Hostname: page-component-74656f9884-skzmx Total loading time: 0 Render date: 2026-11-05T13:26:20.981Z Has data issue: false hasContentIssue false

The Revised Hierarchical Model: A critical review and assessment*

Published online by Cambridge University Press:  09 June 2010

JUDITH F. KROLL*
Affiliation:
Department of Psychology, Center for Language Science, Pennsylvania State University, University Park, PA, USA
JANET G. VAN HELL
Affiliation:
Behavioural Science Institute, Radboud University Nijmegen, Nijmegen, the Netherlands and Department of Psychology, Center for Language Science, Pennsylvania State University, University Park, PA, USA
NATASHA TOKOWICZ
Affiliation:
Departments of Psychology and Linguistics, Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, USA
DAVID W. GREEN
Affiliation:
Research Department of Cognitive, Perceptual, and Brain Sciences, University College London, London, UK
*
Address for correspondence: Judith F. Kroll, Department of Psychology, 641 Moore Building, Pennsylvania State University, University Park, PA 16802 USA jfk7@psu.edu
Rights & Permissions [Opens in a new window]

Abstract

Brysbaert and Duyck (this issue) suggest that it is time to abandon the Revised Hierarchical Model (Kroll and Stewart, 1994) in favor of connectionist models such as BIA+ (Dijkstra and Van Heuven, 2002) that more accurately account for the recent evidence on non-selective access in bilingual word recognition. In this brief response, we first review the history of the Revised Hierarchical Model (RHM), consider the set of issues that it was proposed to address and then evaluate the evidence that supports and fails to support the initial claims of the model. Although fifteen years of new research findings require a number of revisions to the RHM, we argue that the central issues to which the model was addressed, the way in which new lexical forms are mapped to meaning and the consequence of language learning history for lexical processing, cannot be accounted for solely within models of word recognition.

Information

Type
Peer Commentaries
Copyright
Copyright © Cambridge University Press 2010