Errors and Intelligence in Computer-Assisted Language Learning
Parsers and Pedagogues
Published on 13. November 2007
304 pages
978-1-134-23356-4 (ISBN)
Description
This book provides the first comprehensive overview of theoretical issues, historical developments and current trends in ICALL (Intelligent Computer-Assisted Language Learning). It assumes a basic familiarity with Second Language Acquisition (SLA) theory and teaching, CALL and linguistics. It is of interest to upper undergraduate and/or graduate students who study CALL, SLA, language pedagogy, applied linguistics, computational linguistics or artificial intelligence as well as researchers with a background in any of these fields.
Reviews / Votes
"A must-read for any computational linguist intending to start work in the field of CALL."Computational Linguistics
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Illustrations
29 Tables, black and white; 34 Line drawings, black and white
File size
3,44 MB
ISBN-13
978-1-134-23356-4 (9781134233564)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Trude Heift | Mathias Schulze
Errors and Intelligence in Computer-Assisted Language Learning
Parsers and Pedagogues
Book
02/2012
1st Edition
Routledge
€57.60
Shipment within 15-20 days
Trude Heift | Mathias Schulze
Errors and Intelligence in Computer-Assisted Language Learning
Parsers and Pedagogues
Book
06/2007
1st Edition
Routledge
€141.80
Shipment within 15-20 days
Persons
Trude Heift is Associate Professor of Linguistics and Associate Dean of Graduate Studies at Simon Fraser University in Canada.
Mathias Schulze is Associate Professor of German at the University of Waterloo in Canada.
Mathias Schulze is Associate Professor of German at the University of Waterloo in Canada.
Content
1. Introduction 2. NLP in CALL 3. Error Analysis and Description 4. Feedback 5. Student Modeling 6. The Past and the Future
