 9519 citations. Previous affiliations of Kathleen Rastle include Pomona College & University of Cambridge.

DRC: a dual route cascaded model of visual word recognition and reading aloud.

Abstract: This article describes the Dual Route Cascaded (DRC) model, a computational model of visual word recognition and reading aloud. The DRC is a computational realization of the dual-route theory of reading, and is the only computational model of reading that can perform the 2 tasks most commonly used to study reading: lexical decision and reading aloud. For both tasks, the authors show that a wide variety of variables that influence human latencies influence the DRC model's latencies in exactly the same way. The DRC model simulates a number of such effects that other computational models of reading do not, but there appear to be no effects that any other current computational model of reading can simulate but that the DRC model cannot. The authors conclude that the DRC model is the most successful of the existing computational models of reading.

The broth in my brother's brothel: morpho-orthographic segmentation in visual word recognition.

Abstract: Much research suggests that words comprising more than one morpheme are represented in a “decomposed” manner in the visual word recognition system. In the research presented here, we investigate what information is used to segment a word into its morphemic constituents and, in particular, whether semantic information plays a role in that segmentation. Participants made visual lexical decisions to stem targets preceded by masked primes sharing (1) a semantically transparent morphological relationship with the target (e.g.,cleaner-CLEAN), (2) an apparent morphological relationship but no semantic relationship with the target (e.g.,corner-CORN), and (3) a nonmorphological form relationship with the target (e.g.,brothel-BROTH). Results showed significant and equivalent masked priming effects in cases in which primes and targets appeared to be morphologically related, and priming in these conditions could be distinguished from nonmorphological form priming. We argue that these findings suggest a level of representation at which apparently complex words are decomposed on the basis of their morpho-orthographic properties. Implications of these findings for computational models of reading are discussed.

358,534 nonwords: The ARC Nonword Database

Abstract: The authors present a model of the phonotactic and orthographic constraints of Australian and Standard Southern British English monosyllables. This model is used as the basis for a web-based psycholinguistic resource, the ARC Nonword Database, which contains 358,534 monosyllabic nonwords—48,534 pseudohomophones and 310,000 non-pseudohomophonic nonwords. Items can be selected from the ARC Nonword Database on the basis of a wide variety of properties known or suspected to be of theoretical importance for the investigation of reading.

Morphological and semantic effects in visual word recognition: A time-course study

Abstract: Some theories of visual word recognition postulate that there is a level of processing or representation at which morphemes are treated differently fromwhole words. Support for these theories has been derived frompriming experiments in which the recognition of a target word is facilitated by the prior presentation of a morphologically related prime (departure-DEPART). In English, such facilitation could be due to morphological relatedness, or to some combination of the orthographic and semantic relatedness characteristic of derivationally related words. We report two sets of visual priming experiments in which the morphological, semantic, and orthographic relationships between primes and targets are varied in three SOA conditions (43 ms, 72 ms, and 230 ms). Results showed that morphological structure plays a significant role in the early visual recognitionof English words that is independent of both semantic and orthographic relatedness. Findings are discussed in terms of current approaches to morphologic...

Ending the reading wars: reading acquisition from novice to expert

Abstract: There is intense public interest in questions surrounding how children learn to read and how they can best be taught. Research in psychological science has provided answers to many of these questio...

Modern Applied Statistics With S

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Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

Abstract: 1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

DRC: a dual route cascaded model of visual word recognition and reading aloud.

Abstract: This article describes the Dual Route Cascaded (DRC) model, a computational model of visual word recognition and reading aloud. The DRC is a computational realization of the dual-route theory of reading, and is the only computational model of reading that can perform the 2 tasks most commonly used to study reading: lexical decision and reading aloud. For both tasks, the authors show that a wide variety of variables that influence human latencies influence the DRC model's latencies in exactly the same way. The DRC model simulates a number of such effects that other computational models of reading do not, but there appear to be no effects that any other current computational model of reading can simulate but that the DRC model cannot. The authors conclude that the DRC model is the most successful of the existing computational models of reading.

Understanding normal and impaired word reading: computational principles in quasi-regular domains.

Abstract: A connectionist approach to processing in quasi-regular domains, as exemplified by English word reading, is developed. Networks using appropriately structured orthographic and phonological representations were trained to read both regular and exception words, and yet were also able to read pronounceable nonwords as well as skilled readers. A mathematical analysis of a simplified system clarifies the close relationship of word frequency and spelling-sound consistency in influencing naming latencies. These insights were verified in subsequent simulations, including an attractor network that accounted for latency data directly in its time to settle on a response. Further analyses of the ability of networks to reproduce data on acquired surface dyslexia support a view of the reading system that incorporates a graded division of labor between semantic and phonological processes, and contrasts in important ways with the standard dual-route account.